Browsing by Author "Chung, S. H."

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A comparison of two methods for transforming non-normal manufacturing data
(2007-01-01)
Chung, S. H.
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Pearn, W. L.
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Yang, Y. S.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Many statistical methods applied to manufacturing quality control and operations management have been under the assumption that the process characteristic investigated is normally distributed. If the process characteristic is not normally distributed, a popular approach is to transform the non-normal data into a normal one. In this paper, we consider the Box-Cox transformation, and compare the transformation power using two different parameter estimation methods, including the maximum likelihood estimator (MLE) and the method of percentiles (MOP). The performance comparison is based on the pass rate under the Shapiro-Wilk normality test. The results show that, in general, the MOP has better pass rate, while the MLE has smaller power variation for most cases investigated. For small sample size (n = 5, 10) both methods perform equally well. For large sample size, the MOP is recommended due to its simplicity and significantly higher pass rate.
An Effective Scheduling Approach for Maximizing Polyimide Printing Weighted Throughput in Cell Assembly Factories
(2009-07-01)
Chung, S. H.
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Tai, Y. T.
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Pearn, W. L.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Polyimide printing (PI) is an important process operation but also often the cause of bottlenecks in capital-intensive cell assembly factories. Therefore, the development of an effective scheduling method to maximize throughput in this PI process is essential and difficult. In the polyimide printing scheduling problem (PISP), jobs are given weights and clustered by their product types, which must be processed on identical parallel PI machines. The setup times for two consecutive jobs between different product types in the PI machines are sequence-dependent. In this paper, the PISP is formulated as a mixed integer linear programming model. The PISP is also transformed into a multiple tour maximum collection problem (MTMCP), a well-known network problem which has been investigated extensively. Based on this transformation, one can therefore solve the PISP near-optimally using the efficient algorithm.
Due-date assignment for wafer fabrication under demand variate environment
(2007-05-01)
Pearn, W. L.
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Chung, S. H.
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Lai, C. A.
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工業工程與管理學系
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Department of Industrial Engineering and Management
In the semiconductor industry, dynamic changes in demand force companies to change the product mix frequently and periodically. Assigning tight but attainable due dates is a great challenge under the circumstances that the product mix changes periodically. In this paper, we consider the due-date assignment problem for wafer fabrication and present a due-date assignment model to set manufacturing due dates satisfying the target on-time-delivery rate. The contamination model is applied to tackle the effect of that product mix varies periodically. We demonstrate the effectiveness and accuracy of the proposed model by solving a real-world example taken from a wafer fabrication shop floor in an IC manufacturing factory.
Fast and effective algorithms for the liquid crystal display module (LCM) scheduling problem with sequence-dependent setup time
(2009-07-01)
Chung, S. H.
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Pearn, W. L.
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Tai, Y. T.
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工業工程與管理學系
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Department of Industrial Engineering and Management
The liquid crystal display module scheduling problem (LCMSP) is a variation of the classical parallel machines scheduling problem, which has many real-world applications, particular, in the thin film transistor liquid crystal display (TFT-LCD) manufacturing industry. In this paper, we present a case study on the LCMSP, which is taken from a final liquid crystal display module (LCM) shop floor in a TFT-LCD industry. For the case we investigated, the jobs are clustered by their product types and the machine setup time is sequentially dependent on the product types of the jobs processed on the machine. In LCMSP, the objective is to maximize the total profit subject to fulfilling contracted quantities without violating the due date and machine capacity restrictions. The LCMSP can be modelled as a multi-level optimization problem. The sub-problem of LCMSP can be transformed into the vehicle routing problem with time window (VRPTW). One can therefore solve the LCMSP efficiently using existing VRPTW algorithms. We present two new algorithms based on the savings algorithms with some modifications to accommodate the LCMSP. Based on the characteristics of the LCM process, a set of test problems is generated covering most of the real-world applications for test purposes. Computational results and performance comparisons show that the proposed algorithms solved the LCMSP efficiently and near-optimally. Journal of the Operational Research Society (2009) 60, 921-933. doi:10.1057/palgrave.jors.2602604
Minimising makespan on parallel batch processing machines with non-identical ready time and arbitrary job sizes
(2009)
Chung, S. H.
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Tai, Y. T.
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Pearn, W. L.
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工業工程與管理學系
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Department of Industrial Engineering and Management
This paper considers the parallel batch processing machine scheduling problem which involves the constraints of unequal ready times, non-identical job sizes, and batch dependent processing times in order to sequence batches on identical parallel batch processing machines with capacity restrictions. This scheduling problem is a practical generalisation of the classical parallel batch processing machine scheduling problem, which has many real-world applications, particularly, in the aging test operation of the module assembly stage in the manufacture of thin film transistor liquid crystal displays (TFT-LCD). The objective of this paper is to seek a schedule with a minimum total completion time for the parallel batch processing machine scheduling problem. A mixed integer linear programming (MILP) model is proposed to optimise the scheduling problem. In addition, to solve the MILP model more efficiently, an effective compound algorithm is proposed to determine the number of batches and to apply this number as one parameter in the MILP model in order to reduce the complexity of the problem. Finally, three efficient heuristic algorithms for solving the large-scale parallel batch processing machine scheduling problem are also provided.
Scheduling integrated circuit assembly operations on die bonder
(2007-04-01)
Pearn, W. L.
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Chung, S. H.
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Lai, C. M.
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工業工程與管理學系
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Department of Industrial Engineering and Management
Solving the integrated circuit (IC) assembly scheduling problem (ICASP) is a very challenging task in the IC manufacturing industry. In the IC assembly factories, the jobs are assigned processing priorities and are clustered by their product types, which must be processed on groups of identical parallel machines. Furthermore, the job processing time depends on the product type, and the machine setup time is sequentially dependent on the orders of jobs processed. Therefore, the ICASP is more difficult to solve than the classical parallel machine scheduling problem. In this paper, we describe the ICASP in detail and formulate the ICASP as in integer programing problem to minimize the total machine workload. An efficient heuristic algorithm is also proposed for solving large-scale problems.
The Design of Outsourcing Planning for Semiconductor Backend Turnkey Service
(2008)
Chung, S. H.
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Chung, I. P.
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Tai, Y. T.
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Chu, Y. M.
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工業工程與管理學系
Wafer fabrications provide the semiconductor backend turnkey service (SBTS) that help their customers to handle the outsourcing business of the three backend processing stages including circuit probing testing, integrated circuit assembly, and final testing. When the process of wafer fabrication is completed, the SBTS provider needs to select appropriate outsourcing firms and to allocate the semi-finished orders to them. In the process of selecting suitable outsourcing firms, the SBTS providers consider the constraints of limited capacity, production cost, due dates, and the processing capabilities of each outsourcing firm. The planning problem for SBTS is very complicated because of requirement variations of orders and capability variations of outsourcing firms. In this paper, a mixed integer programming model for SBTS with the total cost minimization criterion is presented. A case is also provided to demonstrate its applicability of the IP model in real practice.