• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.12
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• pp.1449-1454
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• 2009

The performance variation of a multibody system is affected by a variation of various design variables of the system. And the effects of design variable variations on the performance variation must be considered in design of a multibody system. Accordingly, a variation analysis of a multibody system needs to be conducted in design of a multibody system. For a variation analysis of a performance, population mean and variance which are called statistical parameters of design variables are needed. However, an evaluation of statistical parameters of design variables is impossible in many practical cases. Therefore, an estimation of statistical parameters of the performance based on sample mean and variance which are called statistic of design variables is needed. In this paper, the variation analysis method for a multibody system based on design variable samples was proposed. And, using the proposed method, a variation analysis of the vehicle ride comfort based on sample statistic of design variables was conducted.

• IE interfaces
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• v.18 no.4
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• pp.444-453
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed "adequate". The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimators are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.975-982
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• 2005

The purpose of the Gage R&R study is to determine whether a measurement system is adequate for monitoring a process. If the measurement system variation is small relative to the process variation, then the measurement system is deemed 'adequate'. The sources of variation associated with the measurement system are compared using an analysis of variance (ANOVA) model, in general. A typical ANOVA model used in a standard Gage R&R study is the two-factor random effect model. Then, the ANOVA partitions the total variation into three categories: repeatability, reproducibility, part variation. However, if the process variation possesses the between group variation, within group variation, and within-part variation, these variations can cause the measurement system evaluation to provide misleading results. That is, in the standard Gage R&R study these variations affect the estimate of repeatability, reproducibility, or both. This paper presents a four-factor nested factorial ANOVA model which explicitly considers these variations for the Gage R&R study. The variance component estimates are derived by setting the EMS equations equal to the corresponding mean square from the ANOVA table and solving. And the proposed model is compared with the standard Gage R&R model.

• Korean Institute of Interior Design Journal
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• v.14 no.1
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• pp.64-72
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• 2005

The purpose of this study was to analyze the flexible system in a typological way that develops and promotes the various methods of flexible system. The main method of this study was literature review and content analysis on various flexible systems and a case study of flexible housing. The flexible system in this typological analysis was classified into two categories: 'Elements of Flexibility' and 'Variation'. The category of Flexibility Elements was categorized into 'Primary Elements'(e.g., walls, floors, and ceilings),'Secondary Elements'(e.g., doors, windows, and furniture), and 'Tertiary Elements'(e.g., lighting, hues and finishing materials). Variation Effect was classified into 'Visual Variation', 'AppBicative Variation', and 'Layout Variation'. Also, Variation could be classified into 'Finish-centered', 'Application-centered', and 'Layout-centered' The flexible system developed in this study is a basis for further concrete flexible methods.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.24-33
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• 2001

As we know, the quality of processes is technically depicted by variation, a product or process with the best quality must naturally require the variation as less as possible. The variation is usually reduced with many ways, say, by adjusting parameters settings under robust design with many turns expensive experiments. So ones are trying to reach the robustness by detecting cheap and simple methods. In this paper, a both practical and simple technique for quality improvement, namely reducing the variation, by data classification is studied. First, all possible system factors are included, which may dominate the variation law. And then we make use of the past observations and their classification as well as boxplot charts to find out the internal rule between the variation and the system factor. Next, adjust the location of the system factor according to the rule so that the variation could, to some extent, be lessened. Finally, two typical quality improvement cases based on data classification are presented.

• International journal of advanced smart convergence
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• v.3 no.1
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• pp.15-19
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• 2014

This study was compared the variation system of body posture condition for stability by the posture. We used a model of bio parameter on the basis of the move state in the standing posture. We compared the sway movement derived from average of the physical sensing condition. Vision condition of variation average (Vi-${\sigma}_{AVG-AVG}$) was verified slightly greater at $13.746{\pm}4.05$ unit. Vestibular condition of variation average (Ve-${\sigma}_{AVG-AVG}$) was verified slightly larger at $7.829{\pm}1.071$ unit. Somatosensory condition of variation average (So-${\sigma}_{AVG-AVG}$) was verified slightly smaller at $2.592{\pm}0.538$ unit. CNS condition of variation average (C-${\sigma}_{AVG-AVG}$) was verified slightly larger at $0.46{\pm}0.105$ unit. The valuation system will be to deduce the model of body management with falling and stroke and all that sort of things. There will be to infer a data algorithm and the evaluation of processing system.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.51-59
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• 2009

Lean construction researchers and practitioners have established a new paradigm for managing construction projects. This paradigm stems from insights gained by viewing project delivery as one kind of production and, inspired by the success of the Toyota Production System, leveraging Toyota's 'lean thinking' in the context of such one-of production. Premises of lean construction are that (1) production systems are riddled with variation, (2) variation can be good or bad, but most of it is bad, (3) most of this variation-good or bad-is self-inflicted; consequently 'lean' passionately promotes good- and relentlessly eradicates bad variation. This paper surveys a few of many lean construction means to manage variation. Lean thinking encompasses a lot more than thinking about variation, but that is the lens used here through which construction project management is viewed. Pairing these premises with lean variation-management tools may help readers broaden the insights they can gain from reading the lean construction literature.

• Transactions of Materials Processing
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• v.18 no.2
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• pp.107-111
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• 2009

Temperature variation happens in micro prism roll mold processing system during machining the prism pattern roll mold using manufacturing optical films of LCD (liquid crystal display). This temperature variation induces pitch errors of the prism patterns. The temperature variation displaces the positions of the diamond cutting tool on the roll which was coated by the copper. In order to prevent the pitch errors, the stabilizing the temperature of machining environment is needed. Therefore, the researching on the temperature variation of the ultra-precision roll mold processing system on the machining of micro prism rot 1 mold is needed. In this paper, the temperature variation of micro prism roll mold processing system is researched, the influence is analyzed, and the study for reducing the pitch errors carried out.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.321-325
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• 1988

The objective of this study is to develop a microcomputer-based adaptive controller for an electro hydraulic velocity control system subjected to the variation of system parameters. The step response performance of the system with the adaptive controller is investigated for the variation of the external load torque, the moment of inertia and the reference inputs, and compared with that obtained by PID controller whose gains are constant. The experimental results show that this proposed model reference adaptive controller is robust to the variation of system parameters and yield much better control performance compared with the conventionel PID controller.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.57-64
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• 2015

In this paper, a model reference adaptive control (MRAC) scheme is applied for the precise and robust motion control of a pneumatic system with load variation. The reference model for MRAC is designed systematically using linear quadratic Gaussian control with loop transfer recovery (LQG/LTR). The sigmoid function of inverse velocity is used to compensate for the nonlinear friction force between the sliding parts. The experimental results show that MRAC effectively overcame the limit of the PID controller when there was unknown disturbance, including abrupt load variation and model uncertainty in the pneumatic control system.