Bi-Objective Multiple Criteria Data Envelopment Analysis combined with the Overall Equipment Effectiveness: An application in an automotive company. (20th July 2017)

• Record Type: Journal Article
• Authors: da Silva, Aneirson Francisco; Marins, Fernando Augusto Silva; Tamura, Patricia Miyuki; Dias, Erica Ximenes
• Is Part Of: Journal of cleaner production. Volume 157(2017)
• Page Start: 278
• Page End: 288
• Publication Date: 2017-07-20
• Subjects: Overall machinery effectiveness -- Data envelopment analysis -- Multiple criteria data envelopment analysis -- BiO-MCDEA models -- Overall equipment effectiveness; TPM Total Productive Maintenance -- OEE Overall Equipment Effectiveness -- DEA Data Envelopment Analysis -- DMUs Decision Making Units -- DEA-CCR DEA model proposed by Charnes, Cooper and Rhodes -- DEA-BCC DEA model proposed by Banker, Charnes, and Cooper -- MCDEA Multiple Criteria DEA -- BiO-MCDEA Bi-Objective MCDEA -- OME Overall Machinery Effectiveness -- SMED Single-Minute Exchange of Die -- WF Workforce -- MSA Measurement Systems Analysis -- VBA Visual Basic for Application; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2017.04.147
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: The mass production companies need to seek high efficiency in the use of equipment and human resources, as well as in the consumption of their inputs. One of the key methods to address these challenges is the adoption of Overall Equipment Effectiveness, derived from Total Productive Maintenance. This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness, to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness indicator. The studied company made available production data from ten months, associated to two Press machines, generating twenty Decision Making Units for Data Envelopment Analysis and Bi-Objective Multiple Criteria Data Envelopment Analysis models application. As results, Press #2 was identified as being the most critical because, among the first ten DMUs in the efficiency ranking, seven are associated to Press #1. The targets values recommended by the new indicator were considered feasible to be implemented by the company, thus validating in practice the new proposed procedure for the management of machines effectiveness. Moreover, the identification of the relevant variables (input and output) for the Press #1, and Press #2, allowed the decision maker to act in the best way to increase their efficiency. Graphical abstract: This work aims to propose a new efficiency indicator, called Overall Machinery Effectiveness (OME), to be applied in an automotive company in Brazil that adopted Overall Equipment Effectiveness (OEE) indicator. Highlights: New indicator for measuring machine efficiency is proposed for an automotive company. The new indicator complements Overall Equipment Effectiveness. The new indicator finds out the most critical machines. The new indicator estimate targets for improving their machinery effectiveness.