Improvement of Delivery Reliability by an Intelligent Control Loop between Supply Network and Manufacturing

Abstract

Manufacturing companies operate in an environment characterized as increasingly volatile, uncertain, complex and ambiguous. At the same time, their customer orientation makes it increasingly important to ensure high delivery reliability. Manufacturing sites within a supply network must therefore be resilient against events from the supply network. This requires deeper integration between the supply network and manufacturing control. Therefore, this article presents a concept to connect supply network and manufacturing more closely by integrating events from the supply network into manufacturing control’s decisions. In addition to the requirements, the concept describes the structure of the system as a control loop, a reinforcement learning-based controlling element as the central decision-making component, and the integration into the existing production IT landscape of a company as well as with latest internet of things (IoT) devices and cyber-physical systems. The benefits of the concept were elaborated in expert workshops. In summary, this approach enables an effective and efficient response to events from the supply network through smarter manufacturing control, and thus more resilient manufacturing.

Keywords

• supply network
• resilience
• manufacturing control
• closed-loop control
• machine learning
• reinforcement learning