دانلود مقاله ISI انگلیسی شماره 19107
ترجمه فارسی عنوان مقاله

طراحی یک تامین کننده سیستم مدیریت ارتباط هوشمند: روش شبکه های عصبی مبتنی بر مورد هیبریدی

عنوان انگلیسی
Design of an intelligent supplier relationship management system: a hybrid case based neural network approach
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
19107 2003 13 صفحه PDF
منبع

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

Journal : Expert Systems with Applications, Volume 24, Issue 2, February 2003, Pages 225–237

ترجمه کلمات کلیدی
مدیریت ارتباط با تامین کننده - انتخاب تامین کننده و تعیین معیار - شبکه تامین - استدلال موردی - شبکه های عصبی مصنوعی
کلمات کلیدی انگلیسی
Supplier relationship management, Supplier selection and benchmarking, Supply network, Case based reasoning, Artificial neural network,
پیش نمایش مقاله
پیش نمایش مقاله  طراحی یک تامین کننده سیستم مدیریت ارتباط هوشمند: روش شبکه های عصبی مبتنی بر مورد هیبریدی

چکیده انگلیسی

In today's accelerating world economy, the drive to continually cut costs and focus on core competencies has driven many to outsource some or all of their production. In this environment, improving supply chain execution and leveraging the supply base through effective supplier relationship management (SRM) has become more critical than ever in achieving competitive advantage. It was found that the use of artificial intelligence in the outsourcing function of SRM to identify appropriate suppliers to form a supply network has become a promising solution on which manufacturers depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) using hybrid case based reasoning (CBR) and artificial neural networks (ANNs) techniques to select and benchmark potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, the outsource cycle time from searching for potential suppliers to the allocation of order is greatly reduced.

مقدمه انگلیسی

The integration of customer/supplier relationship management (CRM/SRM) to facilitate supply chain management in the areas of supplier selection using an artificial neural network (ANN) approach to validate the search result using CBR technology during the retrieval stage of the cycle in a real time base is a promising solution for manufacturers to identify appropriate suppliers and trading partners to form a supply network on which they depend for products, components, services and distribution. The result is the formation of an integrated supply network that allows the most appropriate suppliers of the manufacturers to deliver competitively priced, high quality products and services to their final customers according to their demand effectively. Choy, Lee, and Lo (2002a) designed a case based SRM system using a help desk approach and it was then applied in the purchasing department of an outsource-type manufacturer in Hong Kong, which has greatly improved the efficiency in the outsource cycle. Choy, Lee, and Lo (2002b) also suggested and illustrated the technique of using case based reasoning (CBR) and ANN technologies in selecting and benchmarking potential suppliers during the process of new product development for manufacturers who outsource a significant part of their business. In this paper, an intelligent supplier relationship management system (ISRMS) using a hybrid CBR technique to select potential suppliers from a supplier list, followed by the benchmarking of the potential suppliers using ANN technique under a CRM/SRM platform, is discussed. By using ISRMS, manufacturers can shortlist and benchmark appropriate suppliers according to the position the supplier is ranked, resulting in the identification of preferred suppliers with references to the suitability of the supplier attributes selected. As a result, the outsourcing cycle time from searching potential suppliers to the allocation of orders to the most appropriate supplier can be greatly reduced with high accuracy. This paper is divided into seven sections. Section 2 introduces customer relationship management (CRM) and SRM. Section 3 is about CBR and ANNs and their suitability in SRM. Section 4 is the development of ISRMS using a CBR system incorporating major tasks in SRM to form a distinct intelligent supplier evaluation system with the aid of the neural network (NN) shell, which is important for manufacturers wishing to outsource operations to reliable, suitable suppliers and business partners. The procedures for constructing the CBR based supplier selection module and NN based supplier benchmarking module, which are the critical issue for the success of ISRMS, are also detailed in this section. Section 5 is about the application case study, results and benefits by using ISRMS as an intelligent supplier relationship management system in the purchasing department of Honeywell Consumer Product (Hong Kong) Limited, to aid the conventional human reasoning process of suppliers selection. Finally a conclusion of the application of ISRMS in general is made in Section 6.

نتیجه گیری انگلیسی

SRM involves the management of preferred suppliers and finding new ones whilst reducing costs, making procurement predictable and repeatable, pooling buyer experience and extracting the benefits of supplier partnerships, while CRM focused on leveraging and exploiting the interaction with the customer to maximize customer satisfaction, ensure return business, and ultimately enhance customer profitability. It becomes crucial for manufacturers to integrate the demand of customers to their preferred suppliers as well as sourcing new ones in a real time base during the new product development cycle in order to remain competitive in business. The major function of ISRMS is to integrate the customer requirements on product quality, delivery time, and manufacturing cost by two advanced computational retrieval technology called CBR and NNs, to evaluate and benchmark suppliers through a single software platform. With the implementation of ISRMS, an organization can shorten the workflow of selecting and benchmarking business suppliers on receiving a new order. In addition, the potential suppliers retrieved from CSSM are categorized into a different category by NNSBM. In doing so, orders can be assigned to the most competent suppliers appropriately. The workflow of the new system minimizes the human involvement in routine task in the system, and speeds up and enhances the consistency of the decision making process. An ISRMS solution can help manufacturers to reduce the total production time and time to market through the effective outsourcing its works to the most appropriate suppliers. The computerization of the customer–supplier management process helps the enterprise to fully implement a CRM strategy in each department, to achieve a close relationship with suppliers/partners by the integration with the SRM strategy, and consequently increase the manufacturers' own competitiveness, reputation and revenue in the market. By using ISRMS, it is possible for a manufacturer to build long term and profitable relationships with chosen customers, and to maximize the value of its supply base by increasing flexibility and responsiveness to customer requirements and substantially faster cycle times.