C. K. M. Lee

Development of RFID-based Reverse Logistics System

Reverse logistics, which is the management or return flow due to product recovery, goods return, or overstock, form a closed-loop supply chain. The success of the closed-loop supply chain depends on actions of both manufacturers and customers. Now, manufacturers require producing products which are easy for disassembly, reuse and remanufacturing owing to the law of environmental protection. On the other hand, the number of customers supporting environmental protection by delivering their used products to collection points is increasing. According to the findings, the total cost spent in reverse logistics is huge. In order to minimize the total reverse logistics cost and high utilization rate of collection points, selecting appropriate locations for collection points is critical in reverse logistics. This paper proposes a genetic algorithm to determine such locations in order to maximize the coverage of customers. Also, the use of RFID is suggested to count the quantities of collected items in collection points and send the signal to the central return center. This can facilitate the vehicle scheduling for transferring the items from collection points to the return center. The significance of this research is the proposal of RFID-based reverse logistics framework and optimization of locations of collection points which allow economically and ecologically reasonable recycling. Simulation results indicated that the genetic algorithm is able to produce good-quality solutions in terms of coverage of collection points by choosing suitable locations for collection points and RFID can help detect the quantity of returned products so as to increase efficiency of logistics operations.

Strategic logistics outsourcing: An integrated QFD and AHP approach

Third-party logistics service providers (3PLs) play a vital role in contemporary supply chain management. Evaluation and selection of the right 3PLs depends on a wide range of quantitative and qualitative criteria rather than cost-based factors. Although various multi-criteria decision making approaches have been proposed, they have not considered the impact of business objectives and requirements of company stakeholders on the evaluating criteria. To enable the “voice” of company stakeholders is considered, this paper develops an integrated approach for selecting 3PL strategically. In the approach, multiple evaluating criteria are derived from the requirements of company stakeholders using a series of house of quality (HOQ). The importance of evaluating criteria is prioritized with respect to the degree of achieving the stakeholder requirements using analytic hierarchy process (AHP). Based on the ranked criteria, alternative 3PLs are evaluated and compared with each other using AHP again to make an optimal selection.

A fuzzy logic approach to forecast energy consumption change in a manufacturing system

This paper proposes an energy consumption change forecasting system using fuzzy logic to reduce the uncertainty, inconvenience and inefficiency resulting from variations in the production factors. The proposed fuzzy logic approach helps the manufacturer forecast the energy consumption change in the plant when certain production input factors are varied. Predictions given by the proposed system adopts the fuzzy rule reasoning mechanism so that any changes in the overall energy consumption will neither violate the stable power supply and production schedules nor result in energy wastage. To demonstrate how the fuzzy logic approach is applied to a manufacturing system, a case study of the energy consumption forecast in a clothing manufacturing plant has been conducted in an emulated environment. The result of the case indicates a percentage change in the plants energy consumption after analyzing three input parameters. This finding is able to provide a solid foundation on which decision makers and systems analysts can base suitable strategies for ensuring the efficiency and stability of a manufacturing system.

A review of the research methodology for the re-entrant scheduling problem

This paper considers the re-entrant scheduling problem, wherein the most remarkable character is that the jobs enter the processing lines more than once. The objective is to provide a comprehensive review which gives the researchers and practitioners an overview of the applicability of techniques in re-entrant scheduling. Few published reviews dealt with this particular kind of problem and only some research regards the re-entrant character as a hypotaxis of their main problems. This paper is the first paper that gives a full picture of the re-entrant scheduling problem. Considered as a NP-hard problem, a growing number of researchers have employed various methods to solve this complex problem. A survey has been conducted from the recently published literature on the re-entrant problem. This paper has summarised the problem and the relative research methodologies have been studied. Mathematical methods and meta-heuristics, especially Petri net, dispatching rules and genetic algorithm, emerge as the most frequently used methods in recent years, which are presented in detail. Moreover, future research implications have been identified and are suggested. It may help to bring in more awareness of the problem and new techniques to solve it.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

