Multiobjective optimization of torch brazing process by a hybrid of fuzzy logic and multiobjective artificial bee colony algorithm

Alejandro Alvarado-Iniesta (), Jorge L. García-Alcaraz, Manuel Piña-Monarrez and Luis Pérez-Domínguez ()
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Alejandro Alvarado-Iniesta: Autonomous University of Ciudad Juarez
Jorge L. García-Alcaraz: Autonomous University of Ciudad Juarez
Manuel Piña-Monarrez: Autonomous University of Ciudad Juarez

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 3, No 10, 638 pages

Abstract: Abstract This paper describes an application of a hybrid of fuzzy logic (FL) and multiobjective artificial bee colony algorithm (MOABC) for optimizing the torch brazing process of aluminum in the fabrication of condensers in the automotive manufacturing industry of Juarez, Mexico. This work aims to show how artificial intelligence is being applied in the manufacturing sector of Mexico for optimizing processes leading to cost reduction. The approach consists of using FL as surrogate model of the brazing process; after, MOABC is applied to find the nondominated solutions for leak rate which is a quality test of the condenser and production time. Results show the use of artificial intelligence is an excellent tool for optimizing manufacturing processes leading to improve productivity, mainly in the selected region, where this type of methodologies are fairly new in applicability.

Keywords: Process optimization; Fuzzy logic; Multiobjective; Artificial bee colony algorithm; Torch brazing; Mexican industry (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10845-014-0899-2

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