Browsing by Author "Wu, Muh-Cherng"

Now showing 1 - 20 of 38

A case-based reasoning approach to generating new product ideas
(2006-08-01)
Wu, Muh-Cherng
;
Lo, Ying-Fu
;
Hsu, Shang-Hwa
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents an approach to facilitate the generation of new product ideas. In this approach, a product is represented by a vector, which involves a number of product attributes. These attributes are defined based on the user-centered design (UCD) paradigm. That is, the context of use and interactions with users for the product is described by these attributes. By the product representation, a product database can be established. For a benchmarking product, we use the case-based reasoning (CBR) technique to retrieve those products, which are "sufficiently relevant" to the benchmarking one, from the database. The functions of the retrieved products are the candidate new ideas to be added on the benchmarking product. These retrieved products are screened manually to identify creative and valuable ideas. A prototype system of this approach has been implemented. Experiments show that the proposed approach outperforms the brainstorming technique, which has been widely used in industry.
A case-based reasoning approach to generating new product ideas
(2006-08-01)
Wu, Muh-Cherng
;
Lo, Ying-Fu
;
Hsu, Shang-Hwa
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents an approach to facilitate the generation of new product ideas. In this approach, a product is represented by a vector, which involves a number of product attributes. These attributes are defined based on the user-centered design (UCD) paradigm. That is, the context of use and interactions with users for the product is described by these attributes. By the product representation, a product database can be established. For a benchmarking product, we use the case-based reasoning (CBR) technique to retrieve those products, which are "sufficiently relevant" to the benchmarking one, from the database. The functions of the retrieved products are the candidate new ideas to be added on the benchmarking product. These retrieved products are screened manually to identify creative and valuable ideas. A prototype system of this approach has been implemented. Experiments show that the proposed approach outperforms the brainstorming technique, which has been widely used in industry.
A combined dispatching criteria approach to scheduling dual flow-shops
(2013-02-01)
Chiou, Chie-Wun
;
Chen, Wen-Min
;
Wu, Muh-Cherng
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This study investigates a dual flow-shops scheduling problem. In the scheduling context, there are two flow shops and each shop involves three processing stages. The two shops are functionally identical but their stage processing times for a job are different. While sequentially going through the three processing stages, each job is allowed to travel between the two shops. That is, for a job, each of its three stages could be processed in any of the two shops. Such a context is called dual flow-shops in the sense that the two flow shops capacities are completely shared. The scheduling problem involves two decisions: (1) route assignment (i.e. assigning the processing stages of a job to a shop), and (2) job sequencing (i.e. sequencing the jobs waiting before each stage). The scheduling objective is to minimise the coefficient of variation of slack time (CVS ), in which the slack time (also called lateness) denotes the difference between the due date and total completion time of a job. We propose five genetic-algorithm-based (GA-based) solution methods to solve the scheduling problem, which are called GA-EDD, GA-FIFO, GA-SPT, GA-LFO, and GA-COMBO respectively. Numerical experiments indicate that GA-COMBO outperforms the other four methods.
A comparison of two chromosome representation schemes used in solving a family-based scheduling problem
(2013-06-01)
Chen, Chen-Fu
;
Wu, Muh-Cherng
;
Li, Yi-Hsun
;
Tai, Pang-Hao
;
Chiou, Chie-Wun
Meta-heuristic algorithms have been widely used in solving scheduling problems; previous studies focused on enhancing existing algorithmic mechanisms. This study advocates a new perspective developing new chromosome (solution) representation schemes may improve the performance of existing meta-heuristic algorithms. In the context of a scheduling problem, known as permutation manufacturing-cell flow shop (PMFS), we compare the effectiveness of two chromosome representation schemes (S-old and S-new) while they are embedded in a meta-heuristic algorithm to solve the PMFS scheduling problem. Two existing meta-heuristic algorithms, genetic algorithm (GA) and ant colony optimization (ACO), are tested. Denote a tested meta-heuristic algorithm by X_Y, where X represents an algorithmic mechanism and Y represents a chromosome representation. Experiment results indicate that GA_S-new outperforms GA_S-old, and ACO_S-new also outperforms ACO_S-old. These findings reveal the importance of developing new chromosome representations in the application of meta-heuristic algorithms. (C) 2012 Elsevier Ltd. All rights reserved.
