Yu-Hsin Lin

Bio: Yu-Hsin Lin is an academic researcher from Minghsin University of Science and Technology. The author has contributed to research in topics: Wafer fabrication & Bottleneck. The author has an hindex of 9, co-authored 18 publications receiving 660 citations.

Research on using ANP to establish a performance assessment model for business intelligence systems

Abstract: In order to compete in the rigorous environment, the electronization has enabled business to deploy business intelligence (BI) systems for the purpose of decision-making However, to avoid the ineffective experiences during the deployment, it is important to clarify the impact factors of a BI system and find out a suitable assessment method to evaluate the performance of BI systems In this paper, an analytic network process (ANP) based assessment model was constructed to assess the effectiveness of BI systems Furthermore, an expert questionnaire was used to filter out useful performance matrices, used as the sub-criteria of the ANP model Finally, a real case was analyzed using the constructed ANP-based effectiveness assessment model for Business Intelligence systems The results indicate that the most critical factors that impact the effectiveness of a BI system are: output information accuracy, conformity to the requirements, and support of organizational efficiency Utilizing this model to assess the BI performance of the studied case, it reveals that 24% improvement in effectiveness has been reached, which consists with the perception of the management level Therefore, this effectiveness assessment model can be used to evaluate the performances of a BI system It can also provide performance indices and improvement directions for BI users and vendors, respectively, for the total succession in system effectiveness and satisfaction

The study of applying ANP model to assess dispatching rules for wafer fabrication

Abstract: Wafer fabrication is a capital-intensive high-tech sector with highly complex manufacturing processes. Therefore, most of the fabs resort to production dispatching as a means to enhancing production efficiency. The commonly seen methods of production dispatching at the present time are devised to meet single performance indicators. Few methods take into account multiple, or even conflicting performance indicators. Therefore, different production control managers adopt different criteria. Also, as performance indicators change with the variances of production lines and actual demands, it is necessary to clarify the rules of varying dispatching methods and their impacts on all the production performance indicators so that it is possible to explore an architecture for multiple-rule or multiple-target production dispatching in order to meet dynamic performance targets. This paper uses analytical network process (ANP) method to construct a dispatching model based on the characteristics of all the production facilities on-site (such as the utilization of bottleneck machines), in order to explore the relationship among various performance indicators and correlation between performance indicators and the dispatching rules. The aim of this paper is to analyze the production dispatching issues of wafer fabs in an effective and systematic approach, so as to provide an on-site dispatching analysis model that takes into consideration production characteristics and indicator adjustments. This paper finds that the most optimal dispatching method for ANP dispatch model is EDD dispatching method, followed by LS dispatching method. FIFO dispatching method yields the worst performance. The ANP dispatching assess model proposed in this paper can surely serves as an analytical architecture for decision makes to evaluate production dispatching models of multiple production indicators in the future.

A study of optimization of injection molding process parameters for SGF and PTFE reinforced PC composites using neural network and response surface methodology

Abstract: This study analyzed variations of mechanical characteristics that depend on the injection molding techniques during the blending of short glass fiber and polytetrafluoroethylene reinforced polycarbonate composites. A hybrid method including back-propagation neural network (BPNN), genetic algorithm (GA), and response surface methodology (RSM) are proposed to determine an optimal parameter setting of the injection molding process. The specimens are prepared under different injection molding processing conditions based on a Taguchi orthogonal array table. The results of 18 experimental runs were utilized to train the BPNN predicting ultimate strength, flexural strength, and impact resistance. Simultaneously, the RSM and GA approaches were individually applied to search for an optimal setting. In addition, the analysis of variance was implemented to identify significant factors for the injection molding process parameters and the result of BPNN integrating GA was also compared with RSM approach. The results show that the RSM and BPNN/GA methods are both effective tools for the optimization of injection molding process parameters.

