دانلود مقاله ISI انگلیسی شماره 21289
ترجمه فارسی عنوان مقاله

سیستم پشتیبانی تصمیم گیری مبتنی بر منطق فازی برای ارزیابی تامین کنندگان در شیوه های مدیریت زنجیره تامین

عنوان انگلیسی
A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
21289 2013 17 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Mathematical and Computer Modelling, Volume 58, Issues 11–12, December 2013, Pages 1679–1695

ترجمه کلمات کلیدی
ارزیابی تامین کننده - کیفیت - هزینه - زمان - فازی
کلمات کلیدی انگلیسی
Supplier evaluation, Quality, Cost, Time, Fuzzy,
پیش نمایش مقاله
پیش نمایش مقاله  سیستم پشتیبانی تصمیم گیری مبتنی بر منطق فازی برای ارزیابی تامین کنندگان در شیوه های مدیریت زنجیره تامین

چکیده انگلیسی

Supply chain management is an increasingly important organizational concern, and proper evaluation of suppliers constitutes one essential element of supply chain success. Continuous evaluation of a particular supplier becomes more important considering the fact that in most industries the cost of raw materials and component parts constitutes the main cost of a product, such that in some cases it can account for up to 70%. However, there is little research that has helped the organizations in continuous evaluation of their suppliers. We propose a new model, based on fuzzy logic to handle the various attributes, associated with supplier evaluation problems. Four multi-input single output (MISO) mamdani fuzzy inference systems have been proposed for supplier evaluation. The proposed model has also been illustrated through a case study.

مقدمه انگلیسی

Since the introduction of the term supply chain management (SCM) by consultants in the early 1980s, it has gained the attention of researchers and academicians. After the 1990s, academics have attempted to find more and more aspects about SCM [1] and [2]. With these attempts of academicians and researchers, the concept arose from a number of changes in the different stages of the supply chain. These changes effected the rising costs of manufacturing, the shrinking resources of manufacturing bases apart from shortening product life cycles. As a result, the concept has undergone tremendous changes over a few years. It has entirely replaced the traditional terms used to describe the management of material and service flows [3]. The intensive global competition among manufacturers to co-ordinate with and respond quickly the industry value chain from suppliers to customers has made the customer–supplier relationship in SCM important in the new business era. In such circumstances, decision making in each business plays a key role in the cost reduction, and supplier evaluation is one of the important functions in supplier relationship management because doing business with appropriate suppliers is beneficial for the organization to provide a sufficient production volume with good quality [4]. This function becomes more important considering the fact that in most industries the cost of raw materials and component parts constitutes the main cost of a product, such that in some cases it can account for up to 70%. In such circumstances the purchasing department can play a key role in cost reduction, and supplier selection and continuous evaluation of the supplier becomes some of the important functions of purchasing management [5]. The increasing proportion of raw materials and work-in-process of manufactured products, where sourced globally by multinational manufacturers, is a trend in today’s industries. The way to evaluate supplier capability is the main scope of supplier selection. A multi-national manufacturer cannot have direct control over the capability and performance of its hundreds or even thousands of suppliers. However, the evaluation of its suppliers’ capabilities to provide raw materials/component parts is a crucial issue to a multi-national manufacturer. For example, it is common for suppliers, after receiving an order to sub-contract to satisfy the demand, due to the tightness of their own production schedule. Furthermore, internal re-scheduling of production by the supplier may have an impact on their performance level. Their quality assurance and on-time delivery would be in doubt. Therefore, a manufacturer should analyze and evaluate the potential threats when continuing business with suitable supplier(s) resulting from a systematic evaluation process and its corresponding attributes [6]. After selection of an appropriate supplier, therefore, continuous evaluation of supplier(s) is very essential. In [7], Kumar et al. study the single decision supplier selection process in the Indian textile industry, whereas the current paper studies the continuous process of supplier evaluation.

نتیجه گیری انگلیسی

In this paper, an effort has been made to develop a model for supplier evaluation through data collection from survey of 66 Indian textile organizations. A questionnaire has been used to determine the factors, which these organizations consider while evaluating a particular supplier. A multi-input single output (MISO) mamdani fuzzy inference system has been proposed for supplier evaluation taking the most important nine factors, opined by the respondents. As the literature reveals, no logical method is being employed at present to continuously evaluate a supplier in the industry under study. Considering the extent of production cost involved in raw material, the proposed system can be very helpful to the companies for making decisions about supplier evaluation. Apart from supplier evaluation, the proposed methodology can be translated to model the decision making processes of facilities and service purchases by just changing the variables. As illustrated in the above sections, the proposed system is very simple for the engineers/managers of the related fields to use and they will find the implementation of this technique very easy and suitable. Like any other system, the fuzzy logic scheme has its own drawbacks. While developing fuzzy rules for the system, it requires experience from field experts, experimental results and theoretical derivation to make the system effective [39]. Even in some cases, experts may need to be put on site to be sure about the characteristics that may effect the whole system and to adjust the fuzzy rules at the beginning of the stage. This exercise may sometimes increase the cost of system development. Fuzzy reasoning also sacrifices some explanation for accuracy, reliability, and compactness, and lack of the concept of justification for fact as in a rule based system [40]. Model development through usage of a particular sample population can be another limitation of this research work. We feel that a mixed population of respondents from multiple sources can increase the scope of generalizability of the model and we propose the inclusion of this aspect in future research. Though the system has some limitations as listed above, the potential benefits of the implementation of the proposed system in Indian textile organizations are not in doubt. An effective mechanism for the art of designing the right system using the proposed approach is debatable. Therefore, issues related to these concerns are worthy of future research. This study is a modest contribution toward that end.