A cross-cultural study of organizational factors on safety: Japanese vs. Taiwanese oil refinery plants
(2008-01-01)
Hsu, Shang Hwa
;
Lee, Chun-Chia
;
Wu, Muh-Cherng
;
Takano, Kenichi
;
工業工程與管理學系
This study attempts to identify idiosyncrasies of organizational factors on safety and their influence mechanisms in Taiwan and Japan. Data were collected from employees of Taiwanese and Japanese oil refinery plants. Results show that organizational factors on safety differ in the two countries. Organizational characteristics in Taiwanese plants are highlighted as: higher level of management commitment to safety, harmonious interpersonal relationship, more emphasis on safety activities, higher devotion to supervision, and higher safety self-efficacy, as we] I as high quality of safety performance. Organizational characteristics in Japanese plants are highlighted as: higher level of employee empowerment and attitude towards continuous improvement, more emphasis on systematic safety management approach, efficient reporting system and teamwork, and high quality of safety performance. The casual relationships between organizational factors and workers' safety performance were investigated using structural equation modeling (SEM). Results indicate that the influence mechanisms of organizational factors in Taiwan and Japan are different. These findings provide insights into areas of safety improvement in emerging countries and developed countries respectively. (c) 2007 Elsevier Ltd. All rights reserved.
A fuzzy CBR technique for generating product ideas
(2008-01-01)
Wu, Muh-Cherng
;
Lo, Ying-Fu
;
Hsu, Shang-Hwa
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents a fuzzy CBR (case-based reasoning) technique for generating new product ideas from a product database for enhancing the functions of a given product (called the baseline product). In the database, a product is modeled by a 100-attribute vector, 87 of which are used to model the use-scenario and 13 are used to describe the manufacturing/recycling features. Based on the use-scenario attributes and their relative weights - determined by a fuzzy AHP technique, a fuzzy CBR retrieving mechanism is developed to retrieve product-ideas that tend to enhance the functions of the baseline product. Based on the manufacturing/recycling features, a fuzzy CBR mechanism is developed to screen the retrieved product ideas in order to obtain a higher ratio of valuable product ideas. Experiments indicate that the retrieving-and-filtering mechanism outperforms the prior retrieuing-only mechanism in terms of generating a higher ratio of valuable product ideas. (c) 2006 Elsevier Ltd. All rights reserved.
A GA methodology for the scheduling of yarn-dyed textile production
(2009-12-01)
Hsu, Hsi-Mei
;
Hsiung, Yai
;
Chen, Ying-Zhi
;
Wu, Muh-Cherng
;
工業工程與管理學系
This paper presents a scheduling approach for yarn-dyed textile manufacturing. The scheduling problem is distinct in having four characteristics: multi-stage production, sequence-dependent setup times, hierarchical product structure, and group-delivery (a group of jobs pertaining to a particular customer order must be delivered together), which are seldom addressed as a whole in literature. The scheduling objective is to minimize the total tardiness of customer orders. The problem is formulated as a mixed integer programming (MIP) model, which is computationally extensive. To reduce the problem complexity, we decomposed the scheduling problem into a sequence of sub-problems. Each sub-problem is solved by a genetic algorithm (CA), and an iteration of solving the whole sequence of sub-problems is repeated until a satisfactory Solution has been obtained. Numerical experiment results indicated that the proposed approach significantly outperforms the EDD (earliest due date) scheduling method-currently used in the yarn-dyed textile industry. (C) 2009 Elsevier Ltd. All rights reserved.
