Abstract

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.

Author Keywords: Supplier relationship management; Supplier selection and benchmarking; Supply network; Case based reasoning; Artificial neural network

Article Outline

1. Introduction

2. Customer relationship management and supplier relationship management (CRM/SRM)

3. Case based reasoning and artificial neural network

3.1. Process and applications of CBR

3.2. Process and applications of ANNs

4. An intelligent supplier relationship management system

4.1. Supplier selection module (CSSM)

4.2. Supplier benchmarking module (NNSBM)

4.3. Construction of the key components of ISRMS

4.3.1. Case based supplier selection module

4.3.2. Neural network based supplier benchmarking module (NNSBM)

4.3.2.1. Stage 1: design stage

4.3.2.2. Stage 2: training stage

4.3.2.3. Stage 3: generalization stage

5. Application case study and results

6. Conclusions

Acknowledgements

References

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