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  • 1. Abdul Rashid, S. H.
    et al.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Human Values: Increasing importance in the automotive production systems2001Conference paper (Refereed)
  • 2.
    Carlsson, Linnea
    et al.
    University West, School of Business, Economics and IT, Divison of Informatics.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    Eriksson, Kristina
    University West, Department of Engineering Science, Division of Production Systems.
    Taking Responsibility for Industrial Digitalization: Navigating Organizational Challenges2022In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 2, p. 866-866Article in journal (Refereed)
    Abstract [en]

    In this article, an employee perspective has been applied in aiming to explore how organizations face challenges and take responsibility for industrial digitalization, thus extending the research on the human-centric perspective in relation to Industry 4.0 technologies. To give emphasis to the human-centric perspective, the co-workership wheel was applied to identify and analyze data. The findings of an explorative longitudinal qualitative case study consisting of 35 in-depth interviews with informants from a manufacturing company were used. Additional data collection consisted of documents and project meetings. By applying a human-centric perspective, llessons learned from this case study show that taking responsibility for industrial digitalization is challenging and the importance of an adaptive organizational culture and a focus on learning and competence are crucial. We argue that the findings give useful implications for manufacturing organizations navigating the challenges of industrial digitalization to sense and seize the benefits of Industry 4.0 technologies.

    Download full text (pdf)
    fulltext
  • 3.
    de Blanche, Andreas
    et al.
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Belenki, Stanislav
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Lundh Snis, Ulrika
    University West, School of Business, Economics and IT, Divison of Informatics.
    Hattinger, Monika
    University West, Department of Engineering Science, Division of Production Systems.
    Artificial and human aspects of Industry 4.0: an industrial work-integrated-learning research agenda2021In: VILÄR: 9-10 of December, 2021, University West, Trollhättan, 2021Conference paper (Other academic)
    Abstract [en]

    The manufacturing industry is currently under extreme pressure to transform their organizations and competencies to reap the benefits of industry 4.0. The main driver for industry 4.0 is digitalization with disruptive technologies such as artificial intelligence, machine learning, internet of things, digital platforms, etc. Industrial applications and research studies have shown promising results, but they rarely involve a human-centric perspective. Given this, we argue there is a lack of knowledge on how disruptive technologies take part in human decision-making and learning practices, and to what extent disruptive technologies may support both employees and organizations to “learn”. In recent research the importance and need of including a human-centric perspective in industry 4.0 is raised including a human learning and decision-making approach. Hence, disruptive technologies, by themselves, no longer consider to solve the actual problems.

    Considering the richness of this topic, we propose an industrial work-integrated-learning research agenda to illuminate a human-centric perspective in Industry 4.0. This work-in-progress literature review aims to provide a research agenda on what and how application areas are covered in earlier research. Furthermore, the review identifies obstacles and opportunities that may affect manufacturing to reap the benefits of Industry 4.0. As part of the research, several inter-disciplinary areas are identified, in which industrial work-integrated-learning should be considered to enhance the design, implementation, and use of Industry 4.0 technologies. In conclusion, this study proposes a research agenda aimed at furthering research on how industrial digitalization can approach human and artificial intelligence through industrial work-integrated-learning for a future digitalized manufacturing.

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    VILÄR 2021
  • 4.
    Eriksson, Kristina. M.
    University West, Department of Technology, Mathematics and Computer Science, Division for Mechanical Engineering.
    A comparison of changeover time reduction through design changes and changeover sensitive heuristics2007In: PLANs forsknings- och tillämpningskonferens 2007: kundfokuserade varor och tjänster : artiklar från konferensen på Tekniska högskolan i Jönköping 5-6 september 2007, PLAN - Logistikföreningen , 2007, p. 51-66Conference paper (Refereed)
  • 5.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    An investigation of change over sensitive heuristics in an industrial job shop environment2006Doctoral thesis, monograph (Other academic)
    Abstract [en]

    The research in this thesis has investigated scheduling and Changeover Sensitive Heuristics (CSHs). The overall aim was to investigate the relationship between scheduling and changeovers and to develop and examine new scheduling heuristics that are intelligent enough to optimise both due dates and changeover requirements. Two new heuristics that incorporated the sequencing of jobs both according to product families and sub-product families were introduced. The new heuristics are named CSH12 and CSH12-K. A body of case studies have been undertaken. These are based on extensive data collected from the key collaborating company. In order to create generic data sets for a job shop environment, the case studies were extended to incorporate a range of parameters, such as several levels of processing times and job grouping strategies. Through discrete event simulation studies, the performance of the new heuristics has been compared to simple heuristics, semi-heuristics and existing changeover sensitive heuristics. In total, ten heuristics and two semi-heuristics were investigated. Scheduling according to product family (CSH1) compared to subproduct family (CSH2) was also studied and it is concluded that sub-product family sequencing performance better. Overall the new heuristics CSH12 and CSH12-Kshow a worthy performance and can reduce the changeover time the most through effective sequencing in a job shop environment with longer and shorter processing times. The research has also concluded that exhaustive heuristics perform better than non-exhaustive heuristics. Furthermore, CSHs are particularly effective for shorter processing times. This suggests that the choice of heuristic is more important for amix of jobs with shorter processing times. Or the reverse, a mix of jobs with comparatively long processing times is less sensitive to the choice of heuristic.

    Additionally, the research revealed that product families with overall longer processing times result in higher percentage of tardy jobs. Thus, suggesting that dissimilar due date setting is beneficial for different product families. The research has determined the importance of considering appropriate scheduling and sequencing approaches, especially when changeovers have been addressed through design and organisational changes. The application of CSHs has demonstrated that an increase of jobs into the shop is possible. Hence, applying CSHs will achieve a strong competitive advantage.

  • 6.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Book Review "Planning and scheduling in manufacturing and services". Author: Michael L. Pinedo2005In: Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, ISSN 0954-4054, E-ISSN 2041-2975, Vol. 19, no B11, p. 849-850Article, book review (Other academic)
  • 7.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    “Book Review –Scheduling algorithms – Author: Brucker, Peter”.2004In: Proceedings of the Institution of mechanical engineers. Part B, journal of engineering manufacture, ISSN 0954-4054, E-ISSN 2041-2975, Vol. 218, no B12, p. 1845-1845Article, book review (Other academic)
  • 8.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Alsaleh, Abdlkarim
    University West, Department of Engineering Science, Division of Production Systems.
    Behzad Far, Shervin
    Northvolt, .
    Stjern, David
    University West, Department of Engineering Science, Division of Production Systems.
    Applying Digital Twin Technology in Higher Education: An Automation Line Case Study2022In: Advances in Transdisciplinary Engineering, ISSN 2352-751X, Vol. 21, p. 461-472Article in journal (Refereed)
    Abstract [en]

    Abstract. Production systems are being expanded to include Digital Twins (DTs)

    as part of increased industrial digitalization. DTs can bring benefits e.g., increase

    visibility, safety, and accessibility of the system. Further, digital experimentation

    can reduce time and cost. Though, application of DT technologies involves

    challenges i.e., model accuracy or errors in transferring data or codes between the

    DT and the physical twin. Many studies on DTs focus on industrial applications.

    However, DT technology has potential for implementation of digital labs in

    education. This aspect of DTs is of rising importance as distance education has

    increased over the last decade and access to physical laboratories can be restricted

    due to factors such as the Covid-19 pandemic. Thus, there is a need to study the use

    of DT technology in higher education. To address this, we investigate possibilities

    and challenges of applying DT technology in education to conduct industrial-like

    labs virtually. A case of an automation line, with full scale industrial equipment,

    based at a research center, is focused. Results emphasize that the application of DT

    technologies require multi-domain expertise to understand the consequences of

    every single decision in the design process on every piece of equipment involved,

    making the modelling process complex and time consuming. Thus, when applied in

    education, test procedures need to be designed to focus on students’ motivation,

    improved learning and understanding of production systems. DTs are considered

    enabling technologies supporting the concept of Industry 5.0, thus stressing the

    human-centric aspects of advancing Industry 4.0. The predicted application of DTs

    emphasizes the need for educational curricula that include laboratory applications

    and theoretic understanding of DT technologies. This study focusses the application

    of DT technologies in higher education curricula, but the result of the study can

    contribute to other areas such as automation and virtual commissioning towards

    smarter manufacturing

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    fulltext
  • 9.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Bränneby, Eva
    University West, Department of Engineering Science, Division of Welding Technology.
    Hagelin, Monika
    University West, Grants and Innovation Office (GIO).
    An educational model for competence development within simulation and technologies for industry 4.02021In: Proceedings of the 2021 Winter Simulation Conference / [ed] S. Kim, B. Feng, K. Smith, S. Masoud, Z. Zheng, C. Szabo and M. Loper, 2021, p. 1-12, article id 177415Conference paper (Refereed)
    Abstract [en]

    In the era of industry 4.0 businesses are pursuing applications of technological developments towards increased digitization. This in turn necessitates continuous and increasing demand for competence development of professionals. This paper reports a study of the design of university courses targeted towards professionals and investigate how such an educational incentive can act as a catalyst for application of technologies for industry 4.0, including simulation. Quantitative data is collected from fifteen courses addressing the competence need in manufacturing industry, and the qualitative data includes ten focus groups with course participants from companies. The results highlight that the course design enables knowledge exchange between university and industry and between participants. Moreover the pedagogy of working on real cases can facilitate opportunities for introducing new technologies to management. The study shows that the educational incentive explored can act as a catalyst for application of simulation and technologies within industry 4.0 in manufacturing industry.