A GA-Tabu algorithm for scheduling in-line steppers in low-yield scenarios
(2009-11-01)
Chiou, Chie-Wun
;
Wu, Muh-Cherng
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents a scheduling algorithm for an in-line stepper in low-yield scenarios, which mostly appear in cases when new process/production is introduced. An in-line stepper is a bottleneck machine in a semiconductor fab. Its interior comprises a sequence of chambers, while its exterior is a dock equipped with several ports. The transportation unit for entry of each port is a job (a group of wafers), while that for each chamber is a piece of wafer. This transportation incompatibility may lead to a capacity-loss, in particular in low-yield scenarios. Such a capacity-loss could be alleviated by effective scheduling. The proposed scheduling algorithm, called GA-Tabu, is a combination of a genetic algorithm (GA) and a tabu search technique. Numerical experiments indicate that the GA-Tabu algorithm outperforms seven benchmark ones. In particular, the GA-Tabu algorithm outperforms a prior GA both in solution quality and computation efforts. (C) 2009 Elsevier Ltd. All rights reserved.
A genetic algorithm embedded with a concise chromosome representation for distributed and flexible job-shop scheduling problems
(2018-01-01)
Lu, Po-Hsiang
;
Wu, Muh-Cherng
;
Tan, Hao
;
Peng, Yong-Han
;
Chen, Chen-Fu
This paper proposes a genetic algorithm for solving distributed and flexible job-shop scheduling (DFJS) problems. A DFJS problem involves three scheduling decisions: (1) job-to-cell assignment, (2) operation-sequencing, and (3) operation-to-machine assignment. Therefore, solving a DFJS problem is essentially a 3-dimensional solution space search problem; each dimension represents a type of decision. The algorithm is developed by proposing a new and concise chromosome representation , which models a 3-dimensional scheduling solution by a 1-dimensional scheme (i.e., a sequence of all jobs to be scheduled). That is, the chromosome space is 1-dimensional (1D) and the solution space is 3-dimensional (3D). In , we develop a 1D-to-3D decoding method to convert a 1D chromosome into a 3D solution. In addition, given a 3D solution, we use a refinement method to improve the scheduling performance and subsequently use a 3D-to-1D encoding method to convert the refined 3D solution into a 1D chromosome. The 1D-to-3D decoding method is designed to obtain a "good" 3D solution which tends to be load-balanced. In contrast, the refinement and 3D-to-1D encoding methods of a 3D solution provides a novel way (rather than by genetic operators) to generate new chromosomes, which are herein called shadow chromosomes. Numerical experiments indicate that outperforms the IGA developed by De Giovanni and Pezzella (Eur J Oper Res 200:395-408, 2010), which is the up-to-date best-performing genetic algorithm in solving DFJS problems.
A genetic algorithm for scheduling dual flow shops
(2012-01-01)
Chiou, Chie-Wun
;
Chen, Wen-Min
;
Liu, Chin-Min
;
Wu, Muh-Cherng
;
工業工程與管理學系
This study examines a dual-flow shop-scheduling problem that allows cross-shop processing. The scheduling objective is to minimize the coefficient of variation of slack time (lateness), where the slack time (ST) of a job denotes the difference between its due date and total completion time. This scheduling problem involves two decisions: job route assignment (assigning jobs to shops) and job sequencing. This study develops a genetic algorithm (GA) embedded with the earliest due date (EDD) dispatching rule for making these decisions. Numerical experiments with the GA algorithm indicate that the performance of adopting a cross-shop production policy may significantly outperform that of adopting a single-shop production policy. This is particularly true when the two flow shops are asymmetrically designed. This study develops a grouping heuristic algorithm to reduce setup time and due-date-based demand simultaneously. This study uses the proposed genetic algorithm (GA) to prove that the grouping heuristic algorithm performs well. Obtaining an approximate optimal solution makes it possible to decide the route assignment of jobs and the job sequencing of machines. (C) 2011 Elsevier Ltd. All rights reserved.
