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Title: Fuzzy logic in production sequencing: the case of a cosmetics manufacturer in Brazil

Authors: Mario Mannarino Filho; Peter F. Wanke; Henrique L. Correa

Addresses: Federal University of Rio de Janeiro, Cidade Universitária, Rua Paschoal Lemme, 355, Ilha do Fundão, Rio de Janeiro, RJ, CEP: 21.949-900, Brazil ' Federal University of Rio de Janeiro, Center for Studies in Logistics, Infrastructure and Management, Cidade Universitária, Rua Paschoal Lemme, 355, Ilha do Fundão, Rio de Janeiro, RJ, CEP: 21.949-900, Brazil ' Rollins College, Crummer Graduate School of Business, Winter Park, Florida, USA

Abstract: This study aims to develop a way to improve the production sequencing practice of a case company that manufactures cosmetics located in Brazil. Production sequencing is an activity that is part of production planning and control. Our goal is to provide ways to reduce sales loss due to product stock-outs through new practices found in the literature. Simultaneously, we aimed at increasing the number of different items without sales loss thereby helping the achievement of sales goals while improving the meeting of overall demand for products. The approach proposed here includes the development of a decision support tool based on fuzzy logic. Such approach proved to be a good alternative to overcome some of the problems encountered in the case company production sequencing activity. Furthermore, the developed decision support system enabled the organisation decision-making to be more agile and dynamic. Additionally, by facilitating the incorporation of environmental complexity, our proposed solution helped harmonise decision-making across different areas of the company.

Keywords: fuzzy logic; inventory management; production sequencing; systems engineering; cosmetics manufacturing; Brazil; case study; sales loss; product stock-outs; decision support systems; DSS; complexity.

DOI: 10.1504/IJBISE.2016.081589

International Journal of Business Intelligence and Systems Engineering, 2016 Vol.1 No.1, pp.2 - 31

Available online: 16 Jan 2017 *

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