- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered. This paper compiles Multi-criteria decision-making (MCDM) studies related to automotive industry. We applied a Systematic Literature Review on MCDM studies published until 2015 to identify patterns on MCDM applications to design vehicles more fuel efficient in order to achieve full compliance with energy efficiency guidelines (e.g., InovarAuto). From 339 papers, 45 papers have been identified as describing some MCDM technique and correlation to automotive industry. We classified the most common MCDM technique and application in the automotive industry. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainties in the data was also observed. Despite the maturity in the use of MCDM in several areas of knowledge, and intensive use in the automotive industry, none of them are directly linked to car design for energy efficiency. Analytic Hierarchy Process was identified as the common technique applied in the automotive industry.
This paper carried out a unique literature review to classify MCDM techniques with focus on automotive industries. The review categorized 45 scholarly papers from 33 journals until October 2015 into 5 application areas. We classified them by publication year, publication journal, country of application. We found that MCDM techniques have been successfully applied to a wide range of applications in automotive industry. The methods in engineering design are the most frequent, followed by environment and supply chain. We observed that AHP was the most consistent technique followed by PROMETHEE. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainty was also observed [127,24,85,38,14,132,27,90,74]. There is a gap on the use of MCDM for automotive design focused in EE, although a review of the published literature on automotive industry analyzed here indicates greater applicability of MCDM methods for dealing with complex decision-making in automotive sectors with different subjects and terms. None of them focused on EE from automakers point of view. Although there are papers for fleet selection [5,133,74] and fuel selection [134,135,17,129,136] none of them focused on supporting a rational decision on which features should be adopted on each vehicle in order to enhance EE. The methods have been widely used to handle multiple, conflicting criteria even though increasing popularity and applicability of these methods beyond 2010 indicate a paradigm shift in MCDM approaches. It is clear that application of MCDM on automotive design for EE is an option and should be object of future researches.