A Hit-Rate Based Dispatching Rule For Semiconductor Manufacturing
(2008)
Wu, Muh-Cherng
;
Hung, Ting-Uao
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Hit-rate, the percentage of on-time completion, is a very important performance measure in a make-to-order semiconductor fab. This paper presents a dispatching algorithm for such a fab with machine-dedication feature. This feature imposes a constraint on the production route due to the advance of manufacturing technology, and has been rarely addressed in previous literature. A dispatching algorithm, called LBSA, was recently developed for a fab with machine-dedication feature. The LBSA algorithm outperformed many other dispatching methods in terms of hit-rate for short-routing products but not so well for long-routing products. This paper develops a dispatching method that shows a high hit-rate performance for both short-routing and long-routing products. Significance: This paper presents a dispatching algorithm, which outperforms previous methods, in terms of hit-rate of a make-to-order semiconductor fab, with machine dedication feature.
A membership pricing policy to facilitate service scale-expansion
(2017-01-01)
Hung, Hui-Chih
;
Chung, Chung-Yu
;
Wu, Muh-Cherng
;
Shen, Wan-Ling
;
工業工程與管理學系
This paper proposes a multi-year membership pricing policy for a service business like a gym chain. In the pricing policy, the equivalent membership price per year is relatively low to attract customers, and the multi-year membership fees must be prepaid in full. The prepaid cash provides resources for scale-expansion by opening new stores. We develop a nonlinear mixed integer programming model to formulate the pricing decisions. Numerical experiments reveal that the multi-year membership pricing policy, from a long-term perspective, is substantially better than the business-as-usual pricing policy (1-year membership) in cash balance, profit, and market share. Yet, the performances of the two pricing policies do not differ much from a short-term perspective. These findings indicate that the multi-year pricing policy may be a good strategy, because it initially attracts less attention of competitors; suddenly it emerges and substantially outperforms its competitors in cash balance, profit, and market share.
A modified Lotka-Volterra model for competition forecasting in Taiwan\'s retail industry
(2014-11-01)
Hung, Hui-Chih
;
Tsai, Yun-San
;
Wu, Muh-Cherng
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
The retail industry is an important component of the supply chain of the goods and services that are consumed daily and competition has been increasing among retailers worldwide. Thus, forecasting the degree of retail competition has become an important issue. However, seasonal patterns and cycles in the level of retail activity dramatically reduce forecasting accuracy. This paper attempts to develop an improved forecasting methodology for retail industry competition subject to seasonal patterns and cycles. Using market share data and the moving average method, a modified Lotka-Volterra model with an additional constraint on the summation of market share is proposed. Furthermore, the mean absolute error is used to measure the forecasting accuracy of the market share. Real Taiwanese retail data from 1999 is used to validate the forecasting accuracy of our modified Lotka-Volterra model. Our methodology successfully mitigates errors from seasonal patterns and cycles and outperforms other benchmark models. These benchmarks include the Bass and Lotka-Volterra models for revenue or market share data, with or without using the moving average method. Our methodology assists the retail industry in the development of management strategies and the determination of investment timing. We also demonstrate how the Lotka-Volterra model can be used to forecast the degree of industry competition. (C) 2014 Elsevier Ltd. All rights reserved.
A Modified Lotka-Volterra Model for Diffusion and Substitution of Multigeneration DRAM Processing Technologies
(2017-01-01)
Hung, Hui-Chih
;
Chiu, Yu-Chih
;
Wu, Muh-Cherng
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
We attempt to develop an effective forecasting model for the diffusion and substitution of multigeneration Dynamic Random Access Memory (DRAM) processing technologies. We consider market share data and propose a modified Lotka-Volterramodel, in which an additional constraint on the summation of market share is introduced. The mean absolute error is used to measure the accuracy of our market share predictions. Market share data in DRAM industries from quarter one (Q1) of 2005 to 2013 Q4 is collected to validate the prediction accuracy. Our model significantly outperforms other benchmark forecasting models of both revenue and market share data, including the Bass and Lotka-Volterra models. Compared to prior studies on forecasting the diffusion and substitution of multigeneration technologies, our model has two new perspectives: (1) allowing undetermined number of multigeneration technologies and inconsecutive adoption of new technologies and (2) requiring less data for forecasting newborn technologies.
