Intelligent Laboratory Resource Supply Chain Conceptual Network Model with Process and Information Integration, Visibility and Flexibility

Abstract

Abstract. This paper proposes a web-based laboratory resource supply chain conceptual model for an educational institution to increase the process and information integration, visibility and flexibility. The proposed model utilizes a reasoning engine with fuzzy, parallel fuzzy rules, and de-fuzzy processes to decide the optimal purchase ordering quantity and the best constant stocks in the laboratory. The fuzzy takes the crisp input data through the characteristic function and maps the input data into its corresponding membership degree. The fuzzy rules are processed with different degree of membership and all rules in the system are processed before triggering an action. The de-fuzzy takes each item's purchase ordering degree of membership through the singleton output membership function and generates corresponding crisp data. The model allows users keying in their required experimental materials via the Web Site, uses the database management system to integrate all related information, and applies the fuzzy reasoning engine to generate the final purchase order reports to support the executor making the optimal decisions.