A vision for the Operator 4.0 is presented in this paper in the context of human cyber-physical systems and adaptive automation towards human-automation symbiosis work systems for a socially sustainable manufacturing workforce. Discussions include base concepts and enabling technologies for the development of human-automation symbiosis work systems in Industry 4.0.

This paper presents a framework for developing extended reality (XR) systems within manufacturing context. The aim of this study is to develop a systematic framework to improve the usability and user acceptance of future XR systems. So that manufacturing industry can move from the “wow effect” of XR demonstrators into the stage whereas XR systems can be successfully integrated and improve the conventional work routines. It is essential to ensure the usability and user acceptance of XR systems for the wider adoption in manufacturing. The proposed framework was developed through six case studies that covered different XR system developments for different application areas of manufacturing. The framework consists of five iterative phases: (1) requirements analysis, (2) solution selection, (3) data preparation, (4) system implementation and (5) system evaluation. It is validated through one empirical case and seven identified previous studies, which partly aligned with the proposed framework. The proposed framework provides a clear guideline on the steps needed to integrate XR in manufacturing and it extends the XR usage with increased usability and user acceptance. Furthermore, it strengthens the importance of user-centered approach for XR system development in manufacturing.

Collaborative robots becomes more and more common in lab environment and soon also in industry. In order to create resource- and volume flexibility, dynamic and smart automation could be seen as an answer. This paper has investigated the collaborative robots UR3 and UR5 for O-ring assembly and final assembly, compared to the current state which is performed manually. The methodology Dynamo++ was used for measurement and analysis in terms of LoA (cognitive and physical), cycle-time and quality. Furthermore, automation strategy, safety and easiness of programming was investigated. Results show that collaborative robots have great potential in the middle product volume area. A lot of time, layout space and money could be saved with these solutions. However, standards and safety has to be investigated further in order to reach its fully potential

Human-centricity in manufacturing is becoming an essential enabler to achieve social sustainable manufacturing. In particular, human-centric automation can offer new means to increase competitiveness in the face of new social challenges for the factories of the future. This paper proposes a Human-Centred Reference Architecture that can structure and guide efforts to engineer Next Generation Balanced Automation Systems featuring adaptive automation that take into account various criteria in the operating environment such as time-lapse, performance degradation, age-, disability- and inexperience-related limitations of operators to increase their working capabilities.

Purpose: The paper aims to discuss the importance of considering both the physical and cognitive automation when aiming for a flexible or reconfigurable assembly system. This is done in order to handle the increased demand for mass customized production and to maintain or improve the social sustainability within the company.Design/methodology/approach: The methodologies used in this paper are a theoretical review about task allocation and levels of automation and a methodology called DYNAMO++ for the industrial case studies.Findings: The paper provides both theoretical and empirical insights about the importance of considering both the cognitive and physical automation when aiming for a reconfigurable assembly system.Research limitations/implications: The paper will only discuss the cognitive strategy from a social sustainability perspective and not from an economical or environmental angle.Practical implications: The paper presents data from three industrial case studies, mostly in the automotive industry. The result points towards a need for a more structured and quantitative method when choosing automation solutions, furthermore an increased use of cognitive automation solution.Social implications: The results from the case studies show that when the complexity and variety of products increases, a cognitive support for the operators is needed. This strengthens the theory of a need for a cognitive automation strategy within companies.Originality/value: The paper demonstrates an advance in the state of the art in task allocation. The concept model and the DYNAMO++ method can be seen as a step closer towards quantitative measures of task allocation (i.e. changes in both physical and cognitive LoA) and dynamic changes over time.