Towards the Resilient Operator 5.0: The Future of Work in Smart Resilient Manufacturing Systems

Most recently, the COVID-19 pandemic has shown industries all around the world that their current manufacturing systems are not as resilient as expected and therefore many are failing. The workforce is the most agile and flexible manufacturing resource and simultaneously the most fragile one due to its humanity. By making human operators more resilient against a range of factors affecting their work and workplaces, enterprises can make their manufacturing systems more resilient. This paper introduces "The Resilient Operator 5.0" concept, based on human operator resilience and human-machine systems\u27 resilience, providing a vision for the future of work in smart resilient manufacturing systems in the emerging Industry 5.0 hallmark. It suggests how to achieve appropriate smart manufacturing systems\u27 resilience from a human-centric perspective through the means of the Operator 4.0 typology and its related technical solutions

Smooth and Resilient Human–Machine Teamwork as an Industry 5.0 Design Challenge

Smart machine companions such as artificial intelligence (AI) assistants and collaborative robots are rapidly populating the factory floor. Future factory floor workers will work in teams that include both human co-workers and smart machine actors. The visions of Industry 5.0 describe sustainable, resilient, and human-centered future factories that will require smart and resilient capabilities both from next-generation manufacturing systems and human operators. What kinds of approaches can help design these kinds of resilient human–machine teams and collaborations within them? In this paper, we analyze this design challenge, and we propose basing the design on the joint cognitive systems approach. The established joint cognitive systems approach can be complemented with approaches that support human centricity in the early phases of design, as well as in the development of continuously co-evolving human–machine teams. We propose approaches to observing and analyzing the collaboration in human–machine teams, developing the concept of operations with relevant stakeholders, and including ethical aspects in the design and development. We base our work on the joint cognitive systems approach and propose complementary approaches and methods, namely: actor–network theory, the concept of operations and ethically aware design. We identify their possibilities and challenges in designing and developing smooth human–machine teams for Industry 5.0 manufacturing systems

Augmenting the Production Operators for Continuous Improvement

This paper discusses how continuous improvement activities can be supported by augmenting the operators in production. After a brief literature background, real life case examples from manufacturing companies are provided and discussed. Enabling technologies, specifically AR and embedded sensors, can guide the operators in execution of their tasks, quality verification of work done step by step, and data collection from both manual and automated operations in much higher levels of details. Collected data provides an empirical foundation for data-driven analysis and improvement potentials in production and quality operations. The paper contributes to theory and practice by providing research-based innovation experiences on this emerging topic of interest for manufacturing companies.acceptedVersio

Human centric collaborative workplace: the human robot interaction system perspective

The implementation of smart technologies and physical collaboration with robots in manufacturing can provide competitive advantages in production, performance and quality, as well as improve working conditions for operators. Due to the rapid advancement of smart technologies and robot capabilities, operators face complex task processes, decline in competences due to robots overtaking tasks, and reduced learning opportunities, as the range of tasks that they are asked to perform is narrower. The Industry 5.0 framework introduced, among others, the human-centric workplace, promoting operators wellbeing and use of smart technologies and robots to support them. This new human centric framework enables operators to learn new skills and improve their competencies. However, the need to understand the effects of the workplace changes remain, especially in the case of human robot collaboration, due to the dynamic nature of human robot interaction. A literature review was performed, initially, to map the effects of workplace changes on operators and their capabilities. Operators need to perform tasks in a complex environment in collaboration with robots, receive information from sensors or other means (e.g. through augmented reality glasses) and decide whether to act upon them. Meanwhile, operators need to maintain their productivity and performance. This affects cognitive load and fatigue, which increases safety risks and probability of human-system error. A model for error probability was formulated and tested in collaborative scenarios, which regards the operators as natural systems in the workplace environment, taking into account their condition based on four macro states; behavioural, mental, physical and psychosocial. A scoping review was then performed to investigate the robot design features effects on operators in the human robot interaction system. Here, the outcomes of robot design features effects on operators were mapped and potential guidelines for design purposes were identified. The results of the scoping review showed that, apart from cognitive load, operators perception on robots reliability and their safety, along with comfort can influence team cohesion and quality in the human robot interaction system. From the findings of the reviews, an experimental study was designed with the support of the industrial partner. The main hypothesis was that cognitive load, due to collaboration, is correlated with quality of product, process and human work. In this experimental study, participants had to perform two tasks; a collaborative assembly and a secondary manual assembly. Perceived task complexity and cognitive load were measured through questionnaires, and quality was measured through errors participants made during the experiment. Evaluation results showed that while collaboration had positive influence in performing the tasks, cognitive load increased and the temporal factor was the main reason behind the issues participants faced, as it slowed task management and decision making of participants. Potential solutions were identified that can be applied to industrial settings, such as involving participants/operators in the task and workplace design phase, sufficient training with their robot co-worker to learn the task procedures and implement direct communication methods between operator and robot for efficient collaboration

