Masami Miyakawa

Analysis of Incomplete Data in Competing Risks Model

Parametric and nonparametric estimation methods are proposed for reliability characteristics of one failure mode under competing risks with incomplete data; some of the failure times are observed without observing the cause of failure. The efficiencies of these methods are discussed.

Consumer evaluation perspectives of service quality: evaluation factors and two-way model of quality

A two-part investigation of service quality is made to explore perspectives by which consumers evaluate the quality of services. First, attributes constituting quality are determined for several representative mass-market services, and a survey is made of consumer expectations for quality improvement. Using factor analysis, consumer evaluation factors for services are derived and examined across service categories. Next, an investigation is made of the applicability of a two-way model of quality for the same service quality attributes. Using the results of a second survey, the attributes are categorized according to their level of fulfillment and the resultant consumer satisfaction or dissatisfaction. Implications for quality planning and assurance activities are also discussed.

Reliability of a linear connected-(r,s)-out-of-(m,n):F lattice system

A linear connected-(r,s)-out-of-(m,n):F lattice system has its components ordered like the elements of a (m,n)-matrix such that the system fails if all components in a connected (r,s)-submatrix fail. This paper proposes a recursive algorithm, named Yamamoto-Miyakawa (YM), for the system reliability. The YM algorithm requires O(s/sup m-r//spl middot/m/sup 2//spl middot/r/spl middot/n) computing time. Comparisons with the existing methods show its usefulness. We prove that the reliability of the large system tends to exp(-/spl mu//spl middot//spl lambda//sup r/spl middot/s/) as n=/spl mu//spl middot/M/sup /spl eta/-1/, m/spl rarr//spl infin/ if every component has failure probability /spl lambda//spl middot/M/sup /spl eta//(r/spl middot/s/), where /spl mu/, /spl lambda/, /spl eta/ are constant, /spl mu/>0, /spl lambda/>0, /spl eta/>s, or r/(r-1)>/spl eta/>1. >

Application of genetic algorithm to numerical experiment in robust parameter design for signal multi-response problem

Abstract The conventional approach by Dr. Taguchi has been known as an off-line quality control to improve the performance of products or processes at low cost. Most previous Taguchi method applications have dealt only with static single-response problems. But in the recent years, the design has more complicated requirements; not only have more than one quality characteristic, but also deal in dynamic system. Therefore, several approaches dealing with multi-response problems have been increasingly reported. However, they have focused on the static system; the multi-response problems in dynamic system still have received only limited attention. This research proposes an approach using the genetic algorithm to find the best setting of the controllable factors, and outer orthogonal array to consider noises. The objective is to minimize the total average quality loss for the dynamic multi-response numerical experiment. In addition, to enhance the capability of the proposed approach, identifying the adjustment factor according to the two-step method by Dr. Taguchi is applied for the case of changing products or processes’ requirements in the future. The effectiveness of the proposed approach will be demonstrated by an example of a temperature control circuit.

On Stochastic Coherent Systems

As an idea of non-coherent systems, such systems where the system’s state can not be completely determined by the states of its components are considered. This structual model will be used in identifying the failure mechanism based on failure pattern data. The properties of such systems are also investigated.

Statistical testing procedure for the interaction effects of several controllable factors in two-valued input-output systems

Suppose several two-valued input-output systems are designed by setting the levels of several controllable factors. For this situation, the Taguchi method has proposed assigning the controllable factors to the orthogonal array and using analysis of variance (ANOVA) for the standardized signal-noise (SN) ratio, which is a natural measure for evaluating the performance of each input-output system. Though this procedure is simple and useful in application indeed, the result can be unreliable when the estimated standard errors of the standardized SN ratios are unbalanced. In this article, we treat the data arising from the full factorial or fractional factorial designs of several controllable factors as the frequencies of high-dimensional contingency tables, and propose a general testing procedure for the main effects or the interaction effects of the controllable factors.