Pathogenic bacterial growth detection and monitoring is an important scientific process in the field of quality control in the food, water, and medical industries. Very-large-scale process of such bacteria growth monitoring is possible only with an automated process. The mechanism must make sure that the sample is continuously monitored, and detected, data is communicated to supervisors and managers, and data is stored historically retrievable for quality control and analysis. A manual bacteria inspection among the Petri dishes incubated of such bacterial growth in food processing was attempted for automation. The manual inspection in a microbiological industry involves; an operator inspecting the input petri discs to check if there are bacteria, writing down the barcode of the corresponding petri dish, and then sorting the Petri discs depending on the bacterial growth. In this automation attempt of automatizing this petri-disc inspection, the project was split into two phases. 1. Building a vision system to detect bacteria, developing of an algorithm to quantify the growth, and registering the barcode in a registry. 2. The second phase is to design a robot system with programming and define the layout of the station. The development of an intelligent robotized machine vision automated system proves the concept of a major industrial practice that has the potential to significantly increase the quality and productivity of bacterial growth, with increased throughput.

The purpose of this article is to investigate a suitable path planning algorithm for a multi-agent-based Plug & Produce system that can run online during manufacturing. This is needed since in such systems, resources can move around frequently, making it hard to manually create robot paths. To find a suitable algorithm and verify that it can be used online in a Plug & Produce system, a comparative study between various existing sampling-based path planning algorithms was conducted. Much research exists on path planning carried out offline; however, not so much is performed in online path planning. The specific requirements for Plug & Produce are to generate a path fast enough to eliminate manufacturing delays, to make the path energy efficient, and that it run fast enough to complete the task. The paths are generated in a simulation environment and the generated paths are tested for robot configuration errors and errors due to the target being out of reach. The error-free generated paths are then tested on an industrial test bed environment, and the energy consumed by each path was measured and validated with an energy meter. The results show that all the implemented optimal sampling-based algorithms can be used for some scenarios, but that adaptive RRT and adaptive RRT* are more suitable for online applications in multi-agent systems (MAS) due to a faster generation of paths, even though the environment has more constraints. For each generated path the computational time of the algorithm, move-along time and energy consumed are measured, evaluated, compared, and presented in the article.

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.

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.

The theory and applications of Smart Factories and Industry 4.0 are increasing the entry into the industry. It is common in industry to start converting exclusive parts, of their production, into this new paradigm rather than converting whole production lines all at once. In Europe and Sweden, recent political decisions are taken to reach the target of greenhouse gas emission reduction. One possible solution is to replace concrete in buildings with Cross Laminated Timber. In the last years, equipment and software that have been custom made for a certain task, are now cheaper and can be adapted to fit more processes than earlier possible. This in combination, with lessons learned from the automotive industry, makes it possible to take the necessary steps and start redesigning and building tomorrows automated and flexible production systems in the wood industry. This paper presents a proof of concept of an automated inspection system, for wood surfaces, where concepts found in Industry 4.0, such as industrial Internet of things (IIoT), smart factory, flexible automation, artificial intelligence (AI), and cyber physical systems, are utilized. The inspection system encompasses, among other things, of the shelf software and hardware, open source software, and standardized, modular, and mobile process modules. The design of the system is conducted with future expansion in mind, where new parts and functions can be added as well as removed.

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.

New aero engine design puts new demands on the manufacturing methods with increased automation level. Therefore, the use of vision sensors for control and guiding of industrial robots is being increasingly used. In such system, it is need to customise the machine vision system with real components in the real environment which is normally done close to the start-up of the production. This paper addresses a new concept for designing, programming, analysing, testing and verifying a machine vision application early in the design phase, called Virtual Machine Vision. It is based on a robot simulation software where the real machine vision application is simulated before the implementation in the production line. To verify the Virtual Machine Vision concept an advanced stereo vision application was used. Using two captured images from the robot simulated environment, camera calibration, image analysis and stereo vision algorithms are applied to determine a desired welding joint. The information of the weld joint, i.e. robot position and orientation for the weld path, are sent from the machine vision system to the robot control system in the simulation environment and the weld path is updated. The validation of the Virtual Machine Vision concept using the stereo vision application is promising for industrial use, and it is emphasised that the same programs are used in the virtual and real word.

The geometrical quality of a welded assembly is to some extent depending part positions before welding. Here, a design of experiment is set up in order to investigate this relation using physical tests in a controlled environment. Based on the experimental results it can be concluded that the influence of part position before welding is significant for geometrical deviation after welding. Furthermore, a working procedure for a completely virtual geometry assurance process for welded assemblies is outlined. In this process, part variations, assembly fixture variations and welding induced variations are important inputs when predicting the capability of the final assembly.

Thermography has proven to be a suitable nondestructive testing method for automatic crack inspection of welds. However automatic weld inspection raises challenges. E.g. the position of the weld might not be exactly as the predefined weld seam, and a weld joint tracking system is needed. To reduce the number of equipment used, a solution is presented in this papers. The infrared camera in the thermography system is a carrier of information of the weld path. This is used for the weld joint tracking system. It is shown that the weld joint tracker is fast enough for an on-line automatic inspection.