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Constructing an effective production control policy is the most important issue in wafer fabrication factories. Most of researches focus on the input regulations of wafer fabrication. Although many of these policies have been proven to be effective for wafer fabrication manufacturing, in practical, there is a need to help operators decide which lots should be pulled in the right time and to develop a systematic way to alleviate the long queues at the bottleneck workstation. The purpose of this study is to construct a photolithography workstation dispatching rule (PADR). This dispatching rule considers several characteristics of wafer fabrication and influential factors. Then utilize the weights and threshold values to design a hierarchical priority rule. A simulation model is also constructed to demonstrate the effect of the PADR dispatching rule. The PADR performs better in throughput, yield rate, and mean cycle time than FIFO (First‐In‐First‐Out) and SPT (Shortest Process Time).

As the flourish of today’s supply chain, the traditional model of replenishment will cause accumulation of excessive inventory to the retailers and customers, or cause shortages and inability to meet the demands. To solve this problem, Theory of Constraints (TOC) proposed the replenishment model of demand‐pull, combined with the establishment of factory‐warehouse to achieve performance improvement. In the absence of empirical research, this study applied the Bean Game developed by Dr. Goldratt to design a supply chain system for different scenarios, in order to allow players and managers better understanding and supporting the TOC replenishment method through the operations of the game.

High‐tech industry has been the principal economic source for Taiwan in recent years. The characteristics of high‐tech industries in Taiwan are changeable product markets, short product life cycles and high company attrition rate. In the globalization trend, the high‐tech industry has gradually increased corporate competitiveness and reached the goal of sustainable operations through knowledge management, knowledge sharing and new product research and development. Firms have aggressively strengthened and integrated their internal and external resources and enhanced knowledge sharing to increase industry operational performance. Effectively strengthening the knowledge management operation and performance evaluation of knowledge sharing in Taiwan’s high‐tech industry has become a critical issue. In the selection of knowledge sharing Key Performance Indicators (KPI), this research divided the knowledge sharing indicators into representative strategic indicators such as organizational knowledge learning, organizational knowledge resources, organizational information capacity and organizational knowledge performance through screening using Factor Analysis. The characteristics of the constructs were interdependent. This research calculated and adjusted the correlation among the key performance knowledge sharing indicators using ANP and determined the relative weight of knowledge sharing.

The issue of capacity constraint resources (CCR) or bottlenecks wandering in product mix decision by applying Theory of Constraints (TOC) management philosophy has been mentioned and demonstrated in several papers. In this study, the effect for prolonging the planning period (PPP) so as to stabilize the CCR is investigated. The results show that the effect for PPP alternative will be positive or negative which is depending on the environment condition. However, a majority cases which have positive effect for PPP alternative can be recognized prior knowing the marketing demand, which is significant in the real application.

High‐tech industries in Taiwan exist in an environment with diverse product requirements and intense cost reduction and information integration stress. They must develop new operational directions to increase industry competitiveness. Therefore, Taiwan’s high‐tech industries must continue R&D and creativity, establish knowledge sharing mechanisms and improve new product development (NPD) performance. This research analyzed and explored the influences of knowledge management (KM) and knowledge sharing mechanisms introduced by Taiwan’s high‐tech industries on new product development performance. The relationship between knowledge management capabilities and NPD performance is studied. This research considers the intervening industry and corporate position variables. Taiwan’s high‐tech industries have gradually entered the era of IT region integration and application with competitive advantage creation based upon core techniques. The in‐depth study of knowledge management and knowledge sharing introduced by the high‐tech industry revealed double meanings in academic and practical applications. The research results showed the following: (1) the stronger the knowledge management capabilities of Taiwan’s high‐tech industries, the more significant the NPD performance. (2) The better the knowledge sharing mechanism in Taiwan’s high‐tech industries, the more significant the NPD performance. (3) Corporate scale is not necessarily the critical factor in NPD success and the influence of corporate scale on NPD performance did not show significant differences. (4) The stronger the degree of leading corporate techniques, the more significant the NPD performance.

