The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is the integration of advanced sensor and actuator technologies and communications solutions. This work provides an extensive overview of these technologies and highlights that the design of future workplaces should be based on the concept of intelligent space.
The Fourth Industrial Revolution means the digital transformation of production systems. Cyber-physical systems allow for the horizontal and vertical integration of these production systems as well as the exploitation of the benefits via optimization tools. This article reviews the impact of Industry 4.0 solutions concerning optimization tasks and optimization algorithms, in addition to the identification of the new R&D directions driven by new application options. The basic organizing principle of this overview of the literature is to explore the requirements of optimization tasks, which are needed to perform horizontal and vertical integration. This systematic review presents content from 900 articles on Industry 4.0 and optimization as well as 388 articles on Industry 4.0 and scheduling. It is our hope that this work can serve as a starting point for researchers and developers in the field.
This article provides a review about how uncertainties in increasingly complex production and supply chains should be addressed in scheduling tasks. Uncertainty management will be particularly important in Industry 5.0 solutions that will require the close integration of operators and technical systems. To prepare for these challenging developments, this work reviews the sources of uncertainty and the scheduling algorithms that deal with the different types of models developed to handle the uncertain nature of the elements and the environment of complex technological systems. The paper not only identifies the challenges, but also the main building blocks that can help to manage and reduce uncertainties based on the I4.0 and I5.0 solutions. We hope that this study will serve as a starting point for R&D projects and algorithm developments, which will be needed primarily in the field of multi-agent, multistage and inverse optimizations.
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