A Decision-Making Methodology Based on Expert Systems Applied to Machining Tools Condition Monitoring

Manuel Casal-Guisande, Alberto Comesaña-Campos, Alejandro Pereira, José-Benito Bouza-Rodríguez and Jorge Cerqueiro-Pequeño
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Manuel Casal-Guisande: Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
Alberto Comesaña-Campos: Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
Alejandro Pereira: Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
José-Benito Bouza-Rodríguez: Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain
Jorge Cerqueiro-Pequeño: Department of Design in Engineering, University of Vigo, 36208 Vigo, Spain

Mathematics, 2022, vol. 10, issue 3, 1-30

Abstract: The workers operating and supervising machining tools are often in charge of monitoring a high number of parameters of the machining process, and they usually make use of, among others, cutting sound signals, for following-up and assessing that process. The interpretation of those signals is closely related to the operational conditions of the machine and to the work environment itself, because such signals are sensitive to changes in the process’ input parameters. Additionally, they could be considered as a valid indicator for detecting working conditions that either negatively affect the tools’ lifespan, or might even put the machine operators themselves at risk. In light of those circumstances, this work deals with the proposal and conceptual development of a new methodology for monitoring the work conditions of machining tools, based on expert systems that incorporate a reinforcement strategy into their knowledge base. By means of the combination of sound-processing techniques, together with the use of fuzzy-logic inference engines and hierarchization methods based on vague fuzzy numbers, it will be possible to determine existing undesirable behaviors in the machining tools, thus reducing errors, accidents and harmful failures, with consequent savings in time and costs. Aiming to show the potential for the use of this methodology, a concept test has been developed, implemented in the form of a short case study. The results obtained, even if they require more extensive validation, suggest that the methodology would allow for improving the performance and operation of machining tools, as well as the ergonomic conditions of the workplace.

Keywords: tool condition monitoring; fuzzy logic; vague fuzzy sets; expert systems; risk (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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