• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.11 no.2
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• pp.92-101
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• 2001

This article reviewed previous studies on the 3D face recognition and anthropometric facial analysis to design suitable respirators for individuals. 3D facial anthropometric data have not been reported in Korea yet. With 3D facial data, it is possible to design and to manufacture respirators having more effective respirator-face seal and thus providing more comfortable wearing than donning of those respirators designed using 1 and 2-dimensional data. Also 3D data could be used for respirator fit-testing and selecting suitable respirator type and size by computer simulation without several steps of fit-test to each individual worker.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.1
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• pp.1-9
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• 2006

Three categories such as the design of a machine, control and software are necessary in the development of the photomask inspection machine with high resolution. Among them, the design of a software detects inferiority through the comparison of CAD data and real data read by camera from photomask. The block matching algorithm is used since the domain is large and the comparison of data by pixel is accomplished. To correct the error arising from the assembly of a machine, calibration algorithm is used and prefocusing algorithm is suggested to correct the surface of the photomask.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.435-442
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• 2002

It is difficult to access and share design data among heterogeneous CAD systems. Usually, different CAD systems exchange the design data using a neutral format such as IGES or STEP. A prototype CAD system which uses a geometric kernel and a commercial database management system has been implemented. The prototype system used the Open Cascade geometric kernel and the commercial object-oriented database ObjectStore. STEP provides the database schema. The database can be accessed from commercial CAD systems such as SolidWorks or Unigraphics. The data access module from a commercial CAD system is developed with the CAD system's native API, ObjectStore API functions, and ActiveX.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.203-213
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• 2001

The image and impression characteristics of the consumer electronic products have become an important factor in purchasing decisions. This study aims to analyze and interpret the image and impression characteristics based on the consumer preference survey. The survey consisted of two parts. First part was to measure the predetermined 52 design variables that can represent the design variables of the products. In the second part, 60 subjects were requested to evaluate 36 audio/video electronic products on 25 different image attributes such as luxuriousness, attractiveness, and granularity. In this study, empirical data from the survey were analyzed through various multivariate analysis and ANOVA analysis. Additionally, this study suggested a statistical procedure that can be applied to select and/or screen critical design variables. It is expected that the results of this study can provide practical information to the designers of consumer electronic products.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.127-134
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• 2007

Predicting fatigue life of rubber components is an important issue in design procedure for industrial trucks to assure the durability and reliability. Main considerations in designing rubber components against fatigue failure are the compounding technology, shape design, and manufacturing process. Among them the rubber compounding technology is one of the most critical factor to determine more than 50% of component's quality. This paper presents how to improve the durability and reliability of industrial rubber mount during its design, development and prototype testing. The data presented illustrates explicitly the prediction of reliability growth in the product development cycle. The application of these techniques is a part of the product assurance function that plays an important role in rubber components reliability improvement.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.331-343
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• 2002

This paper proposes a fuzzy rule-based model as a means to build usability models between emotional satisfaction and design variables of consumer products. Based on a subtractive clustering algorithm, this model obtains partially overlapping rules from existing data and builds multiple local models each of which has a form of a linear regression equation. The best subset procedure and cross validation technique are used to select appropriate input variables. The proposed technique was applied to the modeling of luxuriousness, balance, and attractiveness of office chairs. For comparison, regression models were built on the same data in two different ways; one using only potentially important variables selected by the design experts, and the other using all the design variables available. The results showed that the fuzzy rule-based model had a great benefit in terms of the number of variables included in the model. They also turned out to be adequate for predicting the usability of a new product. Better yet, the information on the product classes and their satisfaction levels can be obtained by interpreting the rules. The models, when combined with the information from the regression models, are expected to help the designers gain valuable insights in designing a new product.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.216-222
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• 2002

The ergonomic human model can be considered as a tool for the evaluation of ergonomic factors in vehicle design process. The proper anthropometric data on driver's postures are needed in order to apply a human model to vehicle design. Although studies on driver's posture have been carried out for the last few decades, there are still some problems for the posture data to be applied directly to the human model due to the lack of fitness because such studies were not carried out under the conditions for the human model application. In the traditional researches, the joint angles were evaluated by the categorized data, which are not appropriate for the human model application because it is so extensive that it can not explain the posture evaluation data in detail. And the human models require whole-body posture evaluation data rather than joint evaluation data. In this study a postural evaluation function was developed not by category data but by the concept of the loss function in quality engineering. The loss was defined as the discomfort in driver's posture and measured by the magnitude estimation technique in the experiment using a seating buck. Four loss functions for the each joint - knee, hip, shoulder, and elbow were developed and a whole-body postural evaluation function was constructed by the regression analysis using these loss functions as independent factors. The developed postural evaluation function shows a good prediction power for the driver's posture discomfort in validation test. It is expected that the driver's postural evaluation function based on the loss function can be used in the human model application to the vehicle design process.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.47-53
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• 2001

In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

• Proceedings of the Korean Society for Quality Management Conference
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• 2004.04a
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• pp.503-506
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• 2004

Evolutionary operation is useful to improve on-line full-scale manufacturing processes by systematically changing the levels of the process variables without jeopardizing the product. This paper presents a system design for an evolutionary operation software called 'evolutionary optimizer'. The system design is based primarily on data flow diagram. Evolutionary optimizer consists of four modules: factorial design module, many variables module, mixture Production module, and mean/dispersion module.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.4
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• pp.431-438
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• 2000

The purpose of this paper is to design the menu of mobile phone based on the impression engineering. Free response survey analysis was used to collect impression data on mobile phone functions with time interval. Simultaneity analysis was applied to finding the relationship among selected impression. We cluster a set of the related impression so as to design the menu of a mobile phone accordingly. This research is expected to contribute to the improvement of customer satisfaction by reflecting customer's impression in the process of product design.