Wireless Control for Smart Manufacturing: Recent Approaches and Open Challenges

Proceedings of the IEEE, vol. 109, pp. 441–467

Abstract

Smart manufacturing aims to overcome the limitations of today's rigid assembly lines by making the material flow and manufacturing process more flexible, versatile, and scalable. The main economic drivers are higher resource and cost efficiency as the manufacturers can more quickly adapt to changing market needs and also increase the lifespan of their production sites. The ability to close feedback loops fast and reliably over long distances among mobile robots, remote sensors, and human operators is a key enabler for smart manufacturing. Thus, this article provides a perspective on control and coordination over wireless networks. Based on an analysis of real-world use cases, we identify the main technical challenges that need to be solved to close the large gap between the current state of the art in industry and the vision of smart manufacturing. We discuss to what extent existing control-over-wireless solutions in the literature address those challenges, including our own approach toward a tight integration of control and wireless communication. In addition to a theoretical analysis of closed-loop stability, practical experiments on a cyber-physical testbed demonstrate that our approach supports relevant smart manufacturing scenarios. This article concludes with a discussion of open challenges and future research directions.

Authors 6

1. Dominik Baumann

   Max Planck Institute for Intelligent Systems

   Affiliation as printed

   Intelligent Control Systems Group, Max Planck Institute for Intelligent Systems, Stuttgart, Germany

2. Fabian Mager

   Technische Universität Dresden

   Affiliation as printed

   Networked Embedded Systems Lab, Technische Universität Dresden (TU Dresden), Dresden, Germany

3. Ulf Wetzker

   Fraunhofer Institute for Integrated Circuits IIS, Division Engineering of Adaptive Systems EAS · Fraunhofer Institute for Integrated Circuits

   Affiliation as printed

   Division Engineering of Adaptive Systems, Industrial Wireless Communication Group, Fraunhofer Institute for Integrated Circuits IIS, Dresden, Germany

4. Lothar Thiele

   ETH Zurich

   Affiliation as printed

   Computer Engineering Group, ETH Zurich, Zürich, Switzerland

5. Marco Zimmerling

   Technische Universität Dresden

   Affiliation as printed

   Networked Embedded Systems Lab, Technische Universität Dresden (TU Dresden), Dresden, Germany

6. Sebastian Trimpe Aachen Institute for Data Science in Mechanical Engineering

   Max Planck Institute for Intelligent Systems · RWTH Aachen University

   Affiliation as printed

   Institute for Data Science in Mechanical Engineering, RWTH Aachen University, Aachen, Germany

   Intelligent Control Systems Group, Max Planck Institute for Intelligent Systems, Stuttgart, Germany