A novel method to build knowledge graph models for the configuration and operation design of smart and connected industrial products

• DOI: 10.1093/jcde/qwae033
• Publication Date: 2024-04-04T00:31:01Z
• Authors: Yuqian Yang; Maolin Yang; Siwei Shangguan; Yifan Cao; Pingyu Jiang
• Keywords: Knowledge graph; Configuration design

Abstract Smart and connected industrial products (SCIPs), characterized by their capabilities of self-monitoring, environment awareness, machine–machine/machine–human communication collaboration, intelligent decision-making, etc., have become the fundamental elements for cyber-physical systems, digital twin, internet things, etc. Configuring components in SCIPs modeling interaction operation mechanisms are important during design. However, existing product design methods were originally developed none smart products. This could limit accuracy SCIP stage consequently, it may cause more reworks implementation designed SCIPs. In this regard, a configuration method is established, including (i) meta knowledge graph (KG)-based physical system status monitoring required SCIP, (ii) event-state swimlane flowchart-based analysis dynamic interaction, operation, data among components, (iii) KG based overall workflow, self-updating SCIP. Compared with methods, work provides specific not only static customized SCIPs, but also acquisition/storing/transmitting, function configured using kind KG. The both human-readable computer-programmable, can self-update according to predefined reasoning algorithms robot-based grinding processing line used as case study.