International Journal of Reliability, Quality and Safety Engineering

Accelerated degradation test (ADT) has been extensively applied to reliability assessment. To improve the efficiency–cost ratio of ADT, the optimal design method of ADT has become a research hot topic. An optimal design method based on acceleration factor, in which a Wiener degradation model and a step-stress ADT were considered, was proposed in the paper. In order to establish an accurate accelerated degradation model, acceleration factor constant principle was applied to derive the changing rules of Wiener process parameters with accelerated stress. Besides, the exact expression of acceleration factor was determined for a Wiener degradation model. The asymptotic variance of acceleration factor, which was considered as a measure of the consistency of failure mechanisms, was selected to be the objective function of optimal problem so as to ensure that the failure mechanism of products under accelerated stresses is probably consistent with that under the normal use stresses. A numerical example of designing an optimal ADT plan for a certain type electrical connector was studied, in which the effectiveness and feasibility of the proposed method were validated.

A Combined $m$-Consecutive-$k$-out-of-$n$ and Consecutive-$k_b$-out-of-$n$: F System consists of $n$ components ordered in a line such that the system fails iff there exist at least $k_b$ consecutive failed components, or at least $m$ nonoverlapping runs of $k$ consecutive failed components, where $k_b<mk$. This system was been introduced by Mohan et al. [P. Mohan, M. Agrawal and K. Sen, Combined $m$-consecutive-$k$-out-of-$n$: F and consecutive-$k_c$-out-of-$n$: F systems, IEEE Trans. Reliab. 58 (2009) 328–337] where they propose an algorithm to evaluate system reliability by using the (GERT) technique, in the independent case. In this paper, we propose a new formula of the reliability of this system for nonhomogeneous Markov-dependent components. For a Combined $m$-Consecutive-$k$-out-of-$n$ and Consecutive-$k_b$-out-of-$n$: F System with nonhomogeneous Markov-dependent components, we derive closed-form formulas for the marginal reliability importance measure of a single component, and the joint reliability importance measure of two or more than two components using probability generating function (pgf) and conditional pgf methods.

In Japan, the annual sales share of supermarkets and convenience stores increased around 2000. Both self-servicing and delivering a wide variety of products are denominators of these stores, and they have an advantage in retail business competitions because self-service stores can reduce labor costs by engaging consumers with the provision of services and the productivity of these stores is higher than specialty stores. In case of self-service stores, miscellaneous jobs such as cash registering, goods arranging, and shelf reviewing, have to be performed by limited number of clerks and efficient operation methods are required. The inventory management of store shelves for avoiding out-of-stock is an important issue and the AHM-Model which is a famous periodic monitoring inventory utilizing dynamic programming was proposed.

In this paper, store shelves are monitored periodically and are replenished when the total amount of goods is below a threshold. Total expected cost rates are defined and optimal thresholds are discussed utilizing the cumulative damage model analytically.

Most reliability models assume that components and systems experience one failure mode. Several systems such as hardware, however, are prone to more than one mode of failure. Past two-failure mode research derives equations to maximize reliability or minimize cost by identifying the optimal number of components. However, many if not all of these equations are derived from models that make the simplifying assumption that components fail in a statistically independent manner. In this paper, models to assess the impact of correlation on two-failure mode system reliability and cost are developed and corresponding expressions for reliability and cost optimal designs derived. Our illustrations demonstrate that, despite correlation, the approach identifies reliability and cost optimal designs.

A common problem generally encountered during manufacturing process improvement involves simultaneous optimization of multiple ‘quality characteristics’ or so-called ‘responses’ and determining the best process operating conditions. Such a problem is also referred to as ‘multiple response optimization (MRO) problem’. The presence of interaction between the responses calls for trade-off solution. The term ‘trade-off’ is an explicit compromised solution considering the bias and variability of the responses around the specified targets. The global exact solution in such types of nonlinear optimization problems is usually unknown, and various trade-off solution approaches (based on process response surface (RS) models or without using process RS models) had been proposed by researchers over the years. Considering the prevalent and preferred solution approaches, the scope of this paper is limited to RS-based solution approaches and similar closely related solution framework for MRO problems. This paper contributes by providing a detailed step-by-step RS-based MRO solution framework. The applicability and steps of the solution framework are also illustrated using a real life in-house pin-on-disc design of experiment study. A critical review on solution approaches with details on inherent characteristic features, assumptions, limitations, application potential in manufacturing and selection norms (indicative of the application potential) of suggested techniques/methods to be adopted for implementation of framework is also provided. To instigate research in this field, scopes for future work are also highlighted at the end.