  • 10.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    Exploring Socially Sustainable, Smart Manufacturing: Building Bridges Over Troubled Waters2024In: Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems Proceedings of FAIM 2023, June 18–22, 2023, Porto, Portugal, Volume 2: Industrial Management / [ed] Francisco J. G. Silva, Luís Pinto Ferreira, José Carlos Sá, Maria Teresa Pereira, Carla M. A. Pinto, Springer, 2024, Vol. 2Conference paper (Refereed)
    Abstract [en]

    Contemporary manufacturing organizations formulate strategies towards smart manufacturing. However, strategies often merely regard technological improvements of working processes and activities and pay limited attention to human-centric perspectives. This study addresses the complex phenomenon of reaching socially sustainable smart manufacturing by exploring the human-centric perspectives in the eras of Industry 4.0 and Industry 5.0. Data were collected through an explorative qualitative case study with focus groups applying the history wall approach to document informants’ choices of activities that impact digitalization. To investigate informants’ interpretations and experiences of digital initiatives and prospects, the history wall approach was coupled with the analytical lens of the co-workership wheel, with its four conceptual pairs: trust and openness, community spirit and cooperation, engagement and meaningfulness, responsibility, and initiative. A total of 17 informants from different organizational levels at a case company participated. Activities, impacting digitalization, brought forward were grouped into technology, organization, and external impact. Results showed that human-centric and intangible perspectives surfaced as prerequisites when navigating industrial digitalization. Further, digital initiatives and prospects risk drowning in re-occurring organizational changes making successful implementation difficult. Thus, organizations cannot rely solely on technology, but must consider activities related to organizational aspects and impacts from the external environment, when introducing digital initiatives. Intrinsically, recognition of the co-workership concept, emphasizing human-centricity, can support the foundation necessary for bridging the gap towards socially sustainable smart manufacturing and strengthening the emerging I5.0 research.

  • 11.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    To digitalize or not? Navigating and merging human: and technology perspectives in production planning and control2022In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015Article in journal (Refereed)
    Abstract [en]

    Contemporary manufacturing companies are navigating industrial digitalization anticipating increased production efciency and competitiveness in a volatile environment. This study focuses on the implementation processes of digital tools for production planning and control (PPC), i.e., advanced planning and scheduling (APS) software, in relation to the application of analog planning with physical fow boards. Digital tools can support understanding the consequences of production changes and variations, hence facilitating adaptable and resilient manufacturing. However, technological changes can be daunting, and efective implementations require dynamic capabilities to remain competitive in elusive environments. The aim is to study the implementation processes of an APS software to understand the requirements of fruitfully moving from analog planning to next-generation digital tools for decision support in PPC. The paper presents an explorative case study, at a manufacturing company within the energy sector. The interview study took place over 9 months during 2020–2021, investigating current and retrospective aspects of the case across 2019–2021. The case study comprises 17 in-depth interviews with a range of company employees, e.g., logistics managers and functions responsible for digitalization development. The results highlight the challenges of implementing and especially trusting digital tools for PPC. To realize the value of digital tools for PPC, it is argued that it is imperative to simultaneously apply a human-centric perspective in decision making to ensure trustworthy, sustainable, and resilient human-data-technology nexus implementations towards smart manufacturing

  • 12.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Chirumalla, Koteshwar
    Ericsson, Mikael
    University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing.
    Håkansson, Lars
    Götborgs universitet, Göteborg (SWE).
    A novel blended learning course developed jointly between three universities to address competence development of professionals in digitalized manufacturing2019In: VILÄR 5-6 december 2019, University West, Trollhättan: Abstracts / [ed] Kristina Johansson, Trollhättan: University West , 2019, p. 6-7Conference paper (Other academic)
    Abstract [en]

    New competences and knowledge needs arises as manufacturing industry evolves and becomes increasingly digitalized. Facing this transformation, one of the challenges is the continuous and growing need for novel initiatives for competence development.The case portrayed here stems from a Swedish cross-university project aiming to jointly develop and offer courses for competence development of professionals in the manufacturing and IT sectors. The ambition is to increase the impact of the universities' respective efforts of meeting industry competence needs, where the continuous digital transformation entails that employees must develop or even change their qualifications.

    The case outlined focus co-production of a joint course package, at master level, between three universities and their respective company networks. Participating universities have long traditions in working closely with companies in research and education, where approaches for co-production have evolved over time. We make use of our joint understanding of the manufacturing industry's specific competence needs and our experiences of sustainable course formats for participants working full time.The joint course covers aspects of a manufacturing company on three levels: plant level i.e. material and production flows, cell level e.g. robotic simulation and visualisation, and system level i.e. data acquisition and monitoring through sensors. Each university is developing a course module of 2.5 ECTS, addressing a level respectively of their specialist competence. Participants are to complete assignments for each course module, i.e. for all three manufacturing levels, where the previous assignment provides an input to the next level, enabling the participants to encompass a holistic view of a manufacturing system. Participants need to combine study and work and at the same time they wish to extend their network, hence we are adopting a blended learning approach, where virtual labs and web conferences are mixed with physical meetings.A variety of challenges arise when designing such novel approaches: combining company networks, course design including online learning, planning of physical course meetings,

    joint promotion, common admission and validation process, financial models and more. However, engaging in partnerships with industry for knowledge transformation and development has the potential to become rewarding for all parties.

  • 13.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Chirumalla, Koteshwar
    Mälardalens högskola, Akademin för innovation, design och teknik, Innovation och produktrealisering, (SWE).
    Ericsson, Mikael
    University West, Department of Engineering Science, Division of Subtractive and Additive Manufacturing.
    Håkansson, Lars
    Linnéuniversitetet, Växjö, (SWE).
    Developing a professional course on digitalized production for Swedish manufacturing industry: An inter-university collaboration, its challenges, and opportunities2020Conference paper (Refereed)
  • 14.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Chirumalla, Koteshwar
    Mälardalen University, Eskilstuna, (SWE).
    Myrelid, Paulina
    Mälardalen University, Eskilstuna, (SWE).
    Ericsson, Mikael
    University West, Department of Engineering Science, Division of Production Systems.
    Granlund, Anna
    Mälardalen University, Eskilstuna, (SWE).
    Håkansson, Lars
    Linnaeus University, Växjö, (SWE).
    Johansson, Dahniel
    University West, Department of Engineering Science, Division of Production Systems.
    Experiences in Running a Professional Course on Digitally-Enabled Production in Collaboration Between Three Swedish Universities2022In: Advances in Transdisciplinary Engineering, ISSN 2352-751X, Vol. 21, p. 653-664Article in journal (Refereed)
    Abstract [en]

    Abstract. Needs for new competences and knowledge arise as industry 4.0 evolves

    in increasingly digitalized production. This development entails that job

    transformations and future skills need attention from the perspective of industry 5.0,

    where human and machine find ways of working together to improve production

    performance. Facing this perspective, one challenge is a growing need for novel

    lifelong learning initiatives, to meet emerging and altering occupations for the

    fulfilment of future skill requirements. This challenge is addressed here by

    portraying a case where three Swedish universities have formed a distinctive

    collaboration to develop a flexible (i.e. blended) course for professionals, in the

    subject of Digitally-enabled production. The purpose is to develop a sustainable

    collaboration between the universities and create a course format on master level

    addressing lifelong learning for the increasingly digitalized production. The

    ambition is to increase the impact of the universities respective efforts by sharing

    resources and utilizing individual specialized expertise to develop a practical and

    relevant course that can reach a larger target group. The course encompasses

    industry 4.0 readiness on three levels of production systems; plant-, production cell-,

    and component level; to adopt a holistic view of digitalization in production. We

    followed an action research approach for continuously collecting and documenting

    our experiences during the course development, implementation, and dissemination

    of the course. Within the frame of action research, an explorative case study

    describes and analyzes the initiative. The results highlight challenges and

    opportunities for succeeding with this form of co-produced course. The joint course

    gives professionals possibilities to work on cases from their own companies with

    expert supervision from three manufacturing levels to address complex challenges

    in industry 4.0 implementation. To conclude, the importance of lifelong learning in

    relation to the human-centric approach of industry 5.0 is emphasized as a future

    direction.

    Download full text (pdf)
    fulltext
  • 15.
    Eriksson, Kristina M
    et al.
    University West, Department of Engineering Science, Division of Production Engineering.
    Hanson, R.
    Chalmers University of Technology.
    Performance impact of options for routing and delivery initiation in tugger train delivery systems2008In: Proceedings of SPS08, Swedish Production Symposium, 18th – 20th November 2008, Stockholm, Sweden, 2008Conference paper (Refereed)
  • 16.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Hattinger, Monika
    University West, Department of Engineering Science, Division of Production Systems.
    Participants Perspectives and Results from Competence Development Courses for Industrial Work Integrated Learning2019In: VILÄR 5-6 december 2019, University West, Trollhättan: Abstracts / [ed] Kristina Johansson, Trollhättan: University West , 2019, p. 7-8Conference paper (Other academic)
    Abstract [en]

    In a work practice of constant implementation of new manufacturing processes, competence development becomes crucial for practitioners within engineering fields such as production systems, additive manufacturing, industry 4.0 and machine learning. Industrial work is transforming and practitioners constantly need to learn both integrated in work practice and through flexible education.Given this, the purpose of this study is to analyse how participants engage in a unique initiative where courses targeting competence development for manufacturing industry have been co-constructed between one university and a network of companies. The longitudinal initiative (2013-ongoing) focus industry knowledge needs and e-learning design aiming for industrial work integrated learning. Over time a course format of five-week flexible e-learning courses of 2.5 ECTS, on master level, has evolved, and 30 courses within e.g. robotics, additive manufacturing and industrial digitalization, have been designed.

