Jai-Hyun Byun

An Integrative Loss Function Approach to Multi-Response Optimization

Loss function approach is effective for multi-response optimization. However, previous loss function approaches ignore thedispersion performance of squared error loss and model uncertainty. In this paper, a weighted loss function is proposed tosimultaneously consider the location and dispersion performances of squared error loss to optimize correlated multipleresponseswith model uncertainty. We proposean approach tominimize the weighted loss function underthe constraint thatthe confidence intervals of future predictions for the multiple responses should be contained in specification limits of theresponses. An example is illustrated to verify the effectiveness of the proposed method. The results show that the proposedmethod can achieve reliable optimal operating condition under model uncertainty. Copyright

The Taguchi Robust Design Method : Current Status and Future Directions

During the past several decades, the Taguchi robust design method has been widely used in various fields successfully. On the other hand, some researchers and practitioners have criticized the method with respect to the way of utilizing orthogonal arrays, the signal-to-noise ratio as a performance measure, data analysis methods, etc., and proposed alternative approaches to robust design. This paper introduces the Taguchi method first, evaluates the validity of the criticisms, and discusses advantages and disadvantages of each alternative. Finally, research issues to be addressed for effective robust design are presented.

An interval approach to robust design with parameter uncertainty

In robust design, it is common to estimate empirical models that relate an output response variable to controllable input variables and uncontrollable noise variables from experimental data. However, when determining the optimal input settings that minimise output variability, parameter uncertainties in noise factors and response models are typically neglected. This article presents an interval robust design approach that takes parameter uncertainties into account through the confidence regions for these unknown parameters. To avoid obtaining an overly conservative design, the worst and best cases of mean squared error are both adopted to build an optimisation approach. The midpoint and radius of the interval are used to measure the location and dispersion performances, respectively. Meanwhile, a data-driven method is applied to obtain the relative weights of the location and dispersion performances in the optimisation approach. A simulation example and a case study using automobile manufacturing data from the dimensional tolerance design process are used to demonstrate the effectiveness of the proposed approach. The proposed approach of considering both uncertainties is shown to perform better than other approaches.

Trends and Future Directions of Quality Control and Reliability Engineering

Department of Industrial and Systems Engineering, Gyeongsang National UniversityIndustrial engineering has played a central role in creating knowledge on quality control and reliability enginee-ring (Q&R) and delivering such knowledge to various industries. This special issue paper is prepared in celebra-tion of the 40

Robust design under normal model departure

Abstract The basic underlying assumption in robust design is that the experimental data have a normal distribution. However, in many practical cases, the experimental data may actually have an underlying distribution that is not normal. The existence of model departure can have a significant effect on the optimal operating condition estimates of the control factors obtained in the robust design framework. In this article, the effect of normal model departure on the optimal operating condition estimates is investigated and a methodology is constructed to deal with the effect of normal model departure. We provide simulation results which indicate that the sample mean and sample variance should not be used as estimators if one suspects that the underlying distribution of the sample is not normal. Extensive Monte Carlo simulations indicate that there exist attractive alternative estimators to the sample mean and sample variance. These estimators exhibit solid performance when the data are normally distributed and at the same time are quite insensitive to normal model departure.

Understanding Robust Design with Paper Helicopter Experiment

Jai-Hyun Byun ․Yong Tae Kim․Min Ji LeeDepartment of Industrial and Systems Engineering and Engineering Research Institute Gyeongsang National University, Jinju, 660-701Robust design method developed by Genichi Taguchi has been very popular since the 1980s and there have been many academic and applied research works on this topic. However, college students and engineers in companies have had difficulty in understanding the method. This paper presents a procedure to implement the robust design method by an easy-to-execute paper helicopter experiment. A crossed array was adopted, which consists of a resolution IV fractional factorial design with 6 control factors and a factorial design with 3 noise factors. Three performance measures were analyzed; signal-to-noise ratio, mean, and standard deviation of the falling time of the paper helicopter that is to be maximized. Control-noise interaction plots are also given to evaluate the degree of the sensitivity of each level of the control factors to the noise factors. The procedure presented in this paper can be helpful to those who want to have basic knowledge in the robust design method.

Hygrothermal Effect on the Strength of Carbon/Epoxy Composite Single-Lap Bonded Joints

The hygrothermal effect on the strength of composite single-lap bonded joints were investigated. The specimens were manufactured in four different manufacturing methods and tested in three different environmental conditions. An interesting result is that the strengths of the joints in the elevated temperature and wet (ETW) conditions were found to be 11 ~ 23% higher than those in the room temperature and dry (RTD) environment. In contrast, the strengths of the joints in the cold temperature and dry (CTD) condition decrease by 8 ~ 21% compared to those in the RTD environment except for cobonded joint. The difference in the strength by testing environments is mainly attributed to the change of the material properties of adhesive by temperature and moisture.

An interval programming model for continuous improvement in micro-manufacturing

ABSTRACT Continuous quality improvement in micro-manufacturing processes relies on optimization strategies that relate an output performance to a set of machining parameters. However, when determining the optimal machining parameters in a micro-manufacturing process, the economics of continuous quality improvement and decision makers’ preference information are typically neglected. This article proposes an economic continuous improvement strategy based on an interval programming model. The proposed strategy differs from previous studies in two ways. First, an interval programming model is proposed to measure the quality level, where decision makers’ preference information is considered in order to determine the weight of location and dispersion effects. Second, the proposed strategy is a more flexible approach since it considers the trade-off between the quality level and the associated costs, and leaves engineers a larger decision space through adjusting the quality level. The proposed strategy is compared with its conventional counterparts using an Nd:YLF laser beam micro-drilling process.

A Prediction Region‐based Approach to Model Uncertainty for Multi‐response Optimization

Multi-response optimization methods rely on empirical process models based on the estimates of model parameters that relate response variables to a set of design variables. However, in determining the optimal conditions for the design variables, model uncertainty is typically neglected, resulting in an unstable optimal solution. This paper proposes a new optimization strategy that takes model uncertainty into account via the prediction region for multiple responses. To avoid obtaining an overly conservative design, the location and dispersion performances are constructed based on the best-case strategy and the worst-case strategy of expected loss. We reveal that the traditional loss function and the minimax/maximin strategy are both special cases of the proposed approach. An example is illustrated to present the procedure and the effectiveness of the proposed loss function. The results show that the proposed approach can give reasonable results when both the location and dispersion performances are important issues. Copyright

Suggestions on Enhancing the Effectiveness of Government Quality Assurance Activities for Military Supplies in Production Stage

ABSTRACT Purpose: Government quality assurance (QA) activities in Korea, which is carried out by the Defense Agency for Technology and Quality, is not effective due to 1) the obscureness of the QA implementation method, 2) the gap between QA activities of provisions and those conduc ted in the fields, and 3) the variation in subjective judgement among the QA personnel. The purpose of this paper is to propose some suggestions to enhance the effectiveness of government QA activities for military supplies in the production stage.Methods: QA activities for military supplies are investigated and proble matic aspects are deduced for the production stage. To secure the effectiveness of the QA activit ies, Defense Contract Management Agency ● Received 4 February 2016, 1st revised 9 March 2016, accepted 1 0 March 2016Corresponding Author(jbyun@gnu.ac.kr)ⓒ 2016, The Korean Society for Quality ManagementThis 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 u nrestricted non-Commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.* 본 논문은 2015년 국방기술품질원의 지원을 받아 수행된 연구내용임.