In recent years, the labor consciousness is gradually valued. During the process of pursuing sustainable operation, the enterprises treat occupational hazard risk as the waste of cost. The purpose of OHSAS 18000 occupational security and health management system is to systematically establish the business managerial measures in terms of occupational security and calamity prevention. This research proceeded with questionnaire analysis with respect to the relationship between the OHSAS 18000 system implementation and competitiveness in Taiwan’s industries. The research result revealed that there was significant relationship between Taiwan firms’ execution of OHSAS 18000 system and industry competitiveness. Thus, the enterprises can decide the proper managerial plans according to the result of their own risk evaluation to prevent the happening of accidents and reduce the operational cost. They can thus completely control business occupational hazard risk through “systematic” management.

Any business activities may have impact on environmental to a certain extent. Enterprises must find appropriate approaches to measure the impact on these environmental aspects, which can be used as the basis to direct enterprises’ efforts to improve the environmental impact. The method used to evaluate significant factors in life cycle assessment standards is the one most commonly used by enterprises in general to measure environmental impact. By this method, the decisive factors of each environmental aspect are given scores according to the preset scoring standard of the organizaion. The scores are added up for each aspect and ranked to assess major environmental apsects. The drawback of this assessment method, that is, it ignores the degree to which each of these factors affects the environment, results in poor credibility. Therefore, this study attempts to solve some qualitative problems by applying to fuzzy theory, in particular, by identifying appropriate fuzzy numbers through fuzzy sets and membership function. Moreover, the study seeks to obtain a crisp value in the process of defuzzifization in order to make up for the shortfall of the original method in dealing with relative weight of decisive factors and thus increase its applicability and credibility. The department of light production of an electronics company is used as an example in this study to measure environmental aspects by employing both the traditional significant factor method and the fuzzy environmental impact assessment model proposed in this study. Based on verification and comparison of results, the model proposed in this study is more feasible as it reduces partiality in decision‐making by taking the relative weights of decisive factors into consideration.

This paper presents neural network‐based recognition system for automatic light emitting diode (LED) inspection. The back‐propagation neural network (BPNN) is proposed and tested. The current‐voltage (I‐V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is doen well, the accuracy of recognition is 100 per cent, and the testing speed of the proposed recognition system is amost one half faster than the traditional inspection system does. The proposed neural‐network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

The objective of this study is to evaluate the equipment risk before and after SEMI S2‐93A implementation, thus providing a guideline for safety improvement. Semiconductor Plant A located in Taiwan’s Hsinchu Science Based Industrial Park with 147 manufacturing machines was used for risk assessment. The study was carried out in three steps. First, a preliminary hazard analysis was conducted. A detailed process safety evaluation was conducted (Hazard and Operability Study, HAZOP); and finally, the equipment risk comparison before and after Semiconductor Equipment Manufacturing Instruction (SEMI S2‐93A) implementation. The preliminary hazard analysis results showed high risk in 21.77 per cent of the manufacturing machines under risk assessment at Plant A. The largest percentage existed in the Diffusion Department. The machine types specified by the hazardous work site review and inspection according to Article 26 of Labor Inspection Regulation (the machines that use such chemicals as, SiHi, HF, HCL, etc. and that are determined to be highly hazardous through preliminary hazard analysis) were added to the detailed process analysis and evaluation. In the third part of this evaluation, the machines at Plant A used for detailed process safety assessment were divided into two groups based on the manufacturing data before and after 1993. The severity, possibility, and actual accident analysis before and after SEMI S2‐93A implementation were compared. The semiconductor Equipment Manufacturing Instruction (SEMI S2‐93A) implementation can reduce the severity and possibility of hazard occurrence.

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work‐order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the ICD packaging industry, this work also proposes a WIP (i.e. work‐in‐process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.