Technology acceptance and leadership 4.0: A quali-quantitative study

With the rapid advancement of Industry 4.0, new technologies are changing the nature of work and organizations. Nevertheless, technology acceptance is still an open issue and research, and practice interventions should investigate its antecedents and implement actions in order to reduce the risks of resistance and foster acceptance and effective usage of the new tools and systems. This quali-quantitative study was aimed at exploring perceptions about Industry 4.0 and its transformations and investigating job antecedents of technology acceptance. Whilst not many studies in the literature on technology acceptance have considered workers’ well-being, in this study, its association with work engagement has also been examined. The qualitative study used focus groups to collect perceptions of 14 key roles in a company that was implementing Industry 4.0. In the same company, the quantitative study involved 263 employees who filled in a questionnaire. The results confirmed that both job resources, namely supervisor support and role clarity, were antecedents of technology acceptance, which, in turn, was associated with work engagement. This study provides useful suggestions for interventions aimed at foster technology acceptance and workers’ well-being in companies that are facing Industry 4.0 transformations. Particularly, investments in both leadership 4.0 development and communication programs are essential

how to improve worker s well being and company performance a method to identify effective corrective actions

Abstract In manufacturing context, social dimension is often neglected. With Industry 4.0, companies focus more on technologies and data. However, human continues to play a key role in cyber-physical systems and company growth. This work proposes a method to help the company to evaluate workers' experience and identify the optimal solution to improve workers' well-being and company performance. It starts from personalized social analysis within a production plant to identify ergonomics problems and intelligently suggest effective corrective actions. The latter are selected achieving the best trade-off between social, economic and productive aspects. Three case studies are proposed to validate the method

Enfoques y tecnologías para la industria 5.0 centrada en el ser humano

A little less than a decade after the emergence of Industry 4.0 in the industrial world, the new paradigm 5.0 is gaining ground, which is simultaneously reflected in the definition of a smart society. In fact, we are witnessing an innovative transition that defines the pace of technological, but also economic and social change. Starting from the innovations of the fourth industrial revolution and from the study of reference guidelines of European Commission (2021) Industry 5.0 “repositions” technologies completely at the service of people and the whole of humanity. The research aims to identify and explore the points of contact and implementations arising from the transition from paradigm 4.0 to the human-centric approach 5.0. Through a comparative analysis of case studies and best practices in the industrial field it is possible to frame and define the future scenarios of manufacturing that see human and machine synchronized and synergistically working together to improve the efficiency of production.Poco menos de una década después de la aparición de la Industria 4.0 en el mundo industrial, gana terreno el nuevo paradigma 5.0, que se refleja simultáneamente en la definición de una sociedad inteligente. De hecho, asistimos a una transición innovadora que define el ritmo del cambio tecnológico, pero también económico y social. Partiendo de las innovaciones de la cuarta revolución industrial, la Industria 5.0 "reposiciona" completamente las tecnologías al servicio de las personas y de toda la humanidad. La investigación pretende identificar -mediante un análisis comparativo de estudios de casos y mejores prácticas- los puntos de contacto y las implementaciones derivadas de la transición del paradigma 4.0 al enfoque centrado en el ser humano 5.0 para definir los escenarios futuros de la fabricación que ven al hombre y a la máquina trabajando juntos de forma sincronizada y sinérgica para mejorar la eficiencia de la producción

Human-centered design for improving the workplace in the footwear sector

Abstract Especially in the footwear sector, the transition from the mass production to the mass customization increasingly requires Industry 4.0 solutions that do not reduce the human contribution to production processes but facilitate and value it to increase the job satisfaction. In this context, this paper proposes a method to (re)design the workplace according to a multiperspective ergonomic assessment. It efficaciously combines the analysis of physiological and environmental parameters by Internet-of-Things, the ergonomics risks identification by experts and the subjective evaluation of workers well-being. The method has been experimented in an Italian factory that produces customized shoes for the luxury market