Literature Review on the Experimental Designs in KSQM for 50 Years

Purpose: This article focuses on the reviewing the papers published in the Journal of the Korean Society for Quality Control (JKSQC) and the Journal of the Korean Society for Quality Management (JKSQM) since 1965, in the area of design of experiments. In this paper, moreover, some other contents of another statistical quality control areas is included. Methods: The reviewed articles are classified into the three main categories: theory and application of experimental designs, response surface methodology and mixture experiments, and roust designs. Some omitted papers in the other areas of reviewing works are also included in this paper, and the contents and relationships of the published articles are examined and summarized in each sub-field. Results: We summarize the reviewed papers in the chronological road-maps for each sub-field, and outline the relations of the connected papers. We provide comments on the contents and the contributions of the reviewed papers. The future direction of the research in the theory and application areas of experimental designs can be provided by the contents of this research. Conclusion: The diverse topics on the improving the quality in the various industry fields are studied and published on the theory, methodology and the empirical application in the fields of designs of experiments. We can see that the Korean Society for Quality Management (KSQM) has tremendously contributed on the improvement of quality in the manufacturing and service industries by publishing the reviewed articles in this paper. ● Received 17 May 2016, 1st revised 31 May 2016, accepted 1 June 2016 Corresponding Author(dhjang@pknu.ac.kr) c 2016, The Korean Society for Quality Management This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-Commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ISSN 1229-1889(Print) ISSN 2287-9005(Online) J Korean Soc Qual Manag Vol. 44, No.2: 245-264, June 2016 http://dx.doi.org/10.7469/JKSQM.2016.44.2.245 246 J Korean Soc Qual Manag Vol. 44, No. 2:245-264, June 2016

[1]  Yong Bin Lim,et al.  EVOP in Experiments with Mixtures , 2011 .

[2]  임용빈.  실험계획법에서 최소 표준화 검출 가능 효과의 크기에 관한 연구 , 1998 .

[3]  Seong-Jun Kim.  Robust Design of a Discrete System Using Taguchi's Standard Signal-to-Noise Ratio , 1999 .

[4]  H. F. Martz,et al.  Empirical Bayes estimation of the binomial parameter , 1974 .

[5]  Heung-Gi Cho,et al.  An Objective Method of Risk Assessment Based on Stochastic Modelling , 2013 .

[6]  Sang-Sik Shin,et al.  A Study on Crack Formation in the K11 Objective Individual Combat Weapon Fire Control System using Analysis of Variance , 2015 .

[7]  In-Jun Jeong.  Weighted Mean Squared Error Minimization Approach to Dual Response Surface Optimization: A Process Capability Indices-Based Weighting Procedure , 2014 .

[8]  ChongMan Kim,et al.  Design of Probabilistic Model for Optimum Manpower Planning in R&D Department , 2013 .

[9]  S. Hong.  Determination of Optimum Process Mean and Screening Limits under a Taguchi's Loss Function , 2000 .

[10]  Yong B. Lim,et al.  Mixture response surface methodology for improving the current operating condition , 2009 .

[11]  유성진,et al.  인공 신경망의 패턴분석에 근거한 지능적 부품품질 관리시스템의 설계 , 2001 .

[12]  Seong-Jun Kim,et al.  An optimal tolerancing of the mixture ratio with variance considerations , 2008 .

[13]  Min-Koo Lee,et al.  Design of Rectifying Screening Inspections under a Bivariate Normal Distribution , 2007 .

[14]  A Note on Finding Optimum Conditions Using Mixture Experimental Data with Process Variables , 2013 .

[15]  Won Young Yun,et al.  A Note on Determining the Level of Noise Factor for Smaller-the- Better Characteristics , 2010 .

[16]  Minjae Park,et al.  Cost Analysis on Warranty Policies Using Freund's Bivariate Exponential Distribution , 2014 .

[17]  Ki-Seong Nam,et al.  A Study of D-Optimal Design in Nonlinear Model Using the Genetic Algorithm , 2000 .

[18]  Sangbok Ree.  Study on the Result Changes with the Size of the Variance in Taguchi Method and Factor Experimental , 2013 .

[19]  Sangbok Ree.  Method determining level of Noise Factor of Taguchi Method under various probability distribution , 2009 .

[20]  김성준,et al.  Design and Analysis of Mixture Experiments for Ball Mix Selection in the Ball Milling , 2014 .

[21]  Sung H. Park.  A class of multifactor designs for estimating the slope of response surfaces , 1987 .

[22]  Myung Joon Kim,et al.  A Study on the Bayes Estimation Application for Korean Standard-Quality Excellence Index(KS-QEI) , 2014 .

[23]  In-Jun Jeong.  An Iterative Posterior Preference Articulation Approach to Dual Response Surface Optimization , 2012 .

[24]  Jae-Young Moon,et al.  Analysis of Causal Relationship among Performance Factors of Quality Management in Korean Public Enterprises : Using Malcolm Baldrige Non-profit Criteria , 2009 .

[25]  Suk Joo Bae,et al.  A Study on Optimal Operation Conditions for an Electronic Device Alignment System by Using Design of Experiments , 2015 .

[26]  Jai-Hyun Byun,et al.  A Case Study of Developing Rapid-Hardening Ultra-Low Temperature Adhesives by Mixture Design and Multiple Response Optimization , 2014 .

[27]  Tae-Young Heo,et al.  Statistical Tests for Process Capability Index CpBased on Mixture Normal Process , 2014 .

[28]  Cho Joong-Jae,et al.  Better Confidence Limits for Process Capability Index $C_{pmk}$ under the assumption of Normal Process , 2004 .

[29]  Sang-Ik Kim,et al.  A Case Study for Finding an Efficient M&S Meta Model through Sequential Response Surface Methodology , 2012 .

[30]  Yoon Been Lee,et al.  A Study of Factors Influencing the Costs of Funding as a Function of Research Area and Financial Institutions , 2013 .

[31]  Sangbok Ree.  A Study on Improving Lecture Satisfaction using Taguchi Method , 2014 .

[32]  Sun-Keun Seo.  Two-Dimensional Assessment for Measurement System Analysis , 2014 .

[33]  Kyung-Mo Kim.  Robust Design Methodology under Design Constraints , 2007 .