    The uniqueness lies in the opportunities continuously taken for co-construction of course design throughout and this has brought about a combination of different practices for collaboration between academia and industry. Course participants perspectives are specifically explored through focus group studies and a questionnaire survey. Between 2014 and spring 2019 a total of 367 participants took part in focus group sessions at the end of each course instance. The questionnaire was distributed in spring 2019 to 638 individuals and the response rate was 12% (77 respondents) of which 56 had completed one or more courses. While the response rate of the questionnaire is low, results confirm the findings from the focus group studies and indicates new aspects for further study.

    Outcomes from the focus groups show that practitioners feel that their own motives for learning are key for course participation. This is corroborated by the questionnaire results where 79% say they apply for the courses with ambition to study built on their own desire. The flexible e-learning format including virtual laboratories, web-conferencing and practical cases, is essential when combining full time work with competence development. This coupled with 89% of the questionnaire respondents finding the course content useful in relation to their own work, indicates the uniqueness of the initiative. Challenges persisting are the university's lack of capacity to swiftly respond to companies' skills needs and the nurture and development of the growing network that requires continued coordination. However, participants perspectives reveal the potential of how to empower co-construction of knowledge for industrial work integrated learning.

  • 17.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Hendberg, Ted
    Siemens Energy AB, Trollhättan, (Swe).
    A Case Study Initiating Discrete Event Simulation as a Tool for Decision Making in I4.0 Manufacturing2021In: Lecture Notes in Business Information Processing, ISSN 1865-1348, E-ISSN 1865-1356, Vol. 414 LNBIP, p. 84-96Article in journal (Refereed)
    Abstract [en]

    Smart manufacturing needs to handle increased uncertainty by becoming more responsive and more flexible to reconfigure. Advances in technology within industry 4.0 can provide acquisition of large amounts of data, to support decision making in manufacturing. Those possibilities have brought anew attention to the applicability of discrete event simulation for production flow modelling when moving towards design of logistics systems 4.0. This paper reports a study investigating challenges and opportunities for initiation of discrete event simulation, as a tool for decision making in the era of industry 4.0 manufacturing. The research has been approached through action research in combination with a real case study at a manufacturing company in the energy sector. The Covid-19 pandemic fated that adjusted and new ways of communication, collaboration, and data collection, in relation to the methods, had to be explored and tried. Throughout the study, production data, such as processing times, have been collected and analyzed for discrete event simulation modelling. The complexity of introducing discrete event simulation as a new tool for decision making is highlighted, where we emphasize the human knowledge and involvement yet necessary to understand and to draw conclusions from the data. The results also demonstrate that the data analysis has given valuable insights into production characteristics, that need addressing. Thus, revealing opportunities for how the initiative of introducing discrete event simulation as an anew tool in the wake of industry 4.0, can act as a catalyst for improved decision making in future manufacturing. © 2021, Springer Nature Switzerland AG.

  • 18.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Jellbo, Oskar
    University West, Department of Engineering Science, Division of Industrial Engineering and Management, Electrical- and Mechanical Engineering.
    Manufacturing logistics courses aimed at competence development: Perspectives of coproduction between university and industry2021In: Plans Forsknings- och tillämpningskonferens 2021: Logistik Möter Praktik, Plan - Logistikföreningen för effektiva flöden , 2021, p. 349-363Conference paper (Refereed)
    Abstract [en]

    New and elevated competences and knowledge needs arise as industry evolves and manufacturing is increasingly focusing digitalisation and sustainability. Facing those aspects of transformation one of the challenges is the continuous and growing need for competence development of professionals. In a work practice of constant implementation of new manufacturing processes, competence development becomes crucial for professionals within engineering fields such as production systems, product development and logistics. This paper reports a study of the design of courses within manufacturing logistics aimed at competence development for industrial professionals. We investigate how such courses can be designed to enable improved logistics practices in manufacturing industry. The course mode and its development are outlined, explaining the university and industry co-production of the incentive. The courses and their specified content are developed jointly with collaborating companies, and the courses are given free of charge as regular university courses advertised as free-standing courses. Data is collected between the period of spring semester 2019 – to spring semester 2021 from five completed courses of 2.5 ECTS on master level within manufacturing logistics. The data comprise quantitative data, such as throughput rate for course participants and qualitative data from focus groups. The focus groups emphasis the perspectives of the course participants and take place at the end of a completed course. Those focus groups serve as course evaluation coupled with highlighting themes of co-production and knowledge exchange between university and industry. The course concept of 2.5 ECTS credits on master level given during a period of five weeks has proven successful as regards meeting competence development need for professionals that are required to study in parallel with full time work. The results highlight participant’s perspectives, revealing that they value the potential of knowledge exchange enabled through the pedagogy of the course concept. Further, we emphasize that co-production between university and industry is beneficial to successfully design education aiming to meet real competence needs and challenges faced by manufacturing companies. To conclude, the results accentuate how the presented course concept can create and encourage conditions that lay the foundation for increased application of, at the companies, previously untried manufacturing logistic methods and new practices within logistics. 

  • 19.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Juste, A.
    Junefjäll, J.
    Reducing energy consumption through production flow simulation: A case study at a car engine manufacturer2021In: 8th International EurOMA Sustainable Operations and Supply Chain Forum La Rochelle Business School - Excelia Group. 22nd and 23rd March 2021, 2021Conference paper (Other academic)
  • 20.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Lycke, Liselott
    University West, Department of Engineering Science.
    Changing traditional academic structures to meet new competence needs in industry Selected thematic track: Perspectives on collaboration for sustainable organisational learning2022Conference paper (Other academic)
    Abstract [en]

    Purpose New technological advancements and global societal changes continuously reshapes manufacturing industry creating increasing competence needs for professionals, as new skill needs, both up-skilling and re-skilling are evolving simultaneously (European Commission, 2021). Thus, industry is struggling with skill shortages at the same time as higher educational institutions (HEIs) traditionally are not structurally organised to design for and meet the new educational demands that are progressively surfacing. Those challenges are addressed here by depicting a case where a Swedish university in collaboration with around 50 external partners, mainly from the manufacturing industry, have co-produced an educational model with short courses, at master level, targeting competence development of professionals (Hattinger and Eriksson, 2020). Such models have evolved over the past decade (Kashyap and Agrawal, 2019) with the content of the courses consecutively adapted to the shifts in industry competence needs (Eriksson et al., 2021). Those initiatives have seen many phases, e.g., calibration of co-production activities between industry and academia (Brunel et al., 2010; Holland, 2019; Sannö et al., 2019) and finding suitable course formats for professionals (Hattinger and Eriksson, 2015). However, the aspects of corresponding and necessary organisational changes to traditional academic structures to successfully encompass such new educational models into the regular education prospects is still challenging and thus needs further understanding. The new educational models mean changes to many functions within HEIs, emphasising that knowledge between functions needs to be transferred, shared, and exchanged. Hence, the aim is to study the changes in the organisation's knowledge from the perspective of organisational learning (Argote, 2013). Following this, the research question asked is: How can academic structural changes, for creating an agile and sustainable university educational model meeting industrial competence needs in a changing society, be understood from the perspective of organisational learning? Case description and outline of the study The case focuses on an educational model developed in co-production between academia and industry, spanning the years 2013-2020. The model is designed with short courses in hybrid format of 2.5 European Credits (ECTS) given over five weeks in the field of production technology. Competence needs and co-production between university and industry has been studied over the years (Hattinger and Eriksson, 2020). However, it is realised that it is essential with joint refection among different functions at HEIs for facilitating organisational changes of traditional academic structures . . .

  • 21.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Mileham, A. R.
    Newnes, L.B.
    A survey investigating current industrial scheduling practice among a cross-section of UK companies2003In: Proceedings of the International Conference on Manufacturing Research (ICMR03), 9th – 11th September, Glasgow, United Kingdom, 2003, p. 409-414Conference paper (Other academic)
  • 22.
    Eriksson, Kristina M.
    et al.
    University West, Department of Technology, Mathematics and Computer Science, Division for Mechanical Engineering.
    Mileham, A.R.
    Newnes, L.B
    A novel scheduling performance comparison tool: scheduling performance profile (SPP) graph2006In: Proceedings of IDMME06, International conference on integrated Design and Manufacturing in Mechanical Engineering: Grenoble, France. May 17-19, Grenoble, 2006Conference paper (Other academic)
  • 23.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Mileham, A.R.
    Newnes, L.B.
    A study of short- medium- and long horizon final production scheduling, applying priority rules and using a discrete event simulation approach2005In: Proceedings of the International Conference on Manufacturing Research (ICMR05), 6th – 8th September, Cranfield, United Kingdom., 2005Conference paper (Other academic)
  • 24.
    Eriksson, Kristina M.
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Ramasamy, Sudha
    University West, Department of Engineering Science, Division of Production Systems.
    Zhang, Xiaoxiao
    University West, Department of Engineering Science, Division of Production Systems.
    Wang, Zhiping
    Research and Technology Development, Volvo Group Trucks Operations, Gothenburg (SWE).
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    Conceptual framework of scheduling applying discrete event simulation as an environment for deep reinforcement learning2022In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 107, p. 955-960Article in journal (Refereed)
    Abstract [en]

    Increased environmental awareness is driving the manufacturing industry towards novel ways of energy reduction to become sustainable yet stay competitive. Climate and enviromental challenges put high priority on incorporating aspects of sustainability into both strategic and operational levels, such as production scheduling, in the manufacturing industry. Considering energy as a parameter when planning makes an already existing highly complex task of production scheduling even more multifaceted. The focus in this study is on inverse scheduling, defined as the problem of finding the number of jobs and duration times to meet a fixed input capacity. The purpose of this study was to investigate how scheduling can be formulated, within the environment of discrete event simulation coupled with reinforcement learning, to meet production demands while simultaneously minimize makespan and reduce energy. The study applied the method of modeling a production robot cell with its uncertainties, using discrete event simulation combined with deep reinforcement learning and trained agents. The researched scheduling approach derived solutions that take into consideration the performance measures of energy use. The method was applied and tested in a simulation environment with data from a real robot production cell. The study revealed opportunities for novel approaches of studying and reducing energy in the manufacturing industry. Results demonstrated a move towards a more holistic approach for production scheduling, which includes energy usage, that can aid decision-making and facilitate increased sustainability in production. We propose a conceptual framework for scheduling for minimizing energy use applying discrete event simulation as an environment for deep reinforcement learning.

