Performance Measurement in Sensorized Sociotechnical Manufacturing Environments

Abstract

Industry 4.0 entails the digitization of the shopfloor operations combining technologies such as internet of things-enabled sensing, cyber-physical systems, data analytics, augmented reality, and wearable devices and robots that transform the manufacturing environment into a workplace of human-machine interactive symbiosis. With the digitization of the manufacturing environment, new opportunities emerge concerning performance measurement as new sources of real-time data become available, including data collated from the operator on the shopfloor. Traditionally, the human dimension had been disjoint from the situation analysis of shopfloor performance that drives evidence based decision making. This paper presents the features and advantages of performance measurement in human-workplace interactive manufacturing where detailed data on human performance is provided by sensors and utilized to improve the performance goals. The paper is concluded with a discussion on the impact of context information management for interactive manufacturing workplaces, as a means of delivering more informed situational awareness, a critical enabler for humanmachine interaction, as well as for handling complexity in disparate data sources.

Augmenting the Production Operators for Continuous Improvement

“…Application of AR will support operators through the provision of detailed work instructions / knowledge points when performing their complex tasks, ensuring the most efficient transfer of design information to physical products. AR tools with embedded motion sensors also aid sensing and receiving data from operators, completing the missing links in captured data from processes, identifying the operators' physical and cognitive situation, and enabling a full and detailed digital view of process steps together with information systems and machine control systems [16].…”

“…Such data allow analysis and evaluation of well-being (e.g., satisfaction, engagement, stress levels) and productivity (e.g., work performance, skills match) of operators both in real-time and longer-terms [16].…”

“…Examples of motion data that can be captured by AR tools and can define the psycho-physiological status of operators are: breath/heart rate, skin conductance and movement of relevant body segments [16].…”

Environment 4.0: How digitalization and machine learning can improve the environmental footprint of the steel production processes

“…Finally, in order to be fruitful for all the involved workers and stakeholders, the outcomes of all the developed data analyses, interpretations as well as of the different optimization stages must be proposed in a practical and understandable way, by taking into account that plant managers and technical personnel are not necessary ICT specialists. To this aim, all the most updated technologies, such as advanced Human-Machine Interfaces and Augmented Reality (AR), can be exploited [43][44][45]. For instance, in literature the importance of exploiting Internet of Things (IoT), Virtual Reality (VR) and AR in remanufacturing is analyzed within the implementation of CE models [46].…”