K.L. Choy

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.

Design of a RFID-based resource management system for warehouse operation

In the past, the selection of resource to execute various warehouse operation services was done by solely human experts. In this paper, a RFlD-based resource management system (RFID-RMS) is designed in helping users to select the most suitable resource usage package for handling warehouse operation order by retrieving and analyzing useful knowledge from a case based data warehouse for solutions in both time saving and cost effective manner. The proposed system, which is suitable for usage in warehouse operating environment, enhances the effectiveness in formulating resource usage package by integrating the case-based reasoning techniques and automatic data collection technique, namely, radio frequency identification (RFID) through applying RFID-RMS in GENCO distribution system, one of the largest international distributions and logistics based company. The utilization of warehouse resource is maximized while work efficiency is greatly enhanced.

Managing uncertainty in logistics service supply chain

Many third party logistics (3PL) providers in South China are small and medium-sized companies and lack of systematic mean on handling information. Uncertainties are created in the business processes due to insufficient information for decision-making. In this study, a logistics information system called Integrated Logistics Information Management System (ILIMS) is proposed. It aims to manage the information flow efficiently between the involved parties in the logistics supply chain through integrating business processes and increasing information transparency to reduce uncertainty. In addition, it provides an effective channel for the 3PL providers to communicate with different contracted suppliers as well as customers through wireless Internet applications. A case study of applying ILIMS in a local 3PL company is discussed. By using this generic system, supply chain uncertainty that associates with the logistics processes can be reduced and leads to a significant performance improvement in the overall order fulfilment process.

A novel fuzzy group decision-making approach to prioritising engineering characteristics in QFD under uncertainties

In new product development, design teams commonly need to define engineering characteristics (ECs) in a quality function deployment (QFD) planning process. Prioritising the engineering characteristics in QFD is essential to properly plan resource allocation. However, the inherent vagueness or impreciseness in QFD presents a special challenge to the effective calculation of the importance of ECs. Generally, there are two types of uncertain input in the QFD process: human perception and customer heterogeneity. Many contributions have been made on methods to prioritise ECs. However, most previous studies only address one of the two types of uncertainties that could affect the robustness of prioritising ECs. To address the two types of uncertainties simultaneously, a novel fuzzy group decision-making method that integrates a fuzzy weighted average method with a consensus ordinal ranking technique is proposed. An example is presented to illustrate the effectiveness of the proposed approach. Results of the implementation indicate that the robustness of prioritising ECs based on the proposed approach is better than that based on the method of Chen et al. (Chen, Y., Fung, R.Y.K., Tang, J.F., 2006. Rating technical attributes in fuzzy QFD by integrating fuzzy weighted average method and fuzzy expected value operator. European Journal of Operational Research, 174 (3), 1553–1556).

Development of performance measurement system in managing supplier relationship for maintenance logistics providers

Purpose – To develop a performance measurement system (PMS) in the application of supplier relationship management operated under a supply chain benchmarking framework. Acting as a monitoring tool for evaluating the performance of maintenance logistics providers against the defined performance levels stated in the contract, and facilitating the application of benchmarking approach in maintenance logistics activities.Design/methodology/approach – A six tiers collaborative management model is designed in building the PMS, by which information sharing of performance history of suppliers is made possible. By following the work flow of the PMS, performance of suppliers is benchmarked with the best‐in‐class supplier, resulting in the identification of the most appropriate supplier for the particular requirement.Findings – PMS helps a company and its suppliers to understand the performance gap between its service levels with the best‐in‐class practice. The resulting performance gap provides valuable information ...

A performance benchmarking system to support supplier selection

In todays competitive business environment, management of suppliers is essential for companies to monitor the value chain of the entire production network. Evidence suggests that undesirable occurrences in companies, such as extensive delays in the planned schedule, serious quality problems and cost overruns, are, to a certain extent, related to the unfulfilled promises of business partners. Subjective judgment and the lack of a systematic method for supplier selection hinder the analysis of the current and projected performance of the suppliers, which is necessary before making a final decision. This paper attempts to propose a generic model for supplier selection, focusing on the methodology to benchmark the potential suppliers and providing a comparison of performance measures based on a number of relevant criteria. To validate the feasibility of the proposed system, this paper makes use of existing AI tools that have been developed for selecting and benchmarking suppliers for manufacturing firms.

