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The purpose of the paper is to show that modern markets are characterized by rapidly changing environments and numerous external forces. Under these conditions, product lifetimes are rapidly reducing. Therefore, products require optimum inspection policies to maintain high quality and reduce costs in the competitive market. This study aims to establish optimal inspection policies of reliability analysis for quantal‐response product with Weibull lifetime components.

This study considers a product consisting of m different components in series with lifetimes that follow Weibull distributions, and applies a competing failure model to examine the proposed series system for quantal‐response products. The maximum likelihood estimators of parameters of the Weibull distribution are derived based on the quantal‐response data in the proposed series system. The statistical features of the model are illustrated through a numerical example of two‐component series products, and the properties of the maximum likelihood estimators were studied via Monte Carlo simulation under a two‐stage inspected scheme for various sampling sizes and inspection time conditions.

Simulation results demonstrate not only that the optimum inspection condition is the inspection times at T₁=0.2 and T₂=0.5 for the two‐stage inspected scheme, but also that the economical sampling size is 150 for both cases.

This research results can be applied to the analysis of one‐shot products, e.g. firework, ammunition, airbag, injector, with Weibull components lifetime distribution or the stockpile storage test.

In daily life, many products, such as light bulbs, fuses, dry batteries, fireworks, semiconductors, are non‐repairable. The non‐repairable products are usually referred to as one‐shot products, or as failed products that are not worth repairing. A one‐shot product is usually required to perform a function once only since its use is normally accompanied by an irreversible reaction or process, e.g. chemical reaction or physical destruction. However, most one‐shot products being stored or deployed are usually not under continuous surveillance. The failed products can only be found by inspection or at the beginning of operation. Therefore, this paper seeks to assess the reliability of one‐shot products.

The study considers a series system consisting of m components with lifetime following Weibull distribution, and applies a competing failure model to investigate the proposed series system for one‐shot products. The maximum likelihood estimators (MLEs) of parameters of the Weibull distribution based on the quantal‐response data in the proposed series system are derived. The model is illustrated with a two‐component series system, and the statistical properties of the MLEs are investigated by Monte Carlo simulation under the two‐stage inspection scheme and the three‐stage inspection scheme.

Simulation results reveal not only that the MLEs of Weibull parameters gradually approximate the true values of Weibull parameters under rising sample sizes, but also that the precision and accuracy of the MLEs of parameters increase with an increasing sample size. Furthermore, the standard deviations of MLEs of Weibull parameters for the two‐stage inspection scheme are smaller than those for the three‐stage inspection scheme.

The paper focuses on the reliability assessment of one‐shot products, e.g. firework, ammunition, airbag, injector, dry battery, with Weibull components lifetime distribution.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.