Hybrid journal (It can contain Open Access articles) ISSN (Print) 1479-389X - ISSN (Online) 1479-3903 Published by Inderscience Publishers[449 journals]

Authors:Nse Udoh, Effanga Effanga, Christian Onwukwe Pages: 1 - 13 Abstract: A Complementary Optimal Age Maintenance (COAM) policy is proposed in this work for repairable systems which require high level of availability and safety standard by exploiting the comparative advantage of minimum expected cost-based optimal age replacement policy and maximum limiting availability-based optimal age replacement policy. The failure distribution, cost of preventive and failure maintenance and downtime of preventive and failure