K.L. Yung

A heuristic genetic algorithm for subcontractor selection in a global manufacturing environment

Presents an investigation of how partner selection problems may be optimized by the use of a precedence network of subprojects. At the start, the problem is described by a model with the subscript type of variables and a non-analytical objective function. It cannot be solved by general mathematical programming methods. By using the fuzzy rule quantification method, a fuzzy logic-based decision-making approach for the project scheduling is proposed. We then develop a fuzzy decision embedded heuristic genetic algorithm (GA/FD) to find the solution for partner selection. The approach was demonstrated by the use of an experimental example drawn from a coal-fired power station construction project. The results show us that the suggested approach can quickly achieve the optimal solution for large-sized problems.

A branch and bound algorithm for sub-contractor selection in agile manufacturing environment

Abstract Partnership and partner selection play a key role for “Opportunity Driven” project contractors in agile manufacturing environment. In this paper, we present an investigation on the partner selection problems with engineering projects. Firstly, the problem is described by a 0–1 integer programming with non-analytical objective function. It is proven that the partner selection problem is a type of earliness and tardiness production planning problems. By introducing the concepts of inefficient and ideal candidates, we propose the theory of solution space reduction which can efficiently reduce the complexity of the problem. Then, a branch and bound algorithm embedded project scheduling is developed to obtain the solution. The approach was demonstrated by the use of an experimental example drawn from a construction project of coal fire power station. The computational results have been found to be satisfactory.

CONWIP based control of a lamp assembly production line

Efficient and effective production control systems are very important for manufacturing plants. CONWIP, one of these production control systems, has a high potential of becoming the best one available because it suits a variety of production environments and is easy to implement. In the following paper, we compare the single-loop and multi-loop CONWIP production control systems for an actual lamp assembly production line producing different kinds of products with discrete distribution processing time and demand. A model is formulated with respect to total cost and service level. A novel rule-based genetic algorithm (GA) approach is proposed for the multi-loop CONWIP system to find the optimum parameter setting. The results have shown that the single-loop CONWIP production control system is more efficient than the multi-loop system. It can greatly decrease the total cost and the WIP (Work-In-Process) with zero shortage probability.

An application of fuzzy sets to process performance evaluation

The successfulness of total quality management is dependent on the initiative of employees to apply their problem solving techniques continuously. However, the performance evaluation is quite subjective since it relies on the individual judgements of supervisors who have different perceptions of the process performance. This paper presents a performance measurement system to determine the priority in execution of quality improvement according to the performances of processes. Using a model containing a set of strategy‐related performance measures, misdirection of implementation of improvement projects due to subjective evaluation of process performance can be reduced. A fuzzy set of quality measures is introduced to calculate numerical quality rating for processes. The model is simulated and experimented on with a conventional improvement implementation practice. It is expected that the proposed model is superior in the major competitive capabilities including quality, cost flexibility, delivery reliability and speed.

The implementation of a model for integration of MRP II and TQM

A way of initiating and sustaining the implementation of total quality management (TQM) by exploiting the widely adopted manufacturing resource planning (MRP II) is presented. A detailed analysis of MRP II software has found that they have a number of inherent features that can be further extended to organizational performance including operations efficiency, responsiveness, company‐wide problem‐solving capability and product quality. This paper contributes in the development of a model for the MRP II with the incorporation of mechanisms to initiate a culture change in the organization towards TQM. In the adaptation of MRP II to guide the implementation of TQM, a structural analysis technique was proposed to help develop a model and methodology for the integration. In the structural analysis, an IDEF model of a “reference” company structure was created to illustrate and describe the integration. The reference company, which is a lamp manufacturer, is used to illustrate the systematic implementation of the...

SCADA in an integrated maintenance management system

In the majority of public utilities, achieving optimum utilisation of existing capital assets for meeting future predicted demand is a major function at all levels of management. In this paper, a set of maintenance strategies and a computerised Supervisory Control and Data Acquisition (SCADA) system for achieving an integrated maintenance management is described. The objective of the integrated system is to enable maintenance projects to be better controlled and resources to be properly utilised. A case study is used to illustrate the proposed maintenance strategies which include the identification of real time and historical data required to measure, visualise and quantify the progress of maintenance activities. Existing and proposed systems and procedures are analysed and discussed with major recommendations included for the design and implementation of this integrated system.

The Risk Programming of Virtual Enterprises Based on Algorithms of Min / Max / Mean / Random-PSO

The classical particle swarm optimization (PSO) is an effective method to find the extreme values of continuous functions, however its application in discrete space is still premature. In this text, four algorithms of PSO are proposed to solve the problem of combinatorial optimization. They are designed according to the different reactions between particle extremum and overall extremum and help to solve the problem of risk programming of virtual enterprises. Among these four algorithms of PSO, namely min-PSO, max-PSO, mean-PSO, and random-PSO, random-PSO is concluded as the best after comparisons. Meanwhile, multi-level fuzzy synthetic evaluation is integrated to assess the overall risk level. Simulation analysis suggested that PSO is a simple but effective algorithm to solve the problem of combinatorial optimization

Evolutionary game analysis and regulatory strategies for online group-buying based on system dynamics

ABSTRACT The emergence of online group-buying provides a new consumption pattern for consumers in e-commerce era. However, many consumers realize that their own interests sometimes can’t be guaranteed in the group-buying market due to the lack of being regulated. This paper aims to develop effective regulation strategies for online group-buying market. To the best of our knowledge, most existing studies assume that three parties in online group-buying market, i.e. the retailer, the group-buying platform and the consumer, are perfectly rational. To better understand the decision process, in this paper, we incorporate the concept of bounded rationality into consideration. Firstly, a three-parties evolutionary game model is established to study each player’s game strategy based on bounded rationality. Secondly, the game model is simulated as a whole by adopting system dynamics to analyze its stability. Finally, theoretical analysis and extensive computational experiments are conducted to obtain the managerial insights and regulation strategies for online group-buying market. Our results clearly demonstrate that a suitable bonus-penalty measure can promote the healthy development of online group-buying market.

Plastic Micro Features Produced by Microwelding Machine

The method of using microwelding machine to fabricate micro features on a stainless steel micro mould has been studied. The micro features obtained from molding using an ultrasonic microwelding machine have shown distinctive characteristics. The microflow behavior of polymer melt during the microwelding process is also studied. The micro molds of 0.2mm thick and through holes of 0.05mm and 0.2mm in diameters were used. Results show micro features can be produced using the microwelding machine with molding speed comparable to that of micro injection molding.

A novel 3D model retrieval approach based on model-partitioning and fuzzy relevance feedback

3D models play an important role in many applications, so there is an urgent need for an effective content based 3D model retrieval system. A variety of 3D model retrieval methods have been proposed in recent years. Shape distributions show superiority over other methods due to ease of computation and invariance to Euclidean motion, but there is poor retrieval performance for the loss in information. This paper introduces two model-partitioning methods to improve shape distributions, in which the two enhanced descriptors are combined with a fuzzy feedback method. Experimental results show that the proposed methods can achieve better retrieval performance.