Adisak Pongpullponsak

Minimizing the cost of integrated systems approach to process control and maintenance model by EWMA control chart using genetic algorithm

This paper studies integrated systems approach to Statistical Process Control (SPC) and Maintenance Management (MM). Previously, only four policies which are in control alert signal, out of control alert signal, in control no signal, and out of control no signal, were used in the consideration (Zhou & Zhu, 2008). The objectives of this research are to develop an integrated model between Statistical Process Control and Planned Maintenance of the EWMA control chart. To do this, warning limit is considered to increase the policy from four to six such as warning limit alert signal and warning limit no signal. A mathematical model is given to analyze the cost of the integrated model before the genetic algorithm approach is used to find the optimal values of six variables (n,h,w,k,?,r) that minimize the hourly cost. A comparison between four-policy and six-policy models shows that the six policy model contains the hourly cost higher than that of the four policy model, it is because the addition of the warning limit in the model leads into increased ability of defective product detection. This consequently results to the increase of repairing and maintenance of machines; therefore the hourly cost is higher. Finally, multiple regressions are employed to demonstrate the effect of cost parameters.

System reliability for non-repairable multi-state series–parallel system using fuzzy Bayesian inference based on prior interval probabilities

In this article, the fuzzy concepts are applied in analysis of the system reliability problem. The fuzzy number is used to construct the fuzzy reliability of the non-repairable multi-state series–parallel system (NMSS). The fuzzy failure rate function is represented by an exponential fuzzy number. By using this innovative approach, the fuzzy system reliability of NMSS is created. In order to analyse this fuzzy system reliability, the fuzzy Bayesian point estimate of fuzzy system reliability is made by the conventional Bayesian formula. And, the posterior fuzzy system reliability of NMSS is developed by Bayesian inference with fuzzy probabilities. Finally, the performance of the method is measured by the mean square error of fuzzy Bayesian point estimate for the fuzzy system reliability of NMSS.

Parameter Interval Estimation of System Reliability for Repairable Multistate Series-Parallel System with Fuzzy Data

The purpose of this paper is to create an interval estimation of the fuzzy system reliability for the repairable multistate series–parallel system (RMSS). Two-sided fuzzy confidence interval for the fuzzy system reliability is constructed. The performance of fuzzy confidence interval is considered based on the coverage probability and the expected length. In order to obtain the fuzzy system reliability, the fuzzy sets theory is applied to the system reliability problem when dealing with uncertainties in the RMSS. The fuzzy number with a triangular membership function is used for constructing the fuzzy failure rate and the fuzzy repair rate in the fuzzy reliability for the RMSS. The result shows that the good interval estimator for the fuzzy confidence interval is the obtained coverage probabilities the expected confidence coefficient with the narrowest expected length. The model presented herein is an effective estimation method when the sample size is n ≥ 100. In addition, the optimal α-cut for the narrowest lower expected length and the narrowest upper expected length are considered.

Optimization for estimation to medical service value of informal workers social security office in Thailand

Abstract The objective of this study is to find the model of medication expense of labor that is out of social security system by using data from Social Security Office: Year 2010 Data surveyed from Thai People. The data is classified to be 3 group by the type of labor that is out of social security system receiving the medical service as the patient of hospital as following: outpatient, inpatient without operation and inpatient with operation. As the data that is collected is not stable, Fuzzy Method is applied for analysis to find the model of medical expense of labor that is out of social security system. Therefore, the total medical expense is the sum of these three models.

Hybrid Fuzzy Estimation of System Reliability for Multi-State System

This article is purpose a hybrid estimation of the fuzzy system reliability for the Non-repairable multi-state series-parallel system (NMSS). Considering the fuzzy parameter of NMSS are prior fuzzy parameters. Then the posterior fuzzy parameters of NMSS are constructed by fuzzy Bayesian point estimate of fuzzy system reliability. Moreover, an approach to construct interval estimation of the fuzzy system reliability of NMSS will be used in estimation of the prior fuzzy confidence interval and posterior fuzzy confidence interval of fuzzy system reliability. Finally, the coverage probability and the expected length that it is used to interpret the efficiency of both fuzzy confidence intervals are presented.