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  • 25.
    Gharaibeh, Lina
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Lantz, Bjorn
    University West, Department of Engineering Science, Division of Production Systems.
    Matarneh, Sandra
    Al-Ahliyya Amman University (JOR).
    Elghaish, Faris
    Queen's University Belfast, Belfast, (GBR).
    Towards digital construction supply chain-based Industry 4.0 solutions: scientometric-thematic analysis2022In: Smart and Sustainable Built Environment, ISSN 2046-6099, E-ISSN 2046-6102Article in journal (Refereed)
    Abstract [en]

    Purpose – The wood construction industry has been described as slow in adapting efficiency-increasingactivities in its operations and supply chain. The industry is still facing challenges related to digitalization, suchas fragmentation, poor traceability and lack of real-time information. This study evaluates the status ofdigitalization in construction supply chains by thematically analyzing the existing literature and mappingresearch trends.Design/methodology/approach – A review of the key literature from 2016 to 2021 was performed. Theresults highlight various technologies and their applications within supply chains and identify research gaps,especially between theoretical frameworks and actual implementation using a scientometric-thematic analysis.Findings – This paper provides a conceptual framework to further aid researchers in exploring the currenttrends in Supply Chain 4.0 and its applications in the wood construction industry compared to other moreadvanced industries. Suggested directions for future research in the wood construction Supply Chain 4.0 areoutlined.Originality/value – The existing literature still lacks a comprehensive review of the potential of a digitalizedsupply chain, especially in the construction industry. This framework is pivotal to continue explaining andobserving the best ways to accelerate and implement Supply Chain 4.0 practices for digitalized supply chainmanagement (SCM) while focusing specifically on the wood construction industry. The literature review resultswill help develop a comprehensive framework for future research direction to create a clearer vision of thecurrent state of digitalization in supply chains and focus on the wood construction supply chain, thus, fullyachieving the benefits of Supply Chain 4.0 in the wood construction industry.

  • 26.
    Gharaibeh, Lina
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Lantz, Björn
    University West, Department of Engineering Science, Division of Industrial Engineering and Management, Electrical- and Mechanical Engineering.
    Building Information Modelling in the wood construction industry: Challenges and level of implementation2022Conference paper (Refereed)
    Abstract [en]

    Building information modelling (BIM) is becoming a necessity for the wood construction industry, this is due to its high level of prefabrication and complex digital procedures using wood sawing machines and sophisticated cuttings. This research examines the levelof BIM implementation in the wood construction industry in Sweden from industry experts prospective. Data was collected through interviews with industrial practitioners and academics. This research provides an important list of challenges that need to be considered to increase the level of BIM implementation in the wood construction industry. The research also provides recommendations for future research to aid in increasing the level of BIM implementation in the wood construction industry in Sweden.

  • 27.
    Gharaibeh, Lina
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Lantz, Björn
    University West, Department of Engineering Science, Division of Industrial Engineering and Management, Electrical- and Mechanical Engineering. University West, Department of Engineering Science, SE-461 86 Trollhättan, Sweden.
    Supply Chain Digitalization in the Wood Manufacturing Industry: A Bibliometric Literature Review2022In: Advances in Transdisciplinary Engineering, ISSN 2352-751X, Vol. 21, p. 617-628Article in journal (Refereed)
    Abstract [en]

    Abstract. The wood manufacturing industry has been described as slow in adopting

    efficiency increasing activities in its operations and supply chain, the industry is still

    facing challenges relating to digitalization such as fragmentation, poor traceability,

    and lack of real-time information. The integration of industry 4.0 technologies can

    enhance the supply chain performance in terms of efficiency, collaboration, quality,

    and transparency. This paper aims to evaluate the current status of digitalization in

    supply chains, by analysing the existing literature and mapping research trends. in an

    aim to create a clearer vision of the current state of digitalization in supply chains in

    general and focusing on the wood manufacturing supply chain in particular, the

    results of the literature review will be used to develop a comprehensive framework

    for future research direction, to fully achieve the benefits of supply chain 4.0 in the

    wood manufacturing industry. This framework serves as a departure point to continue

    explaining and observing the best way to accelerate and implement Supply Chain 4.0

    practices for digitalized supply chain management while focusing specifically on the

    wood manufacturing industry. To achieve the overall purpose, a literature review of

    the key literature from 2016 to 2021 has been performed. using a bibliometric and

    content review analysis, the results shed light on various technologies and their

    applications within supply chains and identify research gaps especially between

    theoretical frameworks and actual implementation. This paper provides a conceptual

    framework to further aid researchers in the exploration of knowledge regarding the

    most current trends in Supply Chain 4.0 and its applications in the wood

    manufacturing industry compared to other advanced industries, as well as the

    directions of the new research in the wood manufacturing Supply Chain 4.0.

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  • 28.
    Gharaibeh, Lina
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Matarneh, Sandra
    Department of Civil Engineering, Al-Ahliyya Amman University, Amman, (JOR).
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Lantz, Björn
    University West, Department of Engineering Science, Division of industrial engineering.
    Digital transformation of the wood construction supply chain through building information modelling: current state of practice2023In: Construction Innovation, ISSN 1471-4175, E-ISSN 1477-0857, Vol. 24, no 7, p. 273-291Article in journal (Refereed)
    Abstract [en]

    Purpose: This study aims to present a state-of-the-art review of building information modelling (BIM) in the Swedish construction practice with a focus on wood construction. It focuses on examining the extent, maturity and actual practices of BIM in the Swedish wood construction industry, by analysing practitioners’ perspectives on the current state of BIM and its perceived benefits. Design/methodology/approach: A qualitative approach was selected, given the study’s exploratory character. Initially, an extensive review was undertaken to examine the current state of BIM utilisation and its associated advantages within the construction industry. Subsequently, empirical data were acquired through semi-structured interviews featuring open-ended questions, aimed at comprehensively assessing the prevailing extent of BIM integration within the Swedish wood construction sector. Findings: The research concluded that the wood construction industry in Sweden is shifting towards BIM on different levels, where in some cases, the level of implementation is still modest. It should be emphasised that the wood construction industry in Sweden is not realising the full potential of BIM. The industry is still using a combination of BIM and traditional methods, thus, limiting the benefits that full BIM implementation could offer the industry. Originality/value: This study provided empirical evidence on the current perceptions and state of practice of the Swedish wood construction industry regarding BIM maturity. © 2023, Lina Gharaibeh, Sandra Matarneh, Kristina Eriksson and Björn Lantz.

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  • 29.
    Gharaibeh, Lina
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Matarneh, Sandra T.
    Civil Engineering Department, Engineering Faculty, Al-Ahliyya Amman University (JOR).
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Lantz, Björn
    University West, Department of Engineering Science, Division of Industrial Engineering and Management, Electrical- and Mechanical Engineering.
    An Empirical Analysis of Barriers to Building Information Modelling (BIM) Implementation in Wood Construction Projects: Evidence from the Swedish Context2022In: Buildings, E-ISSN 2075-5309, Vol. 12, no 8, p. 1067-1067Article in journal (Refereed)
    Abstract [en]

    Building information modelling is gradually being recognised by the architecture, engineering, construction, and operation industry as a valuable opportunity to increase the efficiency of the built environment. Focusing on the wood construction industry, BIM is becoming a necessity; this is due to its high level of prefabrication and complex digital procedures using wood sawing machines and sophisticated cuttings. However, the full implementation of BIM is still far from reality. The main objective of this paper is to explore the barriers affecting BIM implementation in the Swedish construction industry. An extensive literature review was conducted to extract barriers hindering the implementation of BIM in the construction industry. Secondly, barriers to the implementation of BIM in the wood construction industry in Sweden were extracted using the grounded theory methodology to analyse expert input on the phenomenon of low BIM implementation in the wood construction industry in Sweden. Thirty-four barriers were identified. The analysis of this study also led to the development of a conceptual model that recommended solutions to overcome the barriers identified to help maximise BIM implementation within the wood construction industry. Identifying the main barriers affecting BIM implementation is essential to guide organisational decisions and drive policy, particularly for governments that are considering articulating regulations to expand BIM implementation. 

