Using Petri Nets and 4M1E Identification Resolution for Manufacturing Process Control and Information Tracking: Case Study of Transformer Coil Production

• Published in: Applied sciences Vol. 14; no. 20; p. 9321
• Main Authors: Zhang, Xuedong, Sun, Wenlei, Song, Shijie, Lu, Chen
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-10-2024
• Subjects: Blockchain; Case studies; Control equipment industry; Data analysis; Data processing; Design; Efficiency; Electric transformers; extenics; Identification; identification and resolution; Industrial production; Information management; information traceability; Internet; Machine learning; Machinery; Magneto-electric machines; Manufacturing; Methods; petri net; Process controls; production process; Set theory; System theory; Systems engineering; transformer coil; United Kingdom
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app14209321

To solve the problems of chaotic information management and difficult traceability in the manufacturing process of transformer coils, a traceability and management method oriented towards the manufacturing process of transformer coils has been proposed. This method integrates industrial internet identification resolution and extension of Petri net modeling theory. A comprehensive identification and resolution framework for coil manufacturing processes has been constructed. In this manuscript, the authors proposed an industrial data-sharing space based on the producer-consumer model with unified coding identification. This enables information sharing for all resources, including personnel, machinery, materials, methods, environment, and measurements. A method for modeling extensible identification primitives of coil manufacturing process information was proposed, which formalizes the correlation and data structure of process information. A Petri net model for the comprehensive acquisition and integration of elemental information in coil manufacturing processes, as well as a mathematical model for quality traceability, were constructed, thereby forming a complete path for quality traceability information. Finally, based on the method proposed above, a software and hardware environment for identification and traceability for coil manufacturing was established. Taking a certain type of coil as an example, validation was carried out; the results indicate a significant enhancement in the production management and information traceability capabilities of the coil production workshop. This study provides reference and guidance for the process traceability management of power equipment manufacturing.