Wen-Tsann Lin

Service quality attributes determine improvement priority

Purpose – Although there are many quality measurement theories and models, all are imperfect; that is, each has its own advantages and disadvantages. Particularly, some models cannot indicate accurate improvement priorities. The purpose of this study is to develop an integrated performance model that improves service quality and acquires accurate improvement priorities that promote customer satisfaction and eliminate resource wastage.Design/methodology/approach – This study applied a performance matrix and quality loss function (QLF) theory to determine priority items needing improvement. A questionnaire was designed to determine the priority of improvement objectives derived from certain questionnaire items that do not fall into the appropriate performance zone (APZ) of the performance matrix. Finally, the QLF was adopted to rank the improvement objectives in terms of priority. A large QLF area indicates customer satisfaction needs improvement.Findings – This study utilized an employee satisfaction surve...

Evaluation of performance in introducing CE marking on the European market to the machinery industry in Taiwan

Purpose – Aims to assess the effect of European Union performance directives related to CE marking on the machinery industry of Taiwan.Design/methodology/approach – This paper adopts a questionnaire to collect information. By means of a statistical scheme, performance indices of importance and difficulty, which meet the directives requirement, are designated. The performance evaluation matrix presented by Lambert and Sharma is modified using an introduced standardized system.Findings – Management in the industry needs simply to locate the difficulty and importance of the directive on a performance matrix. Performance levels can be assessed and the strategy for improving the performance of CE marking established.Originality/value – Provides information on the best countermeasure that can be obtained to serve as a reference for the industry to introduce CE marking.

A study on the improvements of new product development procedure performance–an application of design for Six Sigma in a semi-conductor equipment manufacturer

With the pressure of intensive global competition and the trend of shortening product life-cycle, the procedure for new product development (NPD) has become the focus of business concerns and investment of large corporations and the key strategy to upgrade competitiveness of corporations. An effective NPD procedure can meet the demands on quality, time-to-delivery and cost limitations of a corporation. Measuring and analysing the performance of the existing NPD procedure and pinpointing and resolving the problems of the existing NPD procedure is the key to improve the NPD performance to meet a corporations demands. Six Sigma is a systemic procedure commonly used to improve product quality. This paper proposes a model to evaluate and improve the performance of NPD procedures by following the systemic procedure of Six Sigma and applying criteria defined by application of performance matrix, factor analysis, and theory of constraints. The resulting model is then verified with real life NPD procedures from a certain semi-conductor equipment manufacturer such that corporative competitiveness can be enhanced through the elevating cycle of performance evaluation, problem excavation, causes analysis, and countermeasure determination and execution proposed by this paper.

A fuzzy AHP-based performance evaluation model for implementing SPC in the Taiwanese LCD industry

Statistical process control (SPC) is one of the most practical and widely used tools to enhance product quality and reduce costs. However, the implementation of SPC has often resulted in unsatisfactory performance; moreover, there is no well-established standard for evaluation of the results of introducing the system. The present study addresses this problem by proposing an effective and convenient performance-evaluation model for implementing SPC. The proposed model draws on the DMAIC methodology of Six Sigma, the performance-evaluation model of Lin et al. (Lin, W.T., Liu, C.H., Hsu, I.C., and Lai, C.T., 2004. An empirical study of QS 9000 in the automobile and related industries in Taiwan. Total Quality Management, 15 (3), 335–378), and the fuzzy mathematical programming of Kaufmann and Gupta (Kaufmann, A. and Gupta, M.M., 1991. Introduction to fuzzy arithmetic: theory and application. New York: Van Nostrand Reinhold) to define the fuzzy indices and control values of importance, action, and performance in developing the proposed performance-evaluation model. The model is then applied in a case study of a Taiwanese liquid crystal display manufacturer. A questionnaire is designed to establish fuzzy indices of importance, action, and performance values for assessment by analytic hierarchy process methodology. Various critical factors and feasible improvement strategies are then compared (using computed weights) to determine the priority of the improvement strategies. To verify improvement, the same model is used to re-evaluate system control performance after implementing the improvement strategies for some time. The study demonstrates that the proposed model is an effective and convenient tool that can be used to analyse and improve the performance of an existing SPC system or to enhance success in implementing a new SPC system while working within constraints of time and costs.

Abnormal diagnosis of Emergency Department triage explored with data mining technology: An Emergency Department at a Medical Center in Taiwan taken as an example

Triage helps to classify patients at emergency departments to make the most effective use of resources distributed. What is more important is that accuracy in carrying out triage matters greatly in terms of medical quality, patient satisfaction and life security. As the numbers of patients in emergency departments increase, learning from the examples of abnormal diagnosis of triage in order to make modifications, constitutes a significant issue. The researcher worked with the Emergency Department of a Taiwan Medical Center to build a model to view abnormal diagnoses in the database from the establishment of a flow path and the selection of parameters for sampling. Data on patients were derived from the database. Two-stage cluster analysis (Wards method and K-means) and decision tree analysis were made on 501 abnormal diagnoses in an emergency department. It was found that nursing personnel make more frequent triage diagnoses than physicians do. Most of abnormal diagnoses stems from patients rather than the diagnosis on the day. Pulse and temperature have greater distinction. The researcher proposes seven correlation laws based on confidence and support proportions, derived from sample point conforming to correlation law that abnormal diagnosis is most likely in diseases of pneumonia and cirrhosis, etc. Through data mining technology, the researchers triage expert system is written in simulation. After periodic updates, it can improve the system and education training without the influence of the subjective factor.

