Industry 4.0 technologies are transforming manufacturing, while Industry 5.0 emphasizes sustainability, resilience, and human-centricity, increasing the need for continuous upskilling and reskilling. This paper investigates the Industry 4.0 technologies demanded by Swedish industrial employees and how engagement with these technologies’ influence competence development. Based on empirical data from a longitudinal competence development initiative within a Swedish industry–university partnership, the study presents industrial work-integrated learning as an approach for coproducing short courses that enhance Industry 4.0 literacy. The findings demonstrate that Industry 4.0 technology literacy supports the development of both technical and human-centric competencies, including digital skills, creativity, adaptability, and collaboration. The study contributes to smart technology management by highlighting how competence based education and industrial work-integrated learning can support digital transformation and align Industry 4.0 advancements with the human-centric vision of Industry 5.0

Capacitive sensors are extensively utilized in manufacturing to detect surface property variations, level sensing, and proximity sensing in assembly lines. They provide feedback to robotic arms, integrate with machine tools to monitor tool wear, control static electricity, and assist in materials sorting and positioning. To ensure their outputs are compatible with subsequent processing equipment, capacitive sensors often incorporate signal conditioning units. These units are crucial for optimizing sensor performance, converting capacitance changes into voltage, current, frequency, or time duration signals, and providing amplification, impedance matching, filtering, and linearization. Linearity is a vital design parameter for capacitive sensors, ensuring accurate and consistent measurements across various applications. Achieving linearity simplifies calibration, enhances predictability and maintains a direct proportionality between the sensor’s output and the measured parameter, thereby improving the overall reliability and performance of the sensing system.

This review article comprehensively analyzes the signal conditioning techniques used in capacitive sensors, emphasizing the importance of linearity. By exploring these techniques, the article offers valuable insights that guide the development of more accurate, reliable, and efficient capacitive sensing systems, which are increasingly essential in advanced manufacturing and automation. 

Policies influence countries' economic sectors, such as the industrial sector. Industry 4.0 (I4.0) demands employees upskilling and can impact unemployment and HIE curricula. The paper proposes to bring forth, analyse engineering education related to I4.0 policies. The paper compares policies related to Workers 5.0 discussing education and training for both regular students and employees (white and blue collars), from polar cases representing emerging countries (Brazil & India), and developed countries (Japan and Sweden). These countries have created policies to become independent and improve their innovation ecosystem. The I4.0 literature and white paper indicate different country-specificities. The paper explores research gaps related to I4.0 and its effect on workers’ competencies; which factors to consider in Human Resource Management; understanding impacts on country education. Comparing how these different countries adjust to I4.0 may contribute to manufacturing sectors addressing this new digital context, contributing to theoretical advancement and informing policy and practice in higher education. The findings indicate education and upskilling concerns, and these countries are reviewing their Engineering Education towards increased digital transformation in the whole society.

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.