To construct a monitoring mechanism of production loss by using Fuzzy Delphi method and fuzzy regression technique - A case study of IC package testing company

Abstract: The development of information technology and internet capabilities over the years has been at an accelerated pace of global intense challenges and competitions of the technologies markets. Therefore, the issue of effectively utilizing valuable information located in databases worldwide, by monitoring the performance of their operations became an important issue in the electronic business environment. Methods to address this issue were employed to quickly identify the Key Performance Indicators (KPI's) and operational problems and clarify any relationships between them, to allow the overall business objectives to be achieved. In this paper, the Fuzzy Delphi and ranking methods were used to extract the most concerning issues through expert questionnaires. A fuzzy regression model was then constructed and applied to clarify the relationships between the KPI's and the key management objective, the area of production loss. Therefore, the key factors for future improvements were obtained by tracking the fuzzy regression model. Finally a case study of a semiconductor assembly and testing, through a company in Taiwan, was used to illustrate the proposed framework. The results indicated that this model could be easily implemented to analyze the influence of concerned KPIs on key management objectives.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Multiple criteria decision-making techniques and their applications – a review of the literature from 2000 to 2014

Abstract: Multiple criteria decision-making (MCDM) is considered as a complex decision-making (DM) tool involving both quantitative and qualitative factors. In recent years, several MCDM techniques and approaches have been suggested to choosing the optimal probable options. The purpose of this article is to systematically review the applications and methodologies of the MCDM techniques and approaches. This study reviewed a total of 393 articles published from 2000 to 2014 in more than 120 peer reviewed journals (extracted from Web of Science). According to experts’ opinion, these articles were grouped into 15 fields. Furthermore, these articles were categorised based on authors, publication date, name of journals, methods, tools, and type of research (MCDM utilising research, MCDM developing research, and MCDM proposing research). The results of this study indicated that in 2013 scholars have published articles more than in other years. In addition, the analytic hierarchy process (AHP) method in the individual tool...

Selecting management systems for sustainable development in SMEs: A novel hybrid model based on DEMATEL, ANP, and ZOGP

Abstract: In recent years, sustainable development strategy for enterprises has become an important issue around the globe. There are four management systems (i.e. ISO 9001, ISO 14001, OHSAS 18001, and SA 8000) that can help small and medium enterprises (SMEs) to create sustainable competitive advantages. In view of the fact that the shortage of resources - time, personnel, as well as money - rules most SMEs, this paper proposes a novel hybrid model for selecting optimal management systems under resource constraints, and illustrates the practical application of such a model through an example. This model first applies the Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to construct interrelations among criteria that organizations require. The second step is to obtain the criterion weights through ANP. Lastly, ANP is integrated with a zero-one goal programming (ZOGP) model to obtain optimal alternatives with desired organizational benefits by fully utilizing limited resources. The purpose of this study is to present an integrated approach that could cope with the interdependencies among various criteria and deal with the constraints on resources, and to demonstrate how to select management systems for phased implementation. Therefore, the main contribution of this paper is to enhance the capacity of SMEs to effectively address the challenge of sustainable development through a novel model of prioritizing available management systems.

An integrated MCDM technique combined with DEMATEL for a novel cluster-weighted with ANP method

Abstract: Traditionally, most importance-assessing methods used to demonstrate the importance among criteria by preference weightings are based on the assumptions of additivity and independence. In fact, people have found that using such an additive model is not always feasible because of the dependence and feedback among the criteria to somewhat different degrees. To solve the issue the analytic network process (ANP) method is proposed by Saaty. The general method is easy and useful for solving the above-mentioned problem. However in ANP procedures, using average method (equal cluster-weighted) to obtain the weighted supermatrix seems to be irrational because there are different degrees of influence among the criteria. Therefore, we intended to propose an integrated multiple criteria decision making (MCDM) techniques which combined with the decision making trial and evaluation laboratory (DEMATEL) and a novel cluster-weighted with ANP method in this paper, in which the DEMATEL method is used to visualize the structure of complicated causal relationships between criteria of a system and obtain the influence level of these criteria. And, then adopt these influence level values as the base of normalization supermatrix for calculating ANP weights to obtain the relative importance. Additionally, an empirical study is illustrated to demonstrate that the proposed method is more suitable and reasonable. By the concept of ideal point, some important conclusions drawn from a practical application can be referred by practitioners.