PyMES: Distributed Manufacturing Execution System for Flexible Industry 4.0 Cyber-Physical Production Systems

Abstract

Industry 4.0 production systems have to support flexibility in products, processes, and production resources. To meet the required level of flexibility, Industry 4.0 production systems have to be capable of interpreting and executing production plans, which consist of generic actions (such as robotic manipulations or transport of material and products). In industrial practice, Manufacturing Execution Systems (MES) together with Supervisory Control and Data Acquisition (SCADA) systems are usually responsible for such tasks. This paper proposes a new architecture of MES implemented in Python that is able to verify, interpret, and execute production plans automatically generated by an AI planner. Moreover, the proposed MES supports running in a distributed way in several instances, where each instance is able to interpret a location-specific part of a production plan. All MES instances are synchronized and the current global or partial (per each instance) production progress can be observed via HTTP/REST API. The proposed approach is demonstrated in practice on the Industry 4.0 Testbed use-case, utilized for evaluation.