Felix T.S. Chan

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.

An innovative performance measurement method for supply chain management

Supply chain management has become such a popular topic in modern business management and researches. It brings the revolutionary philosophy and approach to manage the business with the sustained competitiveness. However, the existing performance measurement theory fails to provide its necessary support in strategy development, decision making, and performance improvement. This paper attempts to propose an innovative performance measurement method to contribute to the development of supply chain management. A process‐based systematic perspective is employed to build an effective model to measure the holistic performance of complex supply chains. Fuzzy set theory is introduced to address the real situation in judgment and evaluation processes. The main framework of this method is outlined with some suggestions and a simple example.

INTEGRATING ENVIRONMENTAL CRITERIA INTO THE SUPPLIER SELECTION PROCESS

Abstract In this paper, a framework for integrating environmental factors into the supplier selection process is presented. Traditionally, companies consider factors like quality, flexibility, etc. when evaluating supplier performance. However, environmental pressure is increasing, resulting in many companies (mainly large companies) beginning to consider environmental issues and the measurement of their suppliers’ environmental performance. This paper aims to develop a decision support tool which should help companies to integrate environmental criteria into their supplier selection process. Subsequently, a framework of the supplier selection process which incorporates environmental performance is developed. Finally, a knowledge-based system is constructed based on the proposed framework is presented and an example is used to illustrate how the knowledge-based system would be implemented.

Interactive selection model for supplier selection process: an analytical hierarchy process approach

Supplier Selection Process (SSP) becomes increasingly important for most manufacturing firms as it helps to reduce directly cost to the bottom line. The selection process involves the determination of quantitative and qualitative factors so as to select the best possible suppliers. It is essential to identify the relationship with the suppliers in terms of tangible factors. Owing to subjective human judgement in determining the relative importance of those selection factors, a method called Chain of Interaction is proposed to solve the problems associated with the dynamic nature of supply chain management. Focusing on the goodwill of an Analytic Hierarchy Process, an Interactive Selection Model is suggested to systemize the earlier steps, such as the determination of buyer-supplier relationships and formation of selection criteria, before the implementation of the Analytic Hierarchy Process with the help of Multi-Criterion Decision Making software called Expert Choice. The proposed Interactive Selection Model can be applied to supplier selection through the identification of buyer-supplier interactions and the valid data-collection methods. A numerical example is presented and the pros and cons of the model examined to seek further modification.

A RFID case-based logistics resource management system for managing order-picking operations in warehouses

In the supply chain, a warehouse is an essential component for linking the chain partners. It is necessary to allocate warehouse resources efficiently and effectively to enhance the productivity and reduce the operation costs of the warehouse. Therefore, warehouse management systems (WMSs) have been developed for handling warehouse resources and monitoring warehouse operations. However, it is difficult to update daily operations of inventory level, locations of forklifts and stock keeping units (SKUs) in real-time by using the bar-code-based or manual-based warehouse management systems. In this paper, RFID technology is adopted to facilitate the collection and sharing of data in a warehouse. Tests are performed for evaluating the reading performance of both the active and passive RFID apparatus. With the help of the testing results, the efficient radio frequency cover ranges of the readers are examined for formulating a radio frequency identification case-based logistics resource management system (R-LRMS). The capabilities of R-LRMS are demonstrated in GSL Limited. Three objectives are achieved: (i) a simplification of RFID adoption procedure, (ii) an improvement in the visibility of warehouse operations and (iii) an enhancement of the productivity of the warehouse. The successful case example proved the feasibility of R-LRMS in real working practice.

A conceptual model of performance measurement for supply chains

Supply chain management (SCM) has gained a tremendous amount of attention from both industries and researchers since the last decade. Until now, there are numerous papers, articles, and reports that address SCM, but there is still a lack of integration between the existing performance measurement methods and practical requirements for the SCM. An innovative performance measurement method is proposed to provide necessary assistance for performance improvement in SCM. The proposed method will address this purpose in these four aspects: a simplified supply chain model; tangible and intangible performance measures in multiple dimensions; a cross‐organizational performance measurement; and fuzzy set theory and weighted average method.

Evaluation methodologies for technology selection

Abstract This paper presents a technology selection algorithm to quantify both tangible and intangible benefits in fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations. From the analytical point of view, decision-makers are asked to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as “very high”, “high”, “medium”, “low” and “very low”, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. Since conventional engineering economic analysis involves uncertainty about future cash flows where cash flows are defined as either crisp numbers or risky probability distributions, the results of analysis may obscure. To deal quantitatively with imprecision or uncertainty, cash flows are modeled as triangular fuzzy numbers which represent “the most likely possible value”, “the most pessimistic value” and “the most optimistic value”. By using this algorithm, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision-making.

The development of intelligent decision support tools to aid the design of flexible manufacturing systems

Abstract The design of flexible manufacturing systems (FMSs) is an essential but costly process. Although FMS design appears to be an excellent area for applying artificial intelligence (AI) and computer simulation techniques, to date there have been limited investigations on integrating AI with the modular simulation software available for FMS design. In this paper an integrated approach for the automatic design of FMS is reported, which uses simulation and multi-criteria decision-making techniques. The design process consists of the construction and testing of alternative designs using simulation methods. The selection of the most suitable design (based on the multi-criteria decision-making technique, the analytic hierarchy process (AHP)) is employed to analyze the output from the FMS simulation models. Intelligent tools (such as expert systems, fuzzy systems and neural networks), are developed for supporting the FMS design process. Active X technique is used for the actual integration of the FMS automatic design process and the intelligent decision support process.

An adaptive genetic algorithm with dominated genes for distributed scheduling problems

This paper proposes an adaptive genetic algorithm for distributed scheduling problems in multi-factory and multi-product environment. Distributed production strategy enables factories to be more focused on their core product types, to achieve better quality, to reduce production cost, and to reduce management risk. However, when comparing with single-factory production, scheduling problems involved in multi-factory one are more complicated, since different jobs distributed to different factories will have different production scheduling, consequently affect the performance of the supply chain. Distributed scheduling problems deal with the assignment of jobs to suitable factories and determine their production scheduling accordingly. In this paper, a new crossover mechanism named dominated gene crossover will be introduced to enhance the performance of genetic search, and eliminate the problem of determining optimal crossover rate. A number of experiments have been carried out. For the comparison purpose, five multi-factory models have been solved by different well known optimization approaches. The results indicate that significant improvement could be obtained by the proposed algorithm.

A comprehensive survey and future trend of simulation study on FMS scheduling

Since the late 1970s when the first collection of papers on scheduling of flexible manufacturing systems (FMSs) has been published, it has been one of the most popular topics for researchers. A number of approaches have been delivered to schedule FMSs including simulation techniques and analytical methods, whereas the former is the most widely used tool for modeling FMSs. The objective of this paper is to review scheduling study on FMSs and analyse future trend that employed simulation techniques as the analyzing tool. Scheduling methodologies are categorized into, namely traditional simulation techniques with single criterion scheduling approaches, traditional simulation techniques with multi-criteria scheduling approaches, and artificial intelligence (AI) approaches in FMSs. It is concluded that AI approaches will be dominating in future study.