• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.43-50
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• 2014

In this paper, we deal with a single machine scheduling problems integrating with step deterioration effect and a rate-modifying activity (RMA). The scheduling problem assumes that the machine may have a single RMA and each job has the processing time of a job with deterioration is a step function of the gap between recent RMA and starting time of the job and a deteriorating date that is individual to all jobs. Based on the two scheduling phenomena, we simultaneously determine the schedule of step deteriorating jobs and the position of the RMA to minimize the makespan. To solve the problem, we propose a hybrid typed genetic algorithm compared with conventional GAs.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.2
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• pp.57-66
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• 2010

In this paper, we propose an enhanced voice recognition algorithm using adaptive MFCC(Mel Frequency Cepstral Coefficients) and neural network. Though it is very important to extract voice data from the raw data to enhance the voice recognition ratio, conventional algorithms are subject to deteriorating voice data when they eliminate noise within special frequency band. Differently from the conventional MFCC, the proposed algorithm imposed bigger weights to some specified frequency regions and unoverlapped filterbank to enhance the recognition ratio without deteriorating voice data. In simulation results, the proposed algorithm shows better performance comparing with MFCC since it is robust to variation of the environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.113-119
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• 1987

A Multistage production-inventory model is developed for deteriorating items. The model is developed deterministic but time-varing demand pattern and instantaneous delivery. Deterioration rates are assumed to vary from period to period. Discrete version of Pontryagin's maximum principle is used to present the efficient alogrithm to solve this model easily. A numerical example is given to illustrate the derived results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.664-677
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• 2014

Wind energy has proven its viability by the emergence of countless wind turbines around the world which greatly contribute to the increased electrical generating capacity of wind farm operators. These infrastructures are usually deployed in not easily accessible areas; therefore, maintenance routines should be based on a well-guided decision so as to minimize cost. To aid operators prior to the maintenance process, a condition monitoring system should be able to accurately reflect the actual state of the wind turbine and its major components in order to execute specific preventive measures using as little resources as possible. In this paper, we propose a fault detection approach which combines cluster analysis and frequent pattern mining to accurately reflect the deteriorating condition of a wind turbine and to indicate the components that need attention. Using SCADA data, we extracted operational status patterns and developed a rule repository for monitoring wind turbine systems. Results show that the proposed scheme is able to detect the deteriorating condition of a wind turbine as well as to explicitly identify faulty components.

• Smart Structures and Systems
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• v.22 no.2
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• pp.151-159
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• 2018

Maintenance activities are regarded as a key part of the repairable deteriorating system because they maintain the equipment in good condition. In practice, many maintenance policies are used in engineering fields to reduce unexpected failures and slow down the deterioration of the system. However, in traditional maintenance policies, maintenance activities have often been assumed to be performed at the same time interval, which may result in higher operational costs and more system failures. Thus, this study presents two non-periodic preventive maintenance (PM) policies for repairable deteriorating systems, employing the failure rate of the system as a conditional variable. In the proposed PM models, the failure rate of the system was restored via the failure rate reduction factors after imperfect PM activities. Operational costs were also considered, which increased along with the operating time of the system and the frequency of PM activities to reflect the deterioration process of the system. A numerical example was provided to illustrate the proposed PM policy. The results showed that PM activities performed at a low failure rate threshold slowed down the degradation of the system and thus extended the system lifetime. Moreover, when the operational cost was considered in the proposed maintenance scheme, the system replacement was more cost-effective than frequent PM activities in the severely degraded system.

• Industrial Engineering and Management Systems
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• v.1 no.1
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• pp.87-92
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• 2002

A stochastic process {$A_n$, n = 1, 2, ...} is an arithmetic process (AP) if there exists some real number, d, so that {$A_n$ + (n-1)d, n =1, 2, ...} is a renewal process (RP). AP is a stochastically monotonic process and can be used for modeling a point process, i.e. point events occurring in a haphazard way in time (or space), especially with a trend. For example, the vents may be failures arising from a deteriorating machine; and such a series of failures id distributed haphazardly along a time continuum. In this paper, we discuss estimation procedures for an AP, similar to those for a geometric process (GP) proposed by Lam (1992). Two statistics are suggested for testing whether a given process is an AP. If this is so, we can estimate the parameters d, ${\mu}_{A1}$ and ${\sigma}^{2}_{A1}$ of the AP based on the techniques of simple linear regression, where ${\mu}_{A1}$ and ${\sigma}^2_{A1}$ are the mean and variance of the first random variable $A_1$ respectively. In this paper, the procedures are, for the most part, discussed in reliability terminology. Of course, the methods are valid in any area of application, in which case they should be interpreted accordingly.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.119-122
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• 1996

The recently proposed control method using a Lyapunov-like function can give global asymptotic stability to a system with mismatched uncertainties if the uncertainties are bounded by a known function and the uncontrolled system is locally and asymptotically stable. In this paper, we modify the method so that it can be applied to a system not satisfying the latter condition without deteriorating qualitative performance. The assured stability in this case is uniform ultimate boundedness which is as useful as global asymptotic stability in the sense that it is global and the bound can be taken arbitrarily small. By the proposed control law we can deal with both matched and mismatched uncertain systems. The above facts conclude that Lyapunov-like control method is superior to any other Lyapunov direct methods in its applicability to uncertain systems.

• Computational Structural Engineering : An International Journal
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• v.1 no.1
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• pp.71-80
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• 2001

A reliability approach to evaluate structural performance has gained increased acceptability and usage over the past two decades. Most reliability analyses are based on the reliability of an individual component without examining the entire structural system. These analyses often result in either unnecessary repairs or unsafe structures. This study uses examples of series, parallel, and series-parallel models of structural systems to illustrate how the component reliabilities affect the reliability of the entire system. The component-system reliability interaction can be used to develop optimum lifetime inspection and repair strategies for structural systems. These examples demonstrate that such strategies must be based on the reliability of the entire structural system. They also demonstrate that the location of an individual component in the system has a profound effect on the acceptable reliability of that component. Furthermore, when a structure is deteriorating over time, the reliability importance of various components is a1so changing with time. For this reason, the most critical component in the early life of the structure may not tie the most critical later.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.247-254
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• 2011

In this paper, we study a single-machine scheduling problem with deteriorating processing time of jobs and multiple rate-modifying activities which reset deteriorated processing time to the original processing time. In this situation, the objective function is to minimize total completion time. First, we formulate an integer programming model. Since the model is difficult to solve as the size of real problem being very large, we design an improved genetic algorithm called adaptive genetic algorithm (AGA) with spontaneously adjusting crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with the conventional GAs with various combinations of crossover and mutation rates.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.13-18
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• 2003

This paper proposes a design method of PID controllers in the framework of a constrained optimization problem. Owing to the popularity for the controller's simplicity and robustness, a great deal of literature concerning PID control design has been published, which can be classified into frequency-based and time-based approaches. However, both approaches have to be considered together for a designed PID control to work well with a guaranteed closed-loop stability. For this purpose, a penalty function is formulated to satisfy both frequency- and time-domain specifications, and is minimized by a recet nonlinear optimization algorithm to attain optimal PID control gains. The proposed method is compared with Wang's and Ho's methods on a suite of example systems. Simulation results show that the PID control tuned by the proposed method improves time-domain performance without deteriorating closed-loop stability.