• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.219-223
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• 2009

Recently, Zhao et al. [Fuzzy Optimization and Decision Making (2007) 6, 279-295] characterized the interarrival times as fuzzy random variables and presented a fuzzy random elementary renewal theorem on the limit value of the expected renewal rate of the process in the fuzzy random renewal process. They also depicted both the interarrival times and rewards are depicted as fuzzy random variables and provided fuzzy random renewal reward theorem on the limit value of the long run expected reward per unit time in the fuzzy random renewal reward process. In this note, we simplify the proofs of two main results of the paper.

• Journal of applied mathematics & informatics
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• v.33 no.5_6
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• pp.607-625
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• 2015

Recently, Wang et al. [Computers and Mathematics with Ap-plications 57 (2009) 1232-1248.] and Wang and Watada [Information Sci-ences 179 (2009) 4057-4069.] studied the renewal process and renewal reward process with fuzzy random inter-arrival times and rewards under the T-independence associated with any continuous Archimedean t-norm. But, their main results do not cover the classical theory of the random elementary renewal theorem and random renewal reward theorem when fuzzy random variables degenerate to random variables, and some given assumptions relate to the membership function of the fuzzy variable and the Archimedean t-norm of the results are restrictive. This paper improves the results of Wang and Watada and Wang et al. from a mathematical per-spective. We release some assumptions of the results of Wang and Watada and Wang et al. and completely generalize the classical stochastic renewal theorem and renewal rewards theorem.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.165-172
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• 2005

In recently, Popova and Wu(1999) proved a theorem which presents the long-run average fuzzy reward per unit time. In this note, we improve this result. Indeed we will show uniform convergence of a renewal reward processes with respect to the level ${\alpha}$ modeled as a fuzzy random variables.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.195-204
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• 2006

In this paper, we consider a renewal process in which both the inter-arrival times and rewards are fuzzy random variables. We prove the uniform levelwise convergence of fuzzy renewal and fuzzy renewal rewards. These results improve the result of Popova and Wu[European J. Oper. Research 117(1999), 606-617] and the main result of Hwang [Fuzzy Sets and Systems 116 (2000), 237-244].

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1345-1352
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• 2008

An inventory with constant demand is studied. We adopt a renewal argument to obtain the transient and stationary distribution of the level of the inventory. We show that the stationary distribution can be also derived by making use of either the level crossing technique or the renewal reward theorem. After assigning several managing costs to the inventory, we calculate the long-run average cost per unit time. A numerical example is illustrated to show how we optimize the inventory.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.4
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• pp.191-201
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• 2016

A stochastic process has been used to develop a condition-based model for preventive maintenance of armor units of rubble-mound breakwaters that can make a decision the optimal interval at which some repair actions should be performed under the perfect maintenance. The proposed cost model in this paper based on renewal reward process can take account of the interest rate, also consider the unplanned maintenance cost which has been treated like a constant in the previous studies to be a time-dependent random variable. A function for the unplanned maintenance cost has been mathematically proposed so that the cumulative damage, serviceability limit and importance of structure can be taken into account, by which a age-based maintenance can be extended to a condition-based maintenance straightforwardly. The coefficients involved in the function can also be properly estimated using a method expressed in this paper. Two stochastic processes, Wiener process and gamma process have been applied to armor stones of rubble-mound breakwaters. By evaluating the expected total cost rate as a function of time for various serviceability limits, interest rates and importances of structure, the optimal period of preventive maintenance can easily determined through the minimization of the expected total cost rate. For a fixed serviceability limit, it shows that the optimal period has been delayed while the interest rate increases, so that the expected total cost rate has become lower. In addition, the gamma process tends to estimate the optimal period more conservatively than the Wiener process. Finally, it is found that the more crucial the level of importance of structure becomes, the more often preventive maintenances should be carried out.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.46-56
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• 2002

The presence of imprecise measurement may seriously affect the efficiency of process control and production cost. A cost model is derived to determine the design parameters of the economic asymmetric $\bar{X}$ and S control charts including measurement errors. The effects of imprecise measurement on the performance of the economic asymmetric $\bar{X}$ and S control charts and production cost are examined for the case where the process mean and process standard deviation may change. Application of the proposed control charts is demonstrated through an example. Numerical examples illustrate the effects of imprecise measurement on the design parameters of the proposed control charts. It shows that the imprecision measurement may seriously affrct the ability of the proposed control charts to detect process disturbances quickly, change the sampling frequency, and increase the production cost compared to the control charts excluding measurement errors.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.136-144
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• 2001

The Markov Chain approach is used to develop an economic adjustment model of a process whose quality can be affected by a single special cause, resulting in changes of the process mean by incorrect adjustment of the process when it is operating according to its capability. The $\bar{X}$ control chart is thus used to signal the special cause. It is demonstrated that the expressions for the expected cycle time and the expected cycle cost are easier to obtain by the proposed approach than by adopting that in Collani, Saniga and Weigang (1994). Furthermore, this approach would be easily extended to derive the expected cycle cost and the expected cycle time for the case of multiple special causes or multiple control charts. A numerical example illustrates the proposed method and its application.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1165-1172
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• 2016

In this paper, a surplus process with investments is introduced. Whenever the level of the surplus reaches a target value V > 0, amount S($0{\leq}S{\leq}V$) is invested into other business. After assigning three costs to the surplus process, a reward per unit amount of the investment, a penalty of the surplus being empty and the keeping (opportunity) cost per unit amount of the surplus per unit time, we obtain the long-run average cost per unit time to manage the surplus. We prove that there exists a unique value of S minimizing the long-run average cost per unit time for a given value of V, and also that there exists a unique value of V minimizing the long-run average cost per unit time for a given value of S. These two facts show that an optimal investment policy of the surplus exists when we manage the surplus in the long-run.