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Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts

Abbas, Adel Taha; Abubakr, Mohamed; Elkaseer, Ahmed; El Rayes, Magdy M.; Mohammed, Monis Luqman; Hegab, Hussien

Abstract:
The continuous pursue of sustainable manufacturing is motivating the utilization of new advanced technology, especially for hard to cut materials. In this study, an adaptive approach for optimization of machining process of AISI 4340 using wiper inserts is proposed. This approach is based on advance yet intuitive modeling and optimization techniques. The approach is based on Artificial Neural Network (ANN), Multi-Objective Genetic Algorithm (MOGA), as well as Linear Programming Techniques for Multidimensional Analysis of Preference (LINMAP), for modeling, optimization and multi-criteria decision making respectively. This integrated approach, to best of the authors’ knowledge, has been deployed for the first time to adaptively serve different designs of manufacturing processes. Such designs have different orientations, namely cost, quality, productivity, and balanced orientation. The capability of the proposed approach to serving such diverse requirements answers one of the most accelerating demands in the manufacturing community due to the dynamics of the uprising smart production lines. Besides, the proposed approach is presented in a straightforward manner that can be extended easily to other design orientations as well as other engineering applications. ... mehr

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Verlagsausgabe §
DOI: 10.5445/IR/1000123846
Veröffentlicht am 18.09.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 2169-3536
KITopen-ID: 1000123846
HGF-Programm 43.22.03 (POF III, LK 01)
Printed Materials and Systems
Erschienen in IEEE access
Band 8
Seiten 159206–159219
Vorab online veröffentlicht am 31.08.2020
Schlagwörter Adaptive design, Artificial neural networks, Genetic Algorithm, Modeling, Wiper inserts, Turning
Nachgewiesen in Web of Science
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