مقاله انگلیسی رایگان در مورد مروری بر تصمیم گیری چند معیاره برای بهره وری از انرژی – الزویر 2018

 

مشخصات مقاله
ترجمه عنوان مقاله مروری بر تصمیم گیری چند معیاره برای بهره وری از انرژی در مهندسی خودرو
عنوان انگلیسی مقاله A review on multi-criteria decision-making for energy efficiency in automotive engineering
انتشار مقاله سال 2018
تعداد صفحات مقاله انگلیسی 13 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
پایگاه داده نشریه الزویر
نوع نگارش مقاله
مقاله مروری (Review article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) scopus – DOAJ
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
رشته های مرتبط  مهندسی صنایع، مکانیک
گرایش های مرتبط  لجستیک و زنجیره تامین
نوع ارائه مقاله
ژورنال
مجله  محاسبات و انفورماتیک کاربردی – Applied Computing and Informatics
دانشگاه  Fiat Chrysler Automobiles (FCA) – Distrito Industrial Paulo Camilo Sul – Betim – Brazil
کلمات کلیدی  تجزیه و تحلیل معیارهای چندگانه، مدیریت تصمیم چند معیاره، بهره وری انرژی
کلمات کلیدی انگلیسی Multiple criteria analysisMulti-criteria decision managementEnergy efficiency
شناسه دیجیتال – doi
https://doi.org/10.1016/j.aci.2018.04.004
کد محصول  E10521
وضعیت ترجمه مقاله  ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید.
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فهرست مطالب مقاله:
abstract

1- Introduction

2- Background

3- Related work

4- Research design

5- Results

6- Discussion

7- Conclusion

References

بخشی از متن مقاله:

abstract

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.

Introduction

Decision process can be defined as a set of actions and methods dynamically organized. This process is triggered by demand for action and it ends with a specific engagement execution [1]. Corporations have to choose the best option by aggregating outcomes of different stakeholders [2]. Although the decision-making problem could be constructed as more than one hierarchy with different criteria [3] to be solved, this process is still hard due to the following:  They are non-repetitive, unprecedented and unique [2].  Criteria may conflict itself, for example, customers want quality but they also want something not expensive. Conflicting criteria make the decision task tough [4,5].  Criteria such as fuel consumption can be objectively measured, commonly named as tangible criteria. Flexibility, quality, efficiency or future income, cannot. This group is classified as intangible criteria. Intangible criteria cannot be converted into numeric or monetary values [6,7]. As proposed by law [8], energy efficiency (EE) should not be calculated by models only, but by the whole universe of new vehicles registered. In this scenario, the composition of vehicles sold in the market will have influence on profits of each automaker, since additional taxes are going to be applied for those automakers that do not achieve a specified target. Among all variables to be considered, one can highlight that analysis of manufacturing costs, customer value perception and market share, can be characterized as a multi-criteria decision-making problem. Due to the increasing competition, dynamic customer demands and regulatory laws, the scenario requires automakers to add energy efficiency items to practically the entire portfolio.

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