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A Simulation Study on The Discounted Cost Distribution under Age Replacement Policy
Dohi, Tadashi,Ashioka, Akira,Kaio, Naoto,Osaki, Shunji Korean Institute of Industrial Engineers 2004 Industrial Engineeering & Management Systems Vol.3 No.2
During the last three decades, a few attentions have been paid for investigating the cost distribution for the optimal maintenance problems. In this article, we derive the moment of the discounted cost distribution over an infinite time horizon for the basic age replacement problem. With first two moments of the discounted cost distribution, we approximate the underlying distribution function by three theoretical distributions. Through a Monte Carlo simulation, we conclude that the log-normal distribution is the best fitted one to approximate the discounted cost distribution.
STUDY ON THE DEVELOPMENT OF A SUPPORT SYSTEM FOR THE DIAGNOSIS OF APHASIA
Misu, Tadashi,Yasuda, Kiyoshi,Dohi, Takeyoshi 대한전자공학회 1992 HICEC:Harbin International Conference on Electroni Vol.1 No.1
There are many methods for the diagnosis of aphasia. We selected the necessary methods used for effective training by speech therapists. The data includes profile, summary, medical information, details of language impairment, and 8 kinds of tests. The system was upgraded to input-output the data effectively and the data base was structured hierarchically. The most important test in Japan is the Standard Language Test of Aphasia for speech therapist. The support system for SLTA and the training system was developed by a similar method. The system guides the examiner, records the data, measures the time of the test, evaluates the data, and control the test. At present, The support system has been evaluated and improved, and works effectively.
Kernel-based nonparametric estimation methods for a periodic replacement problem with minimal repair
Saito, Yasuhiro,Dohi, Tadashi,Yun, Won Y SAGE Publications 2016 Proceedings of the Institution of Mechanical Engin Vol.230 No.1
<P>In this article, we consider nonparametric estimation methods for a periodic replacement problem with minimal repair, where the expected cumulative number of failures (minimal repairs) is unknown. To construct the confidence interval of an estimator of the optimal periodic replacement time which minimizes the long-run average cost per unit time, we apply two kernel-based bootstrap estimation methods and three replication techniques for bootstrap samples, to estimate the optimal periodic replacement time under incomplete knowledge on the failure time distribution. In simulation experiments, we compare those results with the well-known constrained nonparametric maximum likelihood estimate and some parametric models. We also conduct the field data analysis based on an actual minimal repair data and refer to an applicability of our methods.</P>