• Journal of Construction Engineering and Project Management
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• v.10 no.1
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• pp.16-32
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• 2020

Cost and time control of projects is important in preventing project failure. However, achieving effective cost and time control in practice is often challenging. The challenges of project cost and time control in practice are investigated by carrying out a questionnaire survey on the top 150 construction contractors in the UK followed by in-depth semi-structured interviews of practitioners from 15 construction companies in the country. Quantitative analysis reveals that design change is the most important factor inhibiting the ability of UK contractors from effectively controlling both the cost and time of construction projects. Four of the top five factors inhibiting effective cost control are also the top factors inhibiting effective time control albeit in a different order. These top factors-design changes, inaccurate evaluation of project time/duration, risk and uncertainty, non-performance of subcontractors and nominated suppliers were also found to be endogenous factors to the project. Additionally, qualitative analysis of the interviews reveals 16 key challenges to prevent for effective project cost and time control in practice. These are classified into four categorised based on where they stem from as follows; from the organisation (1. Lack of integration of cost and time during project control, 2. lack of management buy-in, 3. complicated project control systems and processes, 4. lack of a project control training regime); from the construction management/project management approach (5. Lapses in integration of interfaces, 6. project control not being implemented from the early stages of a project, 7. inefficient utilisation and control of labour, 8. limited time devoted to planning how a project will be controlled at the outset); from the client; (9. Excessive authorisation gates, 10. use of adversarial and non-collaborative forms of contracts, 11. communication problems within client set-up, 12. obstructive client representatives) and; from the project team (13. Lack of detailed/complete design, 14. lack of trust among the project partners, 15. limited time devoted to project control on site, 16. non-factual reporting). The study posits that knowledge of these project control inhibiting factors and challenges is the first step at ensuring they are avoided and enable the implementation of a more effective project cost and time control process in practice.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.689-694
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• 2018

Recently, fuel consumption efficiency has become the most important issue in the vehicle development process due to the problem of environmental pollution. The air flow patterns of the vehicle body line and rear part are the most important elements affecting the fuel consumption efficiency. Especially, the airflow pattern of the vehicle rear part is the most important design factor to be considered in rear spoiler design. In this paper, the control factors affecting the airflow of the rear spoiler are determined, the airflow sensitivity of these control factors are tested and, then, the optimized control factors to reduce the airflow drag force are proposed. The model of optimized control factors is tested and the values of the optimized control factors are changed by analyzing the S/N ratio and mean value. Finally, the new modified model incorporating the optimized control factors is tested in an air flow tunnel and its ability to decrease the air drag and reduce the cost is verified.

• Journal of Auto-vehicle Safety Association
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• v.4 no.2
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• pp.5-10
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• 2012

Whiplash is the most frequent injury among occupants in low speed rear-end car collision. The aim of this paper is to analyze thecorrelation between influence parameters of head restraints and whiplash injury criteria.In this paper, DFSS (Design for Six Sigma) method is used for optimum design of head restrains. Four control factors of head restraints have selected by function matrix method. The effects of the control factors have been experimentally evaluated by using a sled pulse from 16km/h relative velocity which is suggested by KNCAP (Korean New Car Assessment Program). In order to reduce the noise factors of dynamic tests, whiplash tests were repeated twice. By using DFSS, the correlation between control factors and injury criteria has been comprehended.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.829-835
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• 2009

Parameter design is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. However, there are difficulties in practical application, such as complexity and nonlinear relationships among quality characteristics and control factors (design factors), and interactions occurred among control factors. Neural networks have a learning capability and model free characteristics. There characteristics support neural networks as a competitive tool in processing multivariable input-output implementation. In this paper we propose a substantially simpler optimization procedure for parameter design using neural network. An example is illustrated to compare the difference between the Taguchi method and neural network method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.376-383
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• 2001

Factors leading to poor control of the steam generator in a nuclear power plant are nonminimum phase characteristics, unreliable of flow measurements and nonlinear characteristics, which increase more at low power(below 20%) operation. And the study of problems for water level control in the steam generator is that design water level controller only power renge, not entire. This paper introduces a model predictive control(MPC) algorithm for solving poor control factors and quadratic programming(QP) for solving input constraints. Also presents the design method of stable model predictive controller in the entire power range. The simulation results show the efficiency of proposed MPC controller by comparing with PI controller, and effect of the design parameters.

• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.51-68
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• 2020

Purpose: The primary objective of this research is to develop the optimal operating conditions as well as their associated design spaces for a Cryogenic Submerged Arc Welding(SAW) process by improving its quality and productivity simultaneously. Methods: In order to investigate functional relationships among quality characteristics and their associated control factors of an SAW process, a stepwise design of experiment(DoE) method is proposed in this paper. Based on the DoE results, not only a multi-dimensional design space but also a safe operating space and normal acceptable range(NAR) by integrating statistical confidence intervals were demonstrated. In addition, the optimal operating conditions within the proposed NAR can be obtained by a robust optimal design method. Results: This study provides a customized stepwise DoE method (i.e., a sequential set of DoE such as a factorial design and a central composite design) for Cryogenic SAW process and its statistical analysis results. DoE results can then provide both the main and interaction effects of input control factors and the functional relationships between the input factors and their associated output responses. Maximizing both the product quality with high impact strength and the productivity with minimum processing times simultaneously in a case study, we proposed a design space which can provide both acceptable productivity and quality levels and NARs of input control factors. In order to confirm the optimal factor settings and the proposed NARs, validation experiments were performed. Conclusion: This research may provide significant contributions and applications to many SAW problems by preparing a standardization of the functional relationship between the input factors and their associated output response. Moreover, the proposed design space based on DoE and NAR methods can simultaneously consider a number of quality characteristics including tradeoff between productivity and quality levels.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.8-14
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• 2006

The important function of Ball-Stop part is to operate power shift using suitable pneumatic force for vehicle with more than 5 ton when a driver changes gear. In this paper, we have applied the concept of the DFSS(Design for Six Sigma) to robust design of Ball-Stop part. First, we have found the control factors which could mainly influence the performance of the Ball-Stop part. The simulations of contact between head and detent pin was performed to evaluate effect of control factors according to DOE(Design of experiment) by using $ADAMS^{(R)}$. Finally, we have obtained optimal levels of each factors using $MINITAB^{(R)}$. Through the comparison of the result of optimized design with one of inintial design, we have verified the usefulness of DFSS method which can be applied to robust design of mechanical systems.

• 연구논문집
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• s.26
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• pp.85-94
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• 1996

The purpose of this study is to bring out the optimal design factors which effect on dynamic characteristics in the design of proportional flow control valve with high response characteristics, and to verify the validity of the design factors. In this study, force feedback type flow control valve with nozzle-flapper is studied. And, the influences which fixed orifice, nozzle diameter, and maximum displacement between nozzle and flapper effect on dynamic characteristics are analyzed. We have done simulations using the optimal design factors and simulink(Matlab) as a simulation tool, and verified the validity of our simulations by means of comparison our simulation results with an experimental results of another similar valve.

• Journal of the Ergonomics Society of Korea
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• v.16 no.1
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• pp.107-117
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• 1997

It is necessary to evaluate HMI inaspects of human factors in the design stage of MMIS(man machine interface system) and feedback the result of evaluation because operators performance is mainly influenced by the HMI. Therefore, the MMIS design should be reflected the operators psychological, behavioral and physiological characteristics in the interaction with human machine interface(HMI) in order to improve the safety and availability of the MMIS of a nuclear power plant(NPP) by reduction of human error. The development of human factors experimental evaluation techniques and integrated test facility(ITF) for the human factors evaluation become an important research field to resolve hi,am factors issues on the design of an advanced control room(ACR). We developed am ITF, which is aimed to experiment with the design of the ACR and the human machine interaction as it relates to the control of NPP. This paper presents the development of an ITF that consists of three rooms such as main test room(MTR), supporting test room(STR) and experiment control room(ECR). And, the ITF has a various facilities such as a human machine simulator(HMS), experimental measurement systems and data analysis and experiment evaluation supporting system(DAEXESS). The HMS consists of full-scope simulation model of Korean standard NPP and advanced HMI based on visual display nits (VDUS) such as touch color CRT, large scale display panel(LSDP), flat panel display unit and so on.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.362-373
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• 2004

In this study, we introduce a noble neurogenetic approach to the design of the fuzzy controller. The design procedure dwells on the use of Computational Intelligence (CI), namely genetic algorithms and neurofuzzy networks (NFN). The crux of the design methodology is based on the selection and determination of optimal values of the scaling factors of the fuzzy controllers, which are essential to the entire optimization process. First, tuning of the scaling factors of the fuzzy controller is carried out, and then the development of a nonlinear mapping for the scaling factors is realized by using GA based NFN. The developed approach is applied to an inverted pendulum nonlinear system where we show the results of comprehensive numerical studies and carry out a detailed comparative analysis.