A multiple criteria decision for trading capacity between two semiconductor fabs
(2008-10-01)
Wu, Muh-Cherng
;
Chang, Wen-Jen
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents a multiple criteria decision approach for trading weekly tool capacity between two semiconductor tabs. Due to the high-cost characteristics of tools, a semiconductor company with multiple fabs (factories) may weekly trade their tool capacities. That is, a lowly utilized workstation in one fab may sell capacity to its highly utilized counterpart in the other fab. Wit and Chang [Wu, M. C., & Chang, W. J. (2007). A short-term capacity trading method for semiconductor fabs with partnership. Expert Systems with Application, 33(2), 476-483] have proposed a method for making weekly trading decisions between two wafer tabs. Compared with no trading, their method could effectively increase the two fabs' throughput for a longer period such as 8 weeks. However, their trading decision-making is based on a single criterion-number of weekly produced operations, which may still leave a space for improving. We therefore proposed a multiple criteria trading decision approach in order to further increase the two fabs' throughput. The three decision criteria are: number of operations, number of layers, and number of wafers. This research developed a method to find an optimal weighting vector for the three criteria. The method firstly used NN + GA (neural network + genetic algorithm) to find an optimal trading decision in each week, and then used DOE + RSM (design of experiment + response surface method) to find an optimal weighting vector for a longer period, say 10 weeks. Experiments indicated that the multiple criteria approach indeed outperformed the previous method in terms the fabs' long-term throughput. (C) 2007 Elsevier Ltd. All rights reserved.
A short-term capacity trading method for semiconductor fabs with partnership
(2007-08-01)
Wu, Muh-Cherng
;
Chang, Wen-Jen
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper presents a capacity trading method for two semiconductor fabs that have established a capacity-sharing partnership. A fab that is predicted to have insufficient capacity at some workstations in a short-term period (e.g. one week) could purchase tool capacity from its partner fab. The population of such a capacity-trading portfolio may be quite huge. The proposed method involves three modules. We first use discrete-event simulation to identify the trading population. Secondly, some randomly sampled trading portfolios with their performance measured by simulation are used to develop a neural network, which can efficiently evaluate the performance of a trading portfolio. Thirdly, a genetic algorithm (GA) embedded with the developed neural network is used to find a near-optimal trading portfolio from the huge trading population. Experiment results indicate that the proposed trading method outperforms two other bench-marked methods in terms of number of completed operations, number of wafer outs, and mean cycle time. (c) 2006 Elsevier Ltd. All rights reserved.
An analysis of the ceiling height requirement for a large-scale semiconductor fab
(2010)
Wu, Muh-Cherng
;
Shih, Chang-Fu
;
Chen, Chen-Fu
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper proposes the proposition that the fab ceiling height may become a bottleneck for throughput in a large-scale semiconductor fab. To justify the proposition, we propose a systematic approach for the design of the fab ceiling height. In this approach, we develop a queuing network model to evaluate the cycle time performance of a fab design under a target throughput. This queuing network model is adapted from Connor et al. [1996. A queueing network model for semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 9 (3), 412-427] by additionally treating the transportation facilities as finite-capacity resources. Numerical experiments were carried out. The results indicate that a large-scale fab with an inappropriate ceiling height may limit the installation of transportation capacity, which, in turn, limits the utilisation of tool capacity, and thus lowers the fab throughput that can be achieved.