An enterprise collaborative management system: a case study of supplier selection in new product development

Businesses that remain competitive must not only look into their internal operations, but also communicate and work concurrently with all players in their supply chain network. In this paper, the supplier relationship management module of a server-based enterprise collaborative management system (ECMS) using enterprise application integration (EAI) technology for trial implementation at Honeywell Consumer Products (Hong Kong) Limited, is discussed. A case study using ECMSs supplier relationship management system (ISRMS) to integrate Honeywells supplier rating system (SRS) and product coding system (PCS) via the case-based reasoning (CBR) technique, to select preferred suppliers during the new product development (NPD) process, is also reported here. It is found that the outsource cycle time, from the searching of potential suppliers to the allocation of orders, is greatly reduced. Through the ISRMS of ECMS, manufacturers identify preferred suppliers to form a supply network on which they depend for products, services and distribution effectively.

Decision-making approach for the distribution centre location problem in a supply chain network using the fuzzy-based hierarchical concept

Abstract In the era of global business and competitiveness, supply chain management has emerged as the critical factor for the success of companies. The past few decades have witnessed the importance of the linking channels among suppliers, manufacturers, and customers. The distribution centre (DC) location problem is a very fundamental and basic decision-making problem in terms of an efficient and effective supply chain. The decision concerning DC location, bearing in mind the current and future business perspective, is a cumbersome task and involves a large amount of investment. The selection of a site is a multicriterion decision-making problem and requires a thorough analysis of both qualitative and quantitative factors. The comparative study of different potential sites on a common set of criteria can help to handle the problem systematically and effectively. In general, most of the decision-making approaches such as the analytical hierarchy process (AHP) seem inefficient in handling the imprecise and vague linguistic comparisons of the different criteria. In this paper, a fuzzy integrated hierarchical decision-making approach is developed to solve the DC location selection problem. A case study adopted from previous literature is also discussed in this paper to show the effectiveness and robustness of the proposed methodology over the existing conventional hierarchical approaches.

A real-time risk control and monitoring system for incident handling in wine storage

Due to the fact that wine is highly sensitive to storage conditions such as temperature and humidity, it is a challenging task for a regional distribution hub to provide reliable wine storage facilities for maintaining wine quality during storage. This is especially true when an incident occurs unexpectedly that violates the criteria of suitable storage conditions. Improper incident handling and storage conditions may cause damage to the taste of wine, resulting in depreciation of the wines value. Therefore, controlling and monitoring risk in real-time during wine storage is critical to providing a quick response to prevent the wine quality from deterioration. In this paper, a RFID-based risk control and monitoring system (RCMS), which integrates radio frequency identification (RFID) technology and case-based reasoning (CBR), is proposed for monitoring real-time physical storage conditions and for formulating an immediate action plan for handling incidents. In the retrieval process of the CBR engine, genetic algorithms (GA) are applied to search for case clusters by considering the best combination of multi-dimensional parameters. With the help of RCMS, a shortlist of critical control actions, possible causes of incidents and corresponding actions can be generated to reduce the risk of deteriorating wine quality and possible compensation costs being incurred, while customer satisfaction can be maintained.

A RFID-based recursive process mining system for quality assurance in the garment industry

With the increasing concern about product quality, attention has shifted to the monitoring of production processes to be assured of good quality. Achieving good quality is a challenging task in the garment industry due to the great complexity of garment products. This paper presents an intelligent system, using fuzzy association rule mining with a recursive process mining algorithm, to find the relationships between production process parameters and product quality. The goal is to derive a set of decision rules for fuzzy logic that will determine the quantitative values of the process parameters. Learnt process parameters used in production form new inputs of the initial step of the mining algorithm so that new sets of rules can be obtained recursively. Radio frequency identification technology is deployed to increase the efficiency of the system. With the recursive characteristics of the system, process parameters can be continually refined for the purpose of achieving quality assurance. A case study is described in which the system is applied in a garment manufacturing company. After a six-month pilot run of the system, the numbers of critical defects, major defects and minor defects were reduced by 7, 20 and 24%, respectively while production time and rework cost improved by 26 and 30%, respectively. Results demonstrate the practical viability of the system to provide decision support for garment manufacturers who may not be able to determine the appropriate process settings for achieving the desired product quality.