Browsing by Author "Lee, Amy H. I."

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A green supplier selection model for high-tech industry
(2009-05-01)
Lee, Amy H. I.
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Kang, He-Yau
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Hsu, Chang-Fu
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Hung, Hsiao-Chu
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工業工程與管理學系
With growing worldwide awareness of environmental protection, green production has become an important issue for almost every manufacturer and will determine the sustainability of a manufacturer in the long term. A performance evaluation system for green suppliers thus is necessary to determine the suitability of suppliers to cooperate with the firm. While the works on the evaluation and/or selection of suppliers are abundant, those that concern environmental issues are rather limited. Therefore, in this study, a model for evaluating green suppliers is proposed. The Delphi method is applied first to differentiate the criteria for evaluating traditional suppliers and green suppliers. A hierarchy is constructed next to help evaluate the importance of the selected criteria and the performance of green suppliers. Since experts may not identify the importance of factors clearly, the results of questionnaires may be biased. To consider the vagueness of experts' opinions, the fuzzy extended analytic hierarchy process is exploited. With the proposed model, manufacturers can have a better understanding of the capabilities that a green Supplier must possess and can evaluate and select the most suitable green supplier for cooperation. (C) 2008 Elsevier Ltd. All rights reserved.
A Systematic Evaluation Model for Solar Cell Technologies
(2014)
Hsu, Chang-Fu
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Li, Rong-Kwei
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Kang, He-Yau
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Lee, Amy H. I.
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工業工程與管理學系
Fossil fuels, including coal, petroleum, natural gas, and nuclear energy, are the primary electricity sources currently. However, with depletion of fossil fuels, global warming, nuclear crisis, and increasing environmental consciousness, the demand for renewable energy resources has skyrocketed. Solar energy is one of the most popular renewable energy resources for meeting global energy demands. Even though there are abundant studies on various solar technology developments, there is a lack of studies on solar technology evaluation and selection. Therefore, this research develops a model using interpretive structural modeling (ISM), benefits, opportunities, costs, and risks concept (BOCR), and fuzzy analytic network process (FANP) to aggregate experts' opinions in evaluating current available solar cell technology. A case study in a photovoltaics (PV) firm is used to examine the practicality of the proposed model in selecting the most suitable technology for the firm in manufacturing new products.
A wind turbine evaluation model under a multi-criteria decision making environment
(2012-12-01)
Lee, Amy H. I.
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Hung, Meng-Chan
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Kang, He-Yau
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Pearn, W. L.
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工業工程與管理學系
Due to the impacts of fossil and nuclear energy on the security, economics, and environment in the world, the demand of alternative energy resources is expanding consistently and tremendously in recent years. Wind energy production, with its safe and environmental characteristics, has become the fastest growing renewable energy source in the world. The construction of new wind farms and the installation of new wind turbines are important processes in order to provide a long-term energy production. In this research, a comprehensive evaluation model, which incorporates interpretive structural modeling (ISM) and fuzzy analytic network process (FANP), is constructed to select suitable turbines when developing a wind farm. A case study is carried out in Taiwan in evaluating the expected performance of several potential types of wind turbines, and experts in a wind farm are invited to contribute their expertise in determining the importance of the factors of the wind turbine evaluation and in rating the performance of the turbines with respect to each factor. The most suitable turbines for installation can finally be generated after the calculations. The results can be references for decision makers in selecting the most appropriate wind turbines. (C) 2012 Elsevier Ltd. All rights reserved.
An enhanced model for the integrated production and transportation problem in a multiple vehicles environment
(2016-04)
Kang, He-Yau
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Pearn, W. L.
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Chung, I-Ping
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Lee, Amy H. I.
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工業工程與管理學系
Solving an integrated production and transportation problem (IPTP) is a very challenging task in semiconductor manufacturing with turnkey service. A wafer fabricator needs to coordinate with outsourcing factories in the processes including circuit probing testing, integrated circuit assembly, and final testing for buyers. The jobs are clustered by their product types, and they must be processed by groups of outsourcing factories in various stages in the manufacturing process. Furthermore, the job production cost depends on various product types and different outsourcing factories. Since the IPTP involves constraints on job clusters, job-cluster dependent production cost, factory setup cost, process capabilities, and transportation cost with multiple vehicles, it is very difficult to solve when the problem size becomes large. Therefore, heuristic tools may be necessary to solve the problem. In this paper, we first formulate the IPTP as a mixed integer linear programming problem to minimize the total production and transportation cost. An efficient genetic algorithm (GA) is proposed next to tackle the problem when it becomes too complicated. The objectives are to minimize total costs, where the costs include production cost and transportation cost, under the environment with backup capacities and multiple vehicles, and to determine an appropriate production and distribution plan. The results demonstrate that the proposed GA model is an effective and accurate tool.
An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance
(2011-11-01)
Kang, He-Yau
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Hung, Meng-Chan
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Pearn, W. L.
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Lee, Amy H. I.
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Kang, Mei-Sung
The demands for alternative energy resources have been increasing exponentially in the 21st century due to continuous industrial development, depletion of fossil fuels and emerging environmental consciousness. Renewable energy sources, including wind energy, hydropower energy, geothermal energy, solar energy, biomass energy and ocean power, have received increasing attention as alternative means of meeting global energy demands. After Japan's Fukushima nuclear plant disaster in March 2011, more and more countries are having doubt about the safety of nuclear plants. As a result, safe and renewable energy sources are attracting even more attention these days. Wind energy production, with its relatively safer and positive environmental characteristics, has evolved in the past few decades from a marginal activity into a multi-billion dollar industry. In this research, a comprehensive evaluation model is constructed to select a suitable location for developing a wind farm. The model incorporates interpretive structural modeling (ISM), benefits, opportunities, costs and risks (BOCR) and fuzzy analytic network process (FANP). Experts in the field are invited to contribute their expertise in evaluating the importance of the factors and various aspects of the wind farm evaluation problem, and the most suitable wind farm can finally be generated from the model. A case study is carried out in Taiwan in evaluating the expected performance of several potential wind farms, and a recommendation is provided for selecting the most appropriate wind farm for construction.
