انتخاب تامین کننده و تخصیص میزان تامین نقاط مشترک و غیرمشترک با معیارهای چندگانه تحت محصولات مختلف
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|19151||2008||24 صفحه PDF||سفارش دهید||12476 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Computers & Industrial Engineering, Volume 55, Issue 1, August 2008, Pages 110–133
With limited capacity of suppliers, how to reduce the total operating cost of the enterprise by determining the most suitable production capacity allocation has become the major issue faced by various enterprises in producing multiple types of products. In addition, when manufacturing multiple types of products, due to the high demand of common and non-common parts, which is applicable to various products, enterprises will place special emphasis on the procurement of common and non-common parts, to select most suitable suppliers of parts with the highest quality and minimum time and costs, in order to cut down on operating costs of enterprises. This research first lists parts of various products through bill of material (BOM), and constructs an optimal mathematical model suitable for multi-phase products’ parts, in order to assess the assembling relationship of various parts; it makes use of the linkage among those to select the supplier of common and non-common parts when assessing multiple products. Then considering the limited production capacity of suppliers, it selects the best combination of suppliers of special common and non-common parts. To solve the optimal mathematical model, a genetic algorithm (GA) is proposed to find the acceptable results of the supply selection and quantity allocation problem. It then provides a benchmark for enterprise in current diversified market to purchase and assess common and non-common parts, and makes such benchmark a normal standard for selection of suppliers in the future.
With the change of the market, current enterprises constantly focus on industries. For obtaining opportunities of continuous operation in the meager profit environment, enterprises all solve the operation-related issues with complex structure or non-linear combination in industries and markets through information equipments. In addition, while resource is limited, how can enterprises come up with most efficient and productive resource allocation with optimal method, is the key issue discussed in this research. To meet the different needs of each customer, enterprises have become customer-oriented to produce varieties of products. Moreover, under current competitive environment, if enterprises want to remain in operation continuously and acquire long-term profit, fighting alone is not a good idea. Supplier selection management has to be put in good use to integrate suppliers and enterprise and make the supply-demand become best and maintain a long-term cooperative relationship. Especially for enterprises of multiple products, types of orders are becoming complicated, taking the most popular PDA, for example, with the appearance of nano-tech, many PDA products are being updated. Wang and Che (2004) suggested that currently many companies endeavor to change and improve current products; and in order to maintain or increase the occupancy of mature products, enhancement of quality and reduction of cost are two major tasks. We thought that once products are updated, their common and non-common parts should also be appraised, as shown in Fig. 1 and then the selection of parts and parts suppliers becomes an even more complicated process. Each product is normally composed of many parts, when the number of parts becomes plentiful, there may be more suppliers to choose from, thus increasing the chance of selecting better parts suppliers and even diverting the risks of enterprises. Full-size image (32 K) Fig. 1. Schema of multi-product with common and non-common parts. Figure options How to determine parts supply quota among different supplier groups with limited supply capacity, under the conduction of multiple products and parts and based on different selection criteria, is becoming important for enterprises. Especially in the environment that sees numerous changes taking place concurrently, there are still many factors interlinked. How to assist enterprise in determining the selection of particular part and suppliers to acquire maximum profit, under the condition of rapidly changing market and multiple products, will be an important topic at present time. Heuristic algorithm that features fast calculation function becomes the tool for our assessment. Among various algorithms, GA, as thought by Wang, Yung, and Ip (2001), is most suitable for selecting best supplier combination. And Hokey, Gengui, Mitsuo, and Zhenyu (2005) suggested that GA is the best population-based heuristic algorithm, capable of generating a group of best solutions at once. Therefore, considering the variety of current products, both the selection of suppliers and operation and production of suppliers themselves should be taken into account, so algorithm featuring fast calculation should be employed to solve such problems. In this research, we plan to introduce case studies based on GA to deal with the selection suppliers of common parts and non-common parts of multiple products, allocation of supply, thus cutting off the unnecessary costs of enterprises. Vonderembse and Tracey (1999) mentioned in their research that to face the huge change in the market, enterprise should explore wider supply system, clearly define criteria for selecting and assessing suppliers, in order to improve production performance of the enterprise. Their research results also showed that selection criteria of suppliers and two interfaces adopted by suppliers can all influence performance, and the application of supplier selection criteria is practically very extensive already. Therefore, when developing relationships with suppliers, the importance of supplier selection should not be ignored. To understand the traits of each industry and improve the performance of enterprise by making use of suitable supplier selection criteria, each industry possesses its unique assessment factors and criteria for selecting suppliers in each industry focusing on unique features, which should be discussed separately. In this paper, we developed a set of assessment mode suitable for current multiple products that is different from assessment mechanism for single part supplier in the traditional parts’ change. The purpose of this research is to discuss the assessment mechanism for common and non-common parts’ suppliers on the premise of same parts and suppliers in enterprises possessing multiple product projects, which can serve as reference for supplier selection and quantity allocation made by industries and for industries to come up with correct product strategies during production. This research hopes that a purchase mode conducive to enterprise be sought out through quota allocation to suppliers of different materials under the condition of multiple products, and under the conditions of different purchase cost, transportation cost, assembling cost, assembling time, purchase time, quality of different parts provided by and limited production capacities of various suppliers.
نتیجه گیری انگلیسی
This study emphasizes supplier selection and supply quantity allocation problems to find the fundamental purchasing configuration that will best minimize the T-score total utility function of total products, including cost, time and quality of fulfilling the demands. In this paper, a proposed approach is presented for a purchasing strategy, which is based on the GA and multi-criterion. Using this proposed approach, a modeling procedure is suggested to analyze the product part configure and to establish the supplier assessing and quantity allocating model. With the proposed model, different suppliers for all parts of PDA can be evaluated simultaneously and a quantity allocation plan of common and non-common parts can be created in the purchasing procedure. For evaluating the quality of the results that can be obtained by the GA, we provide the comparison between results of the GA and the commercial Lingo software package. The compared result shows that the proposed model is reliable and robust. In brief, the model can provide a quality solution and is to be applied to a real world application readily.