  • 30.
    Hattinger, Monika
    et al.
    University West, Department of Technology, Mathematics and Computer Science, Division for Mechanical Engineering.
    Christiernin-Gustafsson, Linn
    University West, School of Business, Economics and IT, Division of Computer Engineering.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Engineering. University West, Department of Engineering Science, Division of Production System.
    Digitizing work: Organizational Work-Integrated Learning through Technology Mediated Courses in Manufacturing Industry2013In: 18th WACE World Conference on Cooperative & Work-Integrated Education: WIL-POWER: FUELING THE FUTURE WORKFORCE, WACE , 2013, p. 1-12Conference paper (Other academic)
    Abstract [en]

    The manufacturing industry is continuously facing global competition and customer demands which impose the need to knowledge development to manage changes and long-term business goals. Continuous and lifelong learning is often seen as processes that support competence development and learning integrated within work. In this paper we focus on processes of learning within the manufacturing industry and how learning initiatives as technology mediated courses (TMC) can support learning from the workplace learning needs. Is learning initiatives integrated in work considered as means for strategic business goals? Can TMC be an important learning tool for support of knowledge creation? The study is performed through interviews with production managers and human resource managers with eight manufacturing industries in the western part of Sweden. Through the study we try to understand what knowledge the industry needs to evolve and achieve effective production. We also study the readiness for technology mediated learning. Early results show that the industries have interest in learning initiatives such as TMC and are willing to co-produce knowledge together with universities. We present a matrix model that interlinks business goals and the industries current use of technology mediated learning tools. However, the experience of using tools such as web conference systems and learning management systems for learning initiatives is diversified.

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    Digitizing work
  • 31.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    de Blanche, Andreas
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    Lundh Snis, Ulrika
    University West, School of Business, Economics and IT, Divison of Informatics.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Belenki, Stanislav
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Reviewing human-centric themes in intelligent manufacturing research2022In: International Conference on Work Integrated Learning: Abstract Book, Trollhättan: University West , 2022, p. 125-127Conference paper (Other academic)
    Abstract [en]

    In the era of Industry 4.0, emergent digital technologies generate profound transformations in the industry toward developing intelligent manufacturing. The technologies included in Industry 4.0 are expected to bring new perspectives to the industry on how manufacturing can integrate new solutions to get maximum output with minimum resource utilization (Kamble et al., 2018). Industry 4.0 technologies create a great impact on production systems and processes, however, affect organizational structures and working life conditions by disrupting employees’ everyday practices and knowledge, in which competence and learning, human interaction, and organizational structures are key. Hence, new digital solutions need to be integrated with work and learning to generate more holistic and sustainable businesses (Carlsson et al., 2021).

    The core Industry 4.0 technologies are built on cyber-physical systems (CPS), cloud computing, and the Internet of things (IoT) (Kagermann et al., 2013; Zhou et al., 2018). In recent years, an array of additional technologies has been developed further, such as artificial intelligence (AI), big data analytics, augmented and virtual reality (AR/VR), cyber security, robotics, and automation. Industry 4.0 aims to create a potential for faster delivery times, more efficient and automated processes, higher quality, and customized products (Zheng et al., 2021). Hence, the ongoing transformation through the technological shift of production in combination with market demands pushes the industry and its production process.

    Recent research has substantially contributed to an increased understanding of the technological aspects of Industry 4.0. However, the utilization of technologies is only a part of the complex puzzle making up Industry 4.0 (Kagermann et al., 2013; Zheng et al., 2021). The impact Industry 4.0 technologies and application s have on the industrial context also changes and disrupts existing and traditional work practices (Taylor et al., 2020), management and leadership (Saucedo-Martínez et al., 2018), learning and skills (Tvenge & Martinsen, 2018), and education (Das et al., 2020). This research has shown a growing interest in human-centric aspects of Industry 4.0 (Nahavandi, 2019), i.e., the transformative effects Industry 4.0 has on humans, workplace design, organizational routines, skills, learning, etc. However, these aspects are scarcely considered in-depth. Given this, and from a holistic point of view, there is a need to understand intelligent manufacturing practice from a human-centric perspective, where issues of work practices and learning are integrated, herein refe rred to as industrial work-integrated learning. I-WIL is a research area that particularly pays attention to knowledge production and learning capabilities related to use and development when technology and humans co -exist in industrial work settings (Shahlaei & Lundh Snis, 2022). Even if Industry 4.0 still is relevant for continuous development, a complementary Industry 5.0 has arisen to provide efficiency and productivity as the sole goals to reinforce a sustainable, human-centric, and resilient manufacturing industry (Breque et al., 2021; Nahavandi, 2019).

    Given this situation, the research question addressed here is: How does state-of-the-art research of Industry 4.0 technologies and applications consider human-centric aspects? A systematic literature review was conducted aiming to identify a future research agenda that emphasizes human-centric aspects of intelligent manufacturing, that will contribute to the field of manufacturing research and practices. This question was based on very few systematic literature reviews, considering Industry 4.0 research incorporating human -centric aspects for developing intelligent manufacturing (Kamble et al., 2018; Zheng et al., 2021). The literature review study was structured by the design of Xiao and Watson’s (2019) methodology consisting of the steps 1) Initial corpus creation, 2) Finalizing corpus, and 3) Analyzing corpus, and we also used a bibliometric approach throughout the search process (Glänzel & Schoepflin, 1999). The keyword selection was categorized into three groups of search terms, “industry 4.0”, “manufacturing”, and “artificial intelligence”, see figure 1. (Not included here)

    Articles were collected from the meta -databases EBSCOhost, Scopus, Eric, and the database AIS, to quantify the presence of human-centric or human-involved AI approaches in recent manufacturing research. A total of 999 scientific articles were collected and clustered based on a list of application areas to investigate if there is a difference between various areas in which artificial intelligence is used. The application areas are decision -making, digital twin, flexible automation, platformization, predictive maintenance, predictive quality, process optimization, production planning, and quality assessment.Throughout the review process, only articles that included both AI and human -centric aspects were screened and categorized. The final corpus included 386 articles of which only 93 articles were identified as human -centric. These articles were categorized into three themes: 1) organizational change, 2) competence and learning, and 3) human-automation interaction. Theme 1 articles related mostly to the application areas of flexible automation (11), production planning (9), and predictive maintenance (5). Theme 2 concerned the application areas of production planning and quality assessment (7), and process optimization (7).

    Finally, theme 3 mainly focused on flexible automation (10), digital twin (3), and platformization (3). The rest of the corpus only consisted of one or two articles in related application areas. To conclude, only a few articles were found that reinforce human -centric themes for Industry 4.0 implementations. The literature review identified obstacles and opportu nities that affect manufacturing organizations to reap the benefits of Industry 4.0. Hence, I-WIL is proposed as a research area to inform a new research agenda that captures human and technological integration of Industry 4.0 and to further illuminate human-centric aspects and themes for future sustainable intelligent manufacturing. 

  • 32.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Eriksson, Kristina
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Action Design Research: Design of e-WIL for the Manufacturing Industry2015In: The 2015 Americas Conference on Information Systems (AMCIS 2015): Proceedings, 2015, p. 1-14Conference paper (Refereed)
    Abstract [en]

    This paper reports on a design process of e-learning courses for competence development of experienced employees in the manufacturing industry. Through a cross- organizational collaborative action design research project the aim was to design e-learning courses at university level to support work-integrated learning. Two design- and learning cycles were evaluated over two years. The first cycle identified challenges that were applied to a pilot course in Industrial automation. From evaluation of this course we derived design principles applied to two further courses in Machining and Negotiation skills. The results from our empirical data suggest general principles as competence mapping work, collaborative manufacturing e-WIL cases and interactive learning technologies for design of e-WIL courses as boundary crossing activities to reach transformative learning integrated in the manufacturing industry.

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  • 33.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Action design research: Design of e-WIL for the manufacturing industry2015In: 2015 Americas Conference on Information Systems, AMCIS 2015: 21st Americas Conference on Information Systems, AMCIS 2015, Fajardo, 13 August 2015 - 15 August 2015, Americas Conference on Information Systems , 2015Conference paper (Refereed)
    Abstract [en]

    This paper reports on a design process of e-learning courses for competence development of experienced employees in the manufacturing industry. Through a crossorganizational collaborative action design research project the aim was to design e-learning courses at university level to support work-integrated learning. Two designand learning cycles were evaluated over two years. The first cycle identified challenges that were applied to a pilot course in Industrial automation. From evaluation of this course we derived design principles applied to two further courses in Machining and Negotiation skills. The results from our empirical data suggest general principles as competence mapping work, collaborative manufacturing e-WIL cases and interactive learning technologies for design of e-WIL courses as boundary crossing activities to reach transformative learning integrated in the manufacturing industry.

  • 34.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Aspects of Knowledge Transformation in Industry-Union-University Collaborations: A study of Work-integrated e-Learning courses target Norwegian industry2018In: VILÄR Abstraktbok / [ed] Kristina Johansson, Trollhättan: Högskolan Väst , 2018, p. 10-10Conference paper (Other academic)
    Abstract [en]

    The focus in this study is on knowledge transformation in the workplace following substantial competence initiatives through blended e-learning at the university level. Competence development on academic level is a key factor for industries in times of increased digitalization of manufacturing work. To develop competitive manufacturing requires employees with expert knowledge, which professional organisations need to strengthening. Even if individual employees' motivation for learning is essential, management need to put efforts on competence development and encourage education that, combine theory and practice in forms of work integrated learning. Blended e-learning courses on university level has been successful for supporting such competence development needs, which here is described as work-integrated e-learning, e-WIL. In this study, we explore practitioners' knowledge transformation after their participation in blended e-WIL courses that are designed with industry target content aiming for workplace transformations. Specifically, we focus on the learning efforts versus the management strategies after e-learning initiatives that have an effect on workplace transformations.