An efficient approach to cross-fab route planning for wafer manufacturing
(2009-10-01)
Wu, Muh-Cherng
;
Shih, Chang-Fu
;
Chen, Chen-Fu
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper proposes an efficient approach to solve a cross-fab route planning problem for semiconductor wafer manufacturing. A semiconductor company usually adopts a dual-fab strategy. Two fab sites are built neighbor to each other to facilitate capacity-sharing. A product thus may be produced by a cross-fab route; that is, some operations of a product are manufactured in one fab and the other operations in the other fab. This leads to a cross-fab routing planning problem, which involves two decisions-determining the cut-off point of the cross-fab route and the route ratio for each product-in order to maximize the throughput subject a cycle time constraint. A prior study has proposed a method to solve the cross-fab route planning problem; yet it is computationally extensive in solving large scale cases. To alleviate this deficiency, we proposed three enhanced methods. Experiment results show that the best enhanced method could significantly reduce the computational efforts from about 13 h to 0.5 h, while obtaining a satisfactory solution. (C) 2009 Elsevier Ltd. All rights reserved.
An enhanced application of Lotka-Volterra model to forecast the sales of two competing retail formats
(2017-07-01)
Hung, Hui-Chih
;
Chiu, Yu-Chih
;
Huang, Huang-Chen
;
Wu, Muh-Cherng
;
工業工程與管理學系
This research develops a sales forecasting model that can analyze the interaction effects of two retail competing formats (convenience-oriented vs. budget-oriented formats). A traditional approach to making such a forecast is based on the Lotka-Volterra equations (also called the LV-model). The LV-model assumes that the population of each species is affected by its self-growth, internal interaction within the species, and external interaction with other species. Most prior studies in business applications directly use sales data as input to the LV-model. The prior approach may result in misleading conclusions when sales data are embedded with seasonal variation, because this variation is not addressed in the original development of the LV-model. Therefore, this study proposes a forecasting framework (an enhanced application of the LV-model). The sales data of each retail format is considered as a compound data, which is decomposed into three individual components: (1) aggregate, (2) competition, and (3) seasonal components. The LV-model is used to forecast the competition component; the other two components are forecasted by typical time series methods; and the data of three components are finally combined into one. Empirical study indicates that the proposed method substantially outperforms the prior approach in terms of forecasting errors (4.4% vs. 16.7% for convenience-oriented and 5.8% vs. 16.2% for budget oriented). In addition, the proposed method reveals a more convincing predator-prey relationship between the two retail formats, which concludes that the convenience-oriented is the predator. To the opposite, the prior approach, concluding that the budget-oriented is the predator, is quite doubtful because the convenience-oriented shall be preferred while the GDP grows over time. This research makes a contribution in how to appropriately apply the LV-model in forecasting revenue and analyzing the interaction effects of two competing business species. (C) 2017 Elsevier Ltd. All rights reserved.
An integrated approach to the design and operation for spare parts logistic systems
(2011-04-01)
Wu, Muh-Cherng
;
Hsu, Yang-Kang
;
Huang, Liang-Chuan
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
This paper attempts to solve a comprehensive design problem for a spare part logistic system. The design factors encompass logistic network design, part vendor selection, and transportation modes selection. Two approaches to solve the problem were proposed. In Approach 1, we simultaneously considered all the design factors and proposed two algorithms (SGA-1 and TGA-1). In Approach 2, the design problem was solved in two stages. Firstly, we aimed to find a near-optimal logistic network. Secondly, with the obtained logistic network, we proposed three algorithms (SGA-2. TGA-2, and NN-GA-Tabu) to find optimal combinations for part vendor and transportation modes selection. Numerical experiments indicate that Approach 2 outperforms Approach 1, and the NN-GA-Tabu outperforms all the other four algorithms. The proposed NN-GA-Tabu might also be a good solution architecture for solving other comprehensive space search problems. (C) 2010 Elsevier Ltd. All rights reserved.