The design space of production planning and control for industry 4.0

In industrial production, distributed control is perceived to be a promising approach for dealing with challenges arising from the increasing dynamical and structural complexity in that field. Currently, future production systems are envisioned to be digitalized and networked systems bearing names such as Industry 4.0, Manufacturing 2.0, Internet of Things, and many others. These visions share the idea of assigning tasks of production control to intelligent objects, such as machines, parts, and products, in order to attain higher flexibility, higher adaptability, and therefore a higher logistics performance. However, limited information and restricted computation capacity may have negative effects: The production system behavior depends on the decisions made by intelligent objects with individual and selfish systems of objectives. This can deteriorate both the stability and the quality of achieved production planning and control solutions. This trade-off situation has led researchers to the belief that a combination of centralized and distributed-as well as of local and global-decision making in control might be the key to an improved and stable logistics performance. However, little is known about the mechanics of these combined, semi-heterarchical control structures. Based on a profound literature review, we compare the approaches and insights from the different research domains in order to classify design decisions that can be made already in the planning phase of a new production system. We take a first step towards the validation of our classification by mapping four paradigms of distributed control into it. Our research can help the designers of future production systems to understand how to avoid the emergence of myopic behavior, and it may serve as a basis for creating new control approaches by exploring the design space. (C) 2018 Elsevier B.V. All rights reserved.