    The industry target courses in the case study, are designed in collaboration between an industry-union-university venture of a Norwegian industry network, the Addiscounion and a Swedish university. Six courses are included comprising three knowledge subjects; Logistics and Supply Chain Management, Engineering Tools, and Robotics and Automation. Addisco was the facilitator for engaging industry university collaboration, and stimulated co-creation between industry companies. Data was collected through a longitudinal action research project, comprising six focus group sessions with 113 industry participants during 2015 and 2018. We analysed the company management support of knowledge transformation through the course participants' manifestations of experiences in focus groups, conducted after each course intervention. Overall results show that most participants experience a low management support of knowledge transformation as an engine for workplace transformation, after conducting e-WIL courses. Stimulation of individual motivation and new skills gained were not promoted within the workplace structures. There seem to be a lack of individual competence plans, time for studies, business models and routines, networking and recognition of the individuals' knowledge transformation. Rather, participants claimed their individual responsibilities, and motivation that drives them to further competence development. We therefore argue for stronger management awareness and designed learning models, to develop company strategies that fully appreciate the benefits and new knowledge that industry participants bring back into the workplace after course participation.

  • 35.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Co-Construction of Knowledge in Work-Integrated E-Learning Courses in Joint Industry-University Collaboration2018In: Proceedings of the 11th International Conference on E-Learning in the Workplace (ICELW 2018) New York, New York, USA 13 – 15 June 2018 / [ed] David Guralnick, New York, 2018, p. 13-18Conference paper (Refereed)
  • 36.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Co-construction of Knowledge in Work-Integrated E-learning Courses in Joint Industry-University Collaboration2018In: International Journal of Advanced Corporate Learning, E-ISSN 1867-5565, Vol. 11, no 1, p. 10-16Article in journal (Refereed)
    Abstract [en]

    Blended e-learning in higher education targeting company knowledge needs, can support continuous competence development for practitioners in the manufacturing industry. However, university education is traditionally not designed for workplace knowledge needs that strengthen practitioners' learning in everyday work, i.e. work-integrated learning.

    Designing for such learning efforts is even more challenging when the pedagogical strategy is to stimulate practitioners own work experiences as a valuable knowledge source in construction with other peers or teachers. The aim is to explore how engineering practitioners and research teachers mutually co-construct knowledge. In particular, three types of case-based methodologies are examined within a range of industry targeted e-learning courses. The study is part of alongitudinal joint industry-university project. Eleven courses were analyzed through focus group sessions with 110 practitioners from 15 different companies. Results show that 1) Virtual digital cases stimulate high technology learning, but show low collaboration with peers, 2) On-line collaborative negotiation cases stimulate both web conferencing and high interactivity, and 3) Real workplace cases do not stimulate e-learning, but motivate strong work-integrated learning and knowledge expansion.

  • 37.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Learning negotiations skills on-line by a case-based methodology through co-construction of knowledge between industry and academy2018In: 12th International Technology, Education and Development Conference (INTED), Valencia, Spain: IATED-INT ASSOC TECHNOLOGY EDUCATION & DEVELOPMENT , 2018, p. 6651-6658Conference paper (Refereed)
    Abstract [en]

    University e-learning education aims to support lifelong learning for practitioners in the manufacturing industry and strengthen their competence development integrated in work practice. However, traditional higher education courses are usually designed for individuals on campus and do not support work practitioners working full time. Hence, they are not usually designed for time independence, flexibility or collaborative learning. Traditionally, campus courses do not include practitioners’ knowledge from their work experiences as a valuable source to be negotiated in knowledge construction with other peers and teachers. However, to integrate practitioners’ workplace experiences, as a valuable knowledge source, is a demanding process when designing e-learning courses that includes pedagogical strategies, case-based methodologies and choices of learning technologies. The aim of this study was to explore how engineering practitioners and research teachers mutually co-construct knowledge in a case-based methodology, specifically within the subject Negotiation Skills. Studies took part within a longitudinal and joint industry-university competence development project between a network of manufacturing industries and one university in the Western part of Sweden. The courses comprise 2.5 European Credits (ECTS) and include cases as a Harvard Case designed with a predefined role-play negotiation game, video production and essay. The case methodology was developing during three design cycles (2014-2015), as a part of the whole course design inspired by an Action Design Research (ADR) approach. Analysis from three focus group session discussions from the three courses including 34 practitioners, and through observations of web-conferencing show that that practitioners’strengthened their knowledge of handling negotiations within work practice. There were problems of using web-conferencing, producing own videos and fulfil written essays stringently, however these problems decreased throughout the three design cycles of the course, due to explicated instructions and a higher practitioner involvement. Generally, results show that practitioners; 1) strengthened their knowledge on how cultural differences affected negotiations, 2) improved their decision making skills in problematic business situations, and 3) developed personal skills on how to visualize conflict situations through reflections on their own actions and communications within practical work situations. The e-learning technology failures also decreased.

  • 38.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Mind the Gap: a Collaborative Competence e-Learning Model between University and Industry2020In: Proceedings of the 53rd Hawaii International Conference on System Sciences Jan 07 - 10, 2020 a Maui, Hawaii, United States of America., 2020, p. 79-88Conference paper (Refereed)
    Abstract [en]

    This article departure from the effects that interorganizational collaboration brings for the participating partners, specifically from design-related activities of e-learning courses and co-production. There search focus is on critical factors for interorganizational collaborative e-learning and coproduction between university and industry. We describe the process of a six-year longitudinal collaborative action research project including six cases and three phases, initialization, implementationand dissemination. The analysis is conducted from a multi-stakeholder perspective; managers, teachers,and practitioners. Overall aim is to reach for a sustainable collaborative competence e-learning model(CCeM) that will increase industrial employees' competences. Main contribution is that co-production of knowledge entails three levels of activities among actors; to have insight into the purposes and practicesof others, the capacity to transform the problems of a practice and together build common knowledge and finally the capacity of mutually co-produce knowledge acted upon in practice towards transformations in the workplace.

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  • 39.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Mind the Gap: A Collaborative Competence E-learning Model Evolving Between University and Industry2020In: Journal of Strategic Innovation and Sustainability, ISSN 1718-2077, Vol. 15, no 5, p. 10-24Article in journal (Refereed)
    Abstract [en]

    This article arises from consideration of the effects of inter-organizational collaboration on participating partners, specifically from design-related activities and co-production of e-learning courses. The research focus is on critical factors for inter-organizational collaborative e-learning and co-production between university and industry. We describe the process of a six-year longitudinal collaborative action research project comprising six cases and three phases-initialization, implementation, and dissemination. The analysis is conducted from a multi-stakeholder perspective: managers, teachers, and practitioners. The overall aim is development of a sustainable collaborative competence e-learning model that will increase industrial employees' competencies. This work's main contribution is the finding that co-production of knowledge entails three levels of activities among actors: insight into the purposes and practices of others, capacity to transform the problems of a practice and build common knowledge together, and finally, the capacity to mutually co-produce knowledge acted upon for transformation in the workplace.

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  • 40.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Hegli, Per
    Addisco Educ, Oslo, (NOR).
    Henriksen, Nina
    Addisco Educ, Oslo, (NOR).
    Management Strategies For Knowledge Transformation: A Study Of Learning Effects In Industry-Union-University Collaborative E-Learning Initiatives2018In: ICERI2018 Proceedings: 11Th International Conference Of Education, Research And Innovation (Iceri2018), International Association for Technology, Education and Development, 2018, p. 10049-10057Conference paper (Refereed)
    Abstract [en]

    Competence development on academic level is a key factor for industries in times of increased digitalization of manufacturing work. To develop competitive manufacturing requires employees with expert knowledge. Even if individual employees’ motivation for learning is essential, management need to put efforts on competence development and encourage education that, combine theory and practice in forms of work-integrated learning. Blended e-learning courses on university level has been successful for supporting such competence development needs, which here is described as work-integrated e-learning, e-WIL. In this study, we explore practitioners’ knowledge transformation after their participation in blended e-WIL courses that are designed with industry target content aiming for workplace transformation. Specifically, we focus on the learning efforts versus the management strategies after e-learning initiatives that have an effect on workplace transformations. The industry target courses are designed in collaboration between an industry-union-university venture of a Norwegian industry network, the Addisco union and a Swedish university. Six courses are included comprising three course subjects; Logistics and Supply Chain Management, Engineering Tools, and Robotics and Automation. Addisco was the facilitator for engaging industry-university collaboration, and stimulated co-creation between industry companies. Data was collected through a longitudinal action research project, comprising six focus group sessions with 113 industry participants during 2015 and 2018. We analysed the company management support of knowledge transformation through the course participants’ experiences after the course interventions. Overall results show that most participants experience a low management support of knowledge transformation as an engine for workplace transformation, after conducting e-WIL courses. Stimulation of individual motivation and new skills gained were not promoted within the workplace structures. There seem to be a lack of individual competence plans, time for studies, business models and routines, networking and recognition of the individuals’ knowledge transformation. Rather, participants claimed individual responsibilities, and motivation that drives them to competence development. We therefore argue for stronger management awareness and to develop company strategies that fully appreciate the added values and new knowledge that industry participants bring back after course participation.

  • 41.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Eriksson, Kristina
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Malmsköld, Lennart
    University West, Department of Engineering Science, Division of Automation Systems.
    Svensson, Lars
    University West, School of Business, Economics and IT, Divison of Informatics.
    E-learning Readiness and Absorptive Capacity in the Manufacturing Industry2014In: International Journal of Advanced Corporate Learning, E-ISSN 1867-5565, Vol. 7, no 3, p. 33-40Article in journal (Refereed)
    Abstract [en]

    The manufacturing industry constantly strive to develop the competencies of their expert production engineers in order to achieve and maintain a competitive advantage. Research shows that the absorptive capacity of a firm is central in order to reach such a goal. The absorptive capacity is the firm´s ability to recognize the value of new external information, assimilate it, and apply it to commercial ends, and thereby exploit the conditions for innovation. In this paper the concept of absorptive capacity is used as a lens for analyzing managerial rationales for engaging in technology enhanced competence development projects. Through interviews with key informants in 15 manufacturing firms we study the capabilities and readiness that organizations need for participation in e-learning initiatives. We present a framework of readiness for technology enhanced competence development comprised of the following interrelated constructs; awareness, e-learning maturity, dynamic capability and co-creativity. Results show a broad variation of levels within the constructs among the firms. Notable is the low level of e-learning maturity and dynamic capability. We argue that e-learning maturity is dependent on all four constructs.