The use of fuzzy measures in a performance-evaluation model for ERP implementation among Taiwanese semiconductor manufacturers

Many semiconductor-related manufacturing enterprises in Taiwan have embarked upon the implementation of enterprise resource planning (ERP) to integrate and optimize various business processes across the entire firm. The present study proposes a performance-evaluation model of ERP implementation utilizing fuzzy measures. The paper then presents an empirical study of semiconductor-related manufacturers in Taiwan in which the proposed model is used to: (i) identify the critical implementation items requiring improvement; and (ii) rank the strategies for improving them according to weight value. A systematic approach is thus proposed to: (i) examine the performance of an ERP implementation process; (ii) determine the items to be improved; and (iii) select appropriate and feasible strategies to improve these items. The proposed model can ensure successful implementation of ERP and thus enhance its potential benefits for semiconductor manufacturers.

Research on integrating different methods of neural networks with case-based reasoning and rule-based system to infer causes of notebook computer breakdown

Important issues for notebook computer companies include how to ascertain the problems of machines sent by customers, and then assigning those machines to the appropriate department for servicing; and how to maintain breakdown data to save both handling time and costs. However, in practical application, unreliable data decreases the models accuracy, and thus, new methods are brought forward in rapid succession to increase accuracy when inferring causes of notebook computer breakdown. This study integrated several different methods, consisting of a neural network, with case-based reasoning (CBR) and a rule-based system (RBS) to propose a gradual model for inferring causes of notebook computer breakdown. It stressed that the model should have accuracy, elasticity, and transparent interpretability. The model contains three phases: data extracting, group indexing and knowledge creation. Initially, the data extraction phase uses a self-organizing map (SOM) and a revised learning vector quantization network method to reduce isomorphic data to similarity characteristic-based clustering, thus, improving data quality. Then, the group indexing phase establishes a clustering index prediction model based on a back-propagation network (BPN) and genetic algorithm (GA) to increase the efficiency of case selections. Then, the knowledge creation phase uses CBR and RBS to create a notebook computer breakdown case selection model to determine the breakdown cause. Finally, the experimental results show that data purification can actually improve the models accuracy. The CBR with clustering index and rule-based reasoning has a better classification accuracy rate than either the CBR, without the clustering index and rule-based reasoning, or the traditional CBR, in addition, it provides a reference for inferring causes of notebook computer breakdown.

Establishing ISO 10015 accreditation system performance model for domestic enterprises

Under Challenge 2008: Major Plans for National Development and New 10 Major Construction Projects by Council of Economic Development and Planning, talent fostering and research development will be the main consideration in the four major investments. With artificial neural network classification technology, a best network structure that eliminates over- or under-evaluation of self-assessment and actual implementation by enterprises is simulated. The accuracy rate of the module is 100% and that of sample is 98.88%. This can measure actual input and manpower training performance level of enterprises. With cross performance matrix, the researcher explores input strategies of organizations on TTQS index perception importance, expert assessment actual implementation and organization self-assessment satisfaction to find the difference of organizations on TTQS index perception important tuned into actual execution. Key questions include learning results transfer working environment, connection of training planning and operation goal achievement and training quality management system and documentation manuals, etc. Values of aspects and indexes of enterprises assessed as Group A (benchmarking) and Group B (excellent) by experts in the database through AHP questionnaire. This will be reference for enterprises on input resource strategies in TTQS index. Beginning planning, design and execution will affect results and review. After sorting in fuzzy hierarchy analysis, the researcher has Enterprise Development Strategies or Strategy Map/Blueprint (Annual Business Development Plan), including development of human resources and training planning details, themes or directions and explanations to employees. With the evaluation model, it is hoped enterprises wishing to be engaged in humanity can have self-evaluation and improve overall human resources based on the solutions in this study. Domestic enterprises can also shorten the time of introducing ISO10015, reduce cost and increase the success rate.

An empirical analysis on auto corporation training program planning by data mining techniques

Research highlights? In this study we introduce Taiwan TrainQuali System (TTQS). ? Analyzing past education training data with SOM and K-means. ? Establishing education training prediction model to explore training performance. ? Verifying practical feasibility of education training prediction model in manufacture industry. Under limited resources in corporation education training, to enhance human resources quality, making education training program planning more efficient is a significant issue in training future talents.In accordance with Taiwan TrainQuali System (TTQS), the basic training structure is ton specify P (Plan) and D (Design). Ensuing results will be easier and successful. From TTQS database of Bureau of Employment and Vocational Training, corporations in Taoyuan, Hsinchu and Miaoli winning Gold Medals (Group B) have gaps outside control line in P and D. Enhancement is needed in the gap. The paper aims at a certain company winning Gold Medals in Taoyuan, Hsinchu and Miaoli to locate hidden or unobvious information with data mining, which will help future education training course planning and design.The researchers use two-stage clustering (SOM and K-means) under data mining theory to collect personnel training data of Automobile Corporation A in Taiwan and China with data mining and analysis. The results under the two algorithms will serve as reference for future education training courses. In the end, in combination of back-propagation neural network to develop education training prediction model, the research offers reference for writing knowledge management system to enhance effects of personnel participation in training at corporations.

Construction of a 3C Product Mold Manufacturing Process Predictive Optimization Model

Mold trials are critical in the mold development process; therefore, it is necessary to develop predictive models that can control processing results and solve problems in processing parameter optimization to ensure manufacturing efficiency and processing quality. Using the six sigma method, this research constructed an optimized 3C (Computer, Communication, and Consumer electronic) product mold manufacturing process predictive model, and conducted an empirical study on the largest electronic products foundry. The Taguchi parameter design method, the back propagation network (BPN) prediction method, and genetic algorithms (GAs) were used to establish an optimization search module. The surface quality was inferred by the network predictive model as a limiting condition for acquiring the maximized material removal rate in milling. The optimized milling processing parameters of the maximum fitness degree can be determined by GA. The findings can serve as a practical reference for quality improvements and decision planning.