W. B. Lee

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.

Design of a case based intelligent supplier relationship management system - The integration of supplier rating system and product coding system

Abstract The design of supplier relationship management to facilitate supplier selection using an integrative case based supplier selection and help desk approach to select the most appropriate suppliers together with their past performance records from a case base warehouse has become a promising solution for manufacturers to identify preferred suppliers and trading partners to form a supply network on which they depend for products, services and distribution. In this paper, an intelligent supplier relationship management system (ISRMS) integrating a companys customer relationship management system, supplier rating system and product coding system by the case based reasoning technique to select preferred suppliers during new product development process is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, it is found that the outsource cycle time from the searching of potential suppliers to the allocation of order, as well as the delay in delivery of goods of suppliers after order allocation, are greatly reduced. In addition, performance of suppliers can be monitored effectively.

An intelligent supplier management tool for benchmarking suppliers in outsource manufacturing

Abstract A global corporations supply chain usually consists of enterprises and manufacturers that are graphically dispersed around the world, whereby each company is involved in a wide variety of supply chain activities such as order fulfillment, international procurement, acquisition of information technology, manufacturing, and customer service. However, selecting suppliers based on accumulated experience is not both effective and scientific due to subjective judgment and lack of systematic analysis. Therefore, continuously tracking and benchmarking performance of suppliers and forming an appropriate supplier selection mechanism is one of the crucial activities in supply chain management. This paper presents an intelligent supplier management tool (ISMT) using the case-based reasoning (CBR) and neural network (NN) techniques to select and benchmark suppliers. The development of ISMT and how the CBR and NN techniques are used in benchmarking suppliers during the process of new product development in Honeywell Consumer Products (Hong Kong) Limited are presented.

Design of an intelligent supplier relationship management system: A hybrid case based neural network approach

Abstract In todays 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.

The processing of metal matrix composites — an overview

Abstract This overview begins by considering the mature situation for polymer matrix composites (PMCs). After a further short section devoted to ceramic matrix composites (CMCs), the main text is devoted to the variety of routes available for processing metallic matrix composites (MMCs). These are divided into those where the main steps are performed in the solid state and those where the process route involves a stage where the matrix is molten. Some discussion is also given to the thermomechanical processing of MMCs and of their properties.

Diamond turning of silicon substrates in ductile-regime

Silicons are used in both wafer fabrication and infrared optics. Direct machining of silicon single crystal was carried out on a precision lathe equipped with an air spindle to a finish of 2.86 nm rms roughness. The success of the turning process depends on optimizing the machining parameters such as feed rate, depth of cut, tool rake angles, the cutting lubricants and the crystallographic orientation of the crystal being cut. It is shown that the commercial production of an optical surface on brittle materials is made possible by single point diamond turning.

Development of a case based intelligent customer–supplier relationship management system

Abstract The integration of customer relationship management (CRM) and supplier relationship management (SRM) to facilitate supply chain management in the areas of supplier selection using a help desk approach has become a promising solution for manufacturers to identify appropriate suppliers and trading partners to form a supply network on which they depend for products, services, and distribution. In this paper, an intelligent customer–supplier relationship management system (ISRMS) using the case based reasoning (CBR) technique to select potential suppliers is discussed. By using ISRMS in Honeywell Consumer Product (Hong Kong) Limited, it is found that the outsource cycle time from the searching of potential suppliers to the allocation of order is greatly reduced.

Design of a knowledge-based logistics strategy system

Traditionally, the formulation of logistics strategies to execute various logistics services is done by human experts. In this paper, a knowledge-based logistics strategy system (KLSS) is designed in helping them to support the logistics strategy development stage by retrieving and analyzing useful knowledge and solutions in a timely and cost effective manner. The proposed knowledge-based system, which is suitable for usage in Hong Kong/Pearl River Delta region, enhances the effectiveness in formulating logistics strategies by integrating techniques like data warehouse, on-line analytical processing, multi-dimensional database management system and case-based reasoning. Through applying KLSS in Eastern Worldwide Company (EWW), resource utilization is maximized and work efficiency is greatly reduced.

Critical Elements and Lessons Learnt from the Implementation of an RFID-enabled Healthcare Management System in a Medical Organization

Healthcare services are complex and life-critical. One mistake in any procedure may lead to irremediable consequences; numerous researchers, thus, introduce information and communication technology to improve quality of services and enhance patient safety by reducing the medical errors. Radio frequency identification (RFID) is considered as one of the emerging tool assist in meeting the challenges of the present situation. In recent years, RFID has been applied in medical organizations for the purpose of managing and tracking medical equipment, monitoring and identifying patients, ensuring that the right medication is given to the right patient, and preventing the use of counterfeit medicine. However, most of the existing literature focuses on demonstrating how RFID can benefit the healthcare industry, whereas little attention has been given to the management issues involved in constructing an RFID project in medical organizations. In this paper, an exploratory case study is conducted in a medical organization to illustrate the development framework and critical issues that should be taken into consideration in the preparation, implementation and maintenance stage of constructing such a project. All the experiences and results discussed in this paper offer valuable and useful insights to steer those who would like to start their journey using RFID in medical organizations.

Multi-agent modeling of dispersed manufacturing networks

Abstract Multi-agent modeling has emerged as a promising discipline for dealing with decision-making processes in distributed information system applications. One such application is the modeling of distributed manufacturing networks which can link up various manufacturing firms to form a “virtual” manufacturing consortium on a global basis. This paper presents a multi-agent model that can be deployed in a dispersed manufacturing network involving companies with different core competence. The multi-agent model plays the important role of monitoring the information flow and task allocation among the network companies by means of intelligent agents, which are software programs designed to accomplish specific tasks like “real” human agents with specialized skills. This proposed model is equipped with various computational intelligence technologies for various purposes, including rule-based reasoning for decomposing jobs into fundamental tasks and object-oriented technology for the design and creation of the intelligent agents, together with a genetic algorithm scheme to optimize the sequence of tasks to be carried out by various agents in order to achieve minimum overhead incurred during the operations across the dispersed network. In this paper, the detailed infrastructure of a multi-agent model and how it can be deployed to enhance the performance of a dispersed manufacturing network are presented.