  • 42.
    Hattinger, Monika
    et al.
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Eriksson, Kristina
    University West, Department of Engineering Science, Division of Manufacturing Processes.
    Malmsköld, Lennart
    University West, Department of Engineering Science, Division of Automation Systems. Chalmers University of Technology, Department of Product and Production Development,.
    Svensson, Lars
    University West, School of Business, Economics and IT, Divison of Informatics.
    Work-Integrated Learning and Co-creation of Knowledge: Design of collaborative technology enhanced learning activities2014In: Proceedings of the 37th Information Systems Research Seminar in Scandinavia (IRIS 37) / [ed] Ahmad Ghazawneh, Jacob Nørbjerg and Jan Pries-Heje, Ringsted, 2014, p. 1-15Conference paper (Refereed)
    Abstract [en]

    In this paper we aim to understand management’s perceptions of knowledge and competence development to inform the design of technology enhanced learning activities integrated in the workplace. Work-integrated learning can be viewed with the university lens on studies of formal education integrated in the workplace setting, but here we rather emphasize the conditions of the workplace as implications for design of successful e-learning initiatives. We conducted interviews with 15 manufacturing industries in Sweden and used qualitative content analysis approach to interpret the text data. Results show that companies describe a rich variation of work-integrated learning activities, but the step towards external collaboration with academia for co-production of knowledge is marginal. Also, broad-minded work for innovations is limited. This imply the need for well-planned design of richer collaborative acitivites between academia and organizations through use of media technology to encourage competence development.

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  • 43. Håkansson, J.
    et al.
    Skoog, E.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    A review of assembly line balancing and sequencing including line layouts2008In: . Proceedings of PLANs forsknings- och tillämpningskonferens, 27th - 28th August, Chalmers Technical University, Gothenburg, Sweden, Göteborg: Chalmers tekniska högskola , 2008Conference paper (Other academic)
  • 44. Håkansson, Johan
    et al.
    Skoog, Emil
    Eriksson K. M., Kristina M
    University West, Department of Engineering Science, Division of Production Engineering.
    A review of assembly line balancing and sequencing including line layouts2008In: Proceedings of PLANs forsknings- och tillämpningskonferens, 2008Conference paper (Refereed)
    Abstract [en]

    This paper comprises a literature review focused on mixed-model assembly line balancing and sequencing problems, including different line layouts. The study was undertaken in collaboration with a company to assist in mapping current state of the art. Balancing problems affect businesses long-term strategic decisions and are complex problems with regard to installation and rebalancing of assembly lines. Sequencing concerns decisions of short-term problem. Sequencing approaches include: level scheduling, mixed-model sequencing and car sequencing. Level scheduling constructs a sequence of variants to create efficient deliveries supported by the just-in-time concept, whereas both car- and mixed-model sequencing aim to minimise violations of a work station’s capacity through constructing a sequence, which alternates variants with high and low work intensity. Five layouts were considered: single-, mixed-model-, multi-model-, two-sided- and u-shaped assembly lines. These layouts were evaluated on the basis of the manufactured product(s), size and space at the production plant, economic resources, number of required operators and machinery. Following a thorough investigation of the literature, a substantial gap between academic discussions and real world practical applications was identified. The aim of forthcoming work is therefore to put this theory into practice.

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  • 45. Johansson, H.P.
    et al.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Johansson, J.
    A work-integrated learning perspective of a PACE global student development project2007In: Proceedings of WACE International Symposium of WIL, June, Singapore, 2007Conference paper (Other academic)
  • 46.
    Lundh Snis, Ulrika
    et al.
    University West, School of Business, Economics and IT, Divison of Informatics.
    de Blanche, Andreas
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Hattinger, Monika
    University West, Department of Engineering Science, Division of Production Systems.
    Olsson, Anna Karin
    University West, School of Business, Economics and IT, Division of Business Administration.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    Belenki, Stanislav
    University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering.
    Artificial and Human Intelligence through Learning: How Industry Applications Need Human-in-the-loop2020In: VILÄR: 3–4 December 2020 University West,Trollhättan. Abstracts / [ed] Kristina Johansson, Trollhättan: Högskolan Väst , 2020, p. 24-26Conference paper (Other academic)
    Abstract [en]

    This study addresses work-integrated learning from a workplace learning perspective.Two companies within the manufacturing industry (turbo machinery and aerospace) together with a multi-disciplinary research group explore the opportunities and challenges related to applications of artificial intelligence and human intelligence and how such applications can integrate and support learning at the workplace.The manufacturing industry is currently under extreme pressure to transform their organizations and competencies to reap the benefits of industry 4.0. The main driverf or industry 4.0 is digitalization with disruptive technologies such as artificial intelligence, internet of things, machine learning, cyber-physical systems, digital platforms, etc. Many significant studies have highlighted the importance of human competence and learning in connection to industry 4.0 in general and disruptive technologies and its transformative consequences in particular. What impact have such technologies on employees and their workplace?

    There is a lack of knowledge on how artificial intelligent systems actually take part in practices of human decision making and learning and to what extent disruptive technology may support both employees and organizations to “learn”. The design  and use of three real-world cases of artificial intelligence applications (as instances of industry 4.0 initiatives) will form the basis of how to support human decision making and scale up for strategic action and learning. Following a work-integratedapproach the overall research question has been formulated together with the two industry partners: How can artificial and human intelligence and learning, interact tobring manufacturing companies into Industry 4.0? An action-oriented research approach with in-depth qualitative and quantitative methods will be used in order to make sense and learn about new applications and data set related to a digitalized production.The contribution of this study will be three lessons learned along with a generic model for learning and organizing in the context of industry 4.0 initiatives. Tentative findings concern how artificial and human intelligence can be smartly integrated into the human work organization, i.e. the workplace. Many iterations of integrating the two intelligences are required. We will discuss a preliminary process-model called “Super8”, in which AI systems must allow for providing feedback on progress as well as being able to incorporate high-level human input in the learning process. The   practical implication of the study will be industrialized in the collaborating 

  • 47.
    Muniz, Jorge
    et al.
    Sao Paulo State University, UNESP (BRA).
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Valemtim, Marta Ligia Pomim
    UNESP (BRA).
    Ramasamy, Sudha
    University West, Department of Engineering Science, Division of Production Systems.
    Shotaro, Yagi
    University of Tokyo, Tokyo (JPN).
    Marins, Fernando A.S.
    UNESP (BRA).
    Voorwald, Herman J.C.
    UNESP (BRA).
    Ericsson, Mikael
    University West, Department of Engineering Science, Division of Production Systems.
    Zhang, Yufeng
    University of Birmingham, Birmingham (GBR).
    Challenges of Engineering Education 5.0 based on I4.0 Policies in Brazil, India, Japan, and Sweden2022In: International Conference on Work Integrated Learning: Abstract Book, Trollhättan: University West , 2022, p. 95-96Conference paper (Other academic)
    Abstract [en]

    Introduction: Industry and academia have placed increasing attention on implementing Industry 4.0 (I4.0) in the production ofgoods and services. Named as Industry 4.0 in Brazil, Made in India in India, Society 5.0 in Japan, andProduktion2030 in Sweden (Ribeiro et al., 2022). Hereafter, we apply I4.0 to simplify, which promises customizedproducts produced in smaller lots, and that repetitive manufacturing tasks can be automated very soon (Karre etal., 2017).Country policies play an important role in pushing different sectors of the economy, aligned as new with theregulatory framework of national and international trade, especially industrial (Aguinis et al., 2020). The implementation of I4.0 literature indicates different specificities in each country, including culture, R&D targets,education and vocational training, and their research opportunities related to how I4.0 affects workers (Jerman etal., 2020). The research-question is: How do different countries approach the opportunities and challenges of Engineering Education 4.0 through similar or different country policies?This study aims to discuss engineering education related to I4.0 policies. This discussion is based on policies fromBrazil, India, Japan, and Sweden related to education and workers 5.0, which include students and employees.Investigating how these countries are adjusting to I4.0 is relevant for national industrial sectors to wish to actefficiently in this new technological context. Industry 4.0 demands new professional skills and will impactemployment. It is noteworthy that this research is in line with the Sustainable Development Goals (SDGs) proposedby the United Nations (UN): Quality Education (SDG-4); o Decent Work and Economic Growth (SDG-8); andIndustry, Innovation, and Infrastructure (ODS-9) which seeks to promote inclusive and sustainableindustrialization and foster innovation. This research aims to contribute to sustainable o rganizational practices;formulation of public policies that alleviate social problems; guidance of professional curricula affected by I 4.0.

    Papers and Data Selection: A literature search was conducted in the Scopus database, which gathers some of the most important journalsrelated to manufacturing technologies with high impact factors, based on the PRISMA method, which refers to aminimum set of evidence-based items to report studies in systematic reviews and meta -analyses (MOHER et al.,2009). The paper set was assembled from the Scopus core collection, using the following search string: “industry4.0” OR “industry 5.0” AND “policies” AND ". The results were narrowed to texts in English, which yielded 1496papers. All titles and abstracts were read, which resulted in a set composed of 14 papers. We also use official documents relating to I4.0 raised from official government websites.