An Integrated Purchase and Production Model for Solar Manufacturing
(2013)
Li, Rong-Kwei
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Hsu, Chang-Fu
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Kang, He-Yau
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Lee, Amy H. I.
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工業工程與管理學系
How to improve competitive edges to meet rapidly changing technological innovations and dynamic customer needs is crucial for the survival and success of firms under a global competitive market. Many firms realize that a good supply chain management is a necessity in the intensive competitive international market. In consequence, it is important for a firm to provide products with a lower cost and good quality at the right time and place to maintain a competitive edge. In this paper, a joint replenishment model for multiple suppliers is developed using a mixed integer programming (MIP) to determine the optimal replenishment time and quantity. The model aims to solve the shortcomings of existing joint replenishment models and to increase the performance and customer satisfaction of the replenishment system. The proposed model is applied in a solar cell manufacturer to maintain a good integrated purchase and production plan.
Capacity pricing mechanism for wafer fabrication
(2008-10-01)
Chung, Shu-Hsing
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Lee, Amy H. I.
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Huang, Chun-Ying
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Chuang, Chia-Chien
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工業工程與管理學系
Wafer fabrication is perhaps the most capital-intensive and technology-intensive industry. Due to customer demand uncertainty, the wafer fabrication industry in Taiwan became dramatically competitive. Emergency orders demanded from customers may exist for the need of time-to-market. How to respond to emergency orders from customers, to analyze the impact to production and cost, and to design an appropriate order acceptance plan, have become an important task for enterprises in pursuing higher service quality and ultimate profit maximization. In this paper, we propose a capacity pricing mechanism to evaluate the impacts of emergency orders. The mechanism is constructed under the circumstances that master production scheduling (MPS), capacity requirement planning (CRP), and data for manufacturing costs are known. Through production planning and profit analysis, the mechanism can analyze pricing factors including the process plans of products, priority levels of products, urgency of orders, and number of layers of poly and metal, so as to reflect the length of cycle time, waiting-time savings, impact to cycle time variance of all orders, and usage amount of critical resources. The capacity price for each product type under each priority level can be determined as a result. (C) 2008 Elsevier Ltd. All rights reserved.
Collaborative production-distribution planning for semiconductor production turnkey service
(2007)
Chung, Shu-Hsing
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Chung, I-Ping
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Lee, Amy H. I.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Semiconductor production turnkey service (SPTS) coordinates wafer fabrication with the outsourcing of the remaining processes including circuit probing testing (C/P testing), integrated circuit (IC) assembly and final testing for buyers. To reduce the production cost and lead time in the supply chain, wafer fabricators must be responsible for the production and distribution planning for the SPTS. Therefore, this research develops an integer-programming (IP) -based model of collaborative production-distribution planning. Under this model, multi-products, multi-stages, and multi-outsourcing factories with different processing capabilities are considered. However, the IP model cannot solve the problem within a polynomial time when the problem becomes as complicated as those in real practice. To confront this problem, we adopt and modify the generalized saving algorithm (GSA) so that the proposed algorithm can solve complicated real-world problems efficiently. The numerical results show that the proposed algorithm can significantly increase the solving efficiency.
Heuristic algorithms to solve the capacity allocation problem in photolithography area (CAPPA)
(2008-06-01)
Chung, Shu-Hsing
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Huang, Chun-Ying
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Lee, Amy H. I.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Wafer fabrication is one of the most complex and high competence manufacturing. How to fully utilize the machine capacity to meet customer demand is a very important topic. In this paper, we address the capacity allocation problem for photolithography area (CAPPA), which belongs to a capacity requirement planning scheme, with the process window and machine dedication restrictions that arise from an advanced wafer fabrication technology environment. Process window means that a wafer needs to be processed on machines that can satisfy its process capability (process specification). Machine dedication means that once the first critical layer of a wafer lot is processed on a certain machine, the subsequent critical layers of this lot must be processed on the same machine to ensure good quality of final products. We present six modified heuristics and a linear-programming-based heuristic algorithm (LPBHA) to solve the problem efficiently. The performance of the proposed algorithms is tested using real-world CAPPA cases taken from wafer fabrication photolithography area. Computational results show that LPBHA is the most effective one, and with a least average and a least standard deviation of deviation ratio of 0.294 and 0.085% compared to the lower bound of the CAPPA.
Measuring production performance of different product mixes in semiconductor fabrication
(2006-03-01)
Chung, Shu-Hsing
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Pearn, Wen Lea
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Lee, Amy H. I.
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工業工程與管理學系
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Department of Industrial Engineering and Management
In a competitive market, a company needs to fully utilize its current capacity in order to acquire higher profit. The purpose of this paper is to present an effective approach to find a set of product mix efficient for the company to achieve the optimal production. Simulation is first used to generate the data of performance measures of different product mixes in a semiconductor fabricator. Data Envelopment Analysis (DEA) is applied next to measure multiple inputs and outputs, without pre-assigning weights, for product mixes, and an efficiency score for producing each product mix relative to other mixes can be obtained. The results provide guidance for a fab in accepting orders when its capacity cannot fully satisfy all the product demand. Significance: This paper applied the DEA method to evaluate the production performance with different product mixes in a semiconductor fabricator. The results provide guidance to the fabricator regarding accepting orders to maximize the production efficiency and the profit, while considering several other important input and output factors that maintain production smoothing.