Swarm intelligence applied in green logistics: A literature review

Abstract Green logistics (GL) is gaining increasing attention among academic researchers and industrial practitioners, due to the escalating deterioration of the environment. Various green activities and operations aiming at improving the performance of GL have been applied synthetically, and most of the activities can be modeled as combinatorial optimization (CO) problems. Exact approaches tend to be incapable of solving the CO problems, especially with the increasing complexity. Thus, meta-heuristic approaches are widely adopted, which can generate a satisfactory solution within an acceptable time. Swarm intelligence (SI) is an innovative branch of meta-heuristics derived from imitating the behavioral pattern of natural insects. The distributed control mechanism and simple interactive rules can manage the swarm of insects effectively and efficiently. There are some pilot studies in applying SI into GL, which indicates that the integration of GL and SI could be a promising choice and of great potential. This research reviews the application of SI in GL through a comprehensive and extensive investigation and analysis of extant literature, which includes 115 publications in the last twenty years. The integration of GL and SI is analyzed from the perspective of both the problem context and the methodology. The categories of GL and SI are classified systematically. The CO problems of GL are further studied with SI algorithms, and innovative and universal guidance for algorithm customization in resolving CO problems emerges as well. Further potential research issues and opportunities of GL and SI are also identified in this research.

Design and development of logistics workflow systems for demand management with RFID

Research highlights? In the responsive logistics information system, radio frequency identification can provide visibility of product flow and capture the real time inventory data. ? The captured data are analysed by online analytical process to identify the market segment. ? With advert of artificial neural network, the demand pattern is recognized and the corresponding replenishment strategy can be formulated. This paper discusses demand and supply chain management and examines how artificial intelligence techniques and RFID technology can enhance the responsiveness of the logistics workflow. This proposed system is expected to have a significant impact on the performance of logistics networks by virtue of its capabilities to adapt unexpected supply and demand changes in the volatile marketplace with the unique feature of responsiveness with the advanced technology, Radio Frequency Identification (RFID). Recent studies have found that RFID and artificial intelligence techniques drive the development of total solution in logistics industry. Apart from tracking the movement of the goods, RFID is able to play an important role to reflect the inventory level of various distribution areas. In todays globalized industrial environment, the physical logistics operations and the associated flow of information are the essential elements for companies to realize an efficient logistics workflow scenario. Basically, a flexible logistics workflow, which is characterized by its fast responsiveness in dealing with customer requirements through the integration of various value chain activities, is fundamental to leverage business performance of enterprises. The significance of this research is the demonstration of the synergy of using a combination of advanced technologies to form an integrated system that helps achieve lean and agile logistics workflow.

Towards product customization: An integrated order fulfillment system

To stay competitive, manufacturing companies nowadays pursue product customization; and configure-to-order (CTO) has been recognized as an ideal business model to implement product customization. Due to the complexities resulting from the large number of customized products, an increased attention has been paid to the order fulfillment process in CTO. However, most of the solutions delivered either focus on own interested areas without considering the impacts from/on the others or approach order fulfillment processes from a strategic level. In view of the limitations of existing solutions and the significance of order fulfillment activity automation and integration, this study considers the entire spectrum of order fulfillment process at an operational level and, proposes an integrated order fulfillment system (IOFS). The IOFS is designed to (1) automatically execute order processing, which is conventionally undertaken in a face-to-face manner; (2) configure products and process plans based on product and process family models; and (3) allow real-time data extraction and sharing of the latest information. Therefore, it assists companies to quickly respond to diverse customer requirements and deliver the expected products at low costs. An industrial example of turn unit assemblies is presented to demonstrate the feasibility and potential of the IOFS for product customization.

Stability of fuzzy PID controllers

In this paper, the stability of fuzzy PID controllers is studied. Using the passivity theorem, the stability region of the effective PID parameters can be derived and hence some sufficient conditions for a stable fuzzy controller can be obtained. With these conditions satisfied, a stable set of fuzzy rules can be designed easily.

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.