    Comparison of Countries’ Education policies and Industry 4.0: The literature addresses difficulties associated with the implementation of I4.0 in emerging economies (Dalagnore,2018; Hong and Muniz Jr., 2022). Not surprisingly, current literature I4.0 related to technology adoption is themost prevalent theme discussed from a hard, technology-oriented perspective rather than a people-oriented.Production systems are sociotechnical systems, with an explicit understanding that all systems involve ongoinginteractions between people and technology, and they are rapidly transforming virtually all areas of human life,work, and interaction.The European Commission’s (Breque et al., 2021) vision for ‘Industry 5.0’ proposes moves past a narrow andtraditional focus on technology-or economic enabled growth of the existing extractive, production andconsumption driven economic model to a more transformative view of growth that is focused on human progressand well-being based on reducing and shifting consumption to new forms of sustainable, circular and regenerativeeconomic value creation and equitable prosperity. This Human-centric production system design and managementapproach (Industry 5.0) is necessary to support skill development, learning, continuous improvement andcollaboration in the organization (Ribeiro et al., 2022).

    Conclusion: Brazil, India, Japan and Sweden create policies to support their own technological independence. All countriesindicate concern about education and development of skills related to I4.0.It can be concluded that the four countries studied from the perspective of Industry 4.0 an d Engineering Education4.0 are all embarking on their journeys towards increased digitalization in industry and society as a whole. Therealization of the human-centered Society 5.0 was realized and highlighted comparatively early for Japan, whereasin the Europe Union and thus in Sweden the focus of the importance of Industry 5.0 development in parallelIndustry 4.0 has risen up since year 2021.The results indicate that although there are many initiatives of meeting the needs for new competence andknowledge in the era of I4.0 to accommodate Engineering Education 4.0 there are still challenges for futureresearch to move forward in the nexus between I4.0 and I5.0. The result, of studying different countries'policies, highlights that it is imperative, when approaching novel technologies in I4.0 and designing Engineering Education 4.0, to in parallel consider technological implementations with the inclusion of I5.0 aspects and humancentric perspectives.

  • 48.
    Olsson, Anna Karin
    et al.
    University West, School of Business, Economics and IT, Division of Business Administration.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Carlsson, Linnea
    University West, School of Business, Economics and IT, Divison of Informatics.
    A co-workership approach on digital transformation: Towards smart manufacturing2022In: Proceedings of the International Association for Computer Information Systems - Europe June 23, 2022: Virtual Conference, International Association for Computer Information Systems, 2022Conference paper (Other academic)
    Abstract [en]

    Digital transformation refers to the process of organizational change, evolving over time for value creation and appropriation aiding for smart manufacturing (Skog, 2019). Regarding the role of organizational means, there is an embedded dynamic generator of challenges, opportunities, and resources that affect the digital transformation at various organizational levels related to social factors such as values, culture, and trust (Ibid). Earlier studies of the Swedish manufacturing industry imply that as the number of digital technologies increase within organizations, while striving towards becoming a smart factory, cooperation and social factors become more imperative (Björkdahl, 2020). By following this reasoning, understanding organizational prerequisites that facilitate the human-centric perspective in relation to digital transformation is crucial when approaching smart manufacturing by moving from Industry 4.0 (I4.0) towards Industry 5.0 (I5.0) (Navarandi, 2019). It is argued that a prerequisite for digital transformation is the employees’ ability to cross organizational boundaries both horizontally and vertically (Carlsson et al., 2022) challenging management. The aim of this study is to explore organizational prerequisites for co-workership in digital transformation towards smart manufacturing. The concept of the co-workership wheel reflects the employee as an autonomous actor within the organization. As such, co-workership is vital for managing organizational change, e.g., digital transformation, capturing employees’ initiatives and prospects (Andersson, et al. 2021). As illustrated in Figure 1 the co-workership wheel consists of four conceptual pairs: Trust and Openness; Community Spirit and Cooperation; Engagement and Meaningfulness; Responsibility and Initiative. Together these four pairs describe the foundation for co-workership within the organization, feedbacking a development process towards smart manufacturing.

    Inspired by the application of the co-workership wheel in the health care sector (ibid), this study builds on previous work by Carlsson et al. (2022) to further contribute to the exploration of co-workership in the manufacturing sector strengthening the I5.0 emerging research. By applying a qualitative case-study, organizational prerequisites for co-workership in digital transformation are explored (Yin, 2018). The term co-worker is herein applied in a general sense to explore employees’ experiences covering both managerial levels and service functions. The case company is a large manufacturing organization in the Swedish energy sector. In-depth interviews (n=29) were conducted over nine months (Oct. 20 – Jun. 21), exploring co-workers' current and retrospective experiences of the early phases of digital transformation. Referral sampling was applied for selecting informants from functions such as design, quality, production, logistics, digitalization development leaders, and corporate service functions including HR, IT, and financial controllers. Access was granted to six internal documents guiding all employees covering the organization’s strategic work with industrial digitalization, vision, and core values: responsibility, excellence, and innovation. Several rounds of data analysis followed, identifying organizational prerequisites related to each of the four conceptual pairs (Andersson et al., 2020) through a coding scheme based on the co-workership wheel, Findings show that employees interpreted digital transformation as difficult to navigate due to limited communication and cooperation across the organization. Furthermore, the need for trust in digital technologies and employee engagement for transformation are emphasized by informants. Thus, it is argued that an adaptive organizational culture and a focus on learning and competence are necessary organizational prerequisites for translating the means of digital transformation. Managers in the manufacturing sector hence need awareness and understanding of when and how to apply co-workership for transformational change. Manufacturing cultures need to absorb a more human-centric perspective when navigating I4.0, moving in incremental steps encompassing the whole organization, rather than treating digital transformation as scattered and disruptive activities. We argue that the findings give useful implications for manufacturing organizations navigating the challenges of digital transformation to reach the benefits of smart manufacturing. As digital transformation cuts across organizational structures and working processes, there is a need to highlight a human-centric perspective on smart manufacturing by applying the conceptual pairs of the co-workership wheel. Lessons learned show that by applying a co-workership approach with its aspects of trust and openness, community spirit and cooperation, engagement and meaningfulness, responsibility and initiatives, management needs to encourage organizational prerequisites such as an adaptive culture and learning and competence for reaching and sustaining a human-centric perspective on digital transformation.

  • 49.
    Ramasamy, Sudha
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Peralippatt, Saptha
    University West, Department of Engineering Science, Division of Production Systems.
    Perumal, Balasubramanian
    University West, Department of Engineering Science, Division of Production Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    Optimized Online Path Planning Algorithms Considering Energy2021In: Proceedings: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE conference proceedings, 2021, p. 1-08Conference paper (Refereed)
    Abstract [en]

    Plug and produce demonstrators handles multiple processes in the industry, appropriate path planning is essential and at the same time there is an increasing emphasis on more sustainable processes. To ensure the sustainability and automate these processes optimized path planning is required. We present an implementation of a path planning algorithm, which creates a smooth collision free path and considers energy use. In the paper, we demonstrated the implementation of PRM (Probabilistic Road Map) path planning and Dijkstra based optimization algorithm in a simulation environment and thereafter test in a real plug and produce demonstrator. To validate the simulated results the real energy was measured through the signal analyzer online. The measured results outlined in this paper includes; computational time, move along path time, and energy use with different loads. From the experiments and results we conclude that the combination of the two algorithms, PRM with Dijkstra, can be used to generate a collision free optimized path. Here we have considered the distance as the cost function for Dijkstra optimization algorithm and measured the energy of the collision free optimized path. The practical implication of this research is as an enabler for any kind of application where there are large variations of orders e.g., kitting techniques in assembly operations for manufacturing industry.

  • 50.
    Ramasamy, Sudha
    et al.
    University West, Department of Engineering Science, Division of Production Systems.
    Eriksson, Kristina M.
    University West, Department of Engineering Science, Division of Production Systems.
    Perumal, Balasubramaniam
    University West, Department of Engineering Science, Division of Production Systems.
    Peralippatt, Saptha
    University West, Department of Engineering Science, Division of Production Systems.
    Danielsson, Fredrik
    University West, Department of Engineering Science, Division of Production Systems.
    Optimized Path Planning by Adaptive RRT* Algorithm for Constrained Environments Considering Energy2021In: Proceedings 2021: 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE conference proceedings, 2021, p. 1-8Conference paper (Refereed)
    Abstract [en]

    Optimized path planning of robots are necessary for the industries to thrive towards greater flexibility and sustainability. This paper proposes an implementation of a collision-free path with the shortest distance. The novelty of the work presented is the new ARRT*(Adaptive Rapidly exploring Random Tree Star) algorithm, which is modified from the RRT*(Rapidly exploring Random Tree Star). In a constraint environment, RRT* algorithms tend to fail when searching for suitable collision-free paths. The proposed ARRT* algorithm gives an optimized feasible collision-free paths in a constraint environment. The feasibility to implement RRT* and ARRT* in a Multi Agent System as a path agent for online control of robots is demonstrated. We have created a digital twin simulated environment to find a collision-free path based on these two algorithms. The simulated path is tested in real robots for feasibility and validation purpose. During the real time implementation, we measured the following parameters: the algorithm computation time for generating a collision-free path, move along time of the path in real time, and energy consumed by each path. These parameters were measured for both the RRT* and the ARRT* algorithms and the test results were compared. The test results were showing that ARRT* performs better in a constrained environment. Both algorithms were tested in a Plug and Produce setup and we find that the generated paths for both algorithms are suitable for online path planning applications.

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