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

Authors :
Xuedong Zhang
Wenlei Sun
Shijie Song
Chen Lu
Source :
Applied Sciences, Vol 14, Iss 20, p 9321 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

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.

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
20
Database :
Directory of Open Access Journals
Journal :
Applied Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.1f2de8a35a46e3bb6b806dce0e09a2
Document Type :
article
Full Text :
https://doi.org/10.3390/app14209321