Prescriptive system for reconfigurable manufacturing systems considering variable demand and production rates

• Type: Article in International Conference Proceedings Book
• Date: 2020

Authors

Baltazar, C (Author) Other; Reis, J (Author) Other; Gil Manuel Gonçalves (Author) FEUP

Conference proceedings International

Title: CEUR Workshop Proceedings

Pages: 38-45

1st Eclipse Research International Conference on Security, Artificial Intelligence and Modeling for the Next Generation Internet of Things, SAM IoT 2020

17 September 2020 through 18 September 2020

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: P-00T-2XK

Abstract (EN): The current market is dynamic and, consequently, industries need to be able to meet unpredictable market changes in order to remain competitive. To address the change in paradigm, from mass production to mass customization, manufacturing flexibility is key. Moreover, current digitalization of the industry opens opportunities regarding real-time decision support systems allowing the companies to make strategic decisions, and gain competitive advantage and business value. The main contribution of this paper is a proof of concept Prescriptive System with a highly parameterizable simulation environment catered to meet the needs of Reconfigurable Manufacturing Systems allied with an optimization module that takes into consideration productivity, market demand and equipment degradation. With this system, the effects of different throughput rates are monitored which results in better recommendations to mitigate production losses due to maintenance actions while taking into consideration the health status of the remaining assets. In the proposed solution the simulation module is modeled based on Directed Acyclic Graphs and the optimization module based on Genetic Algorithms. The results were evaluated against two metrics, variation of pieces referred as differential and availability of the system. Analysis of the results show that productivity in all testing scenarios improves. Also, in some instances, availability slightly increases which shows promising indicators. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Language: English

Type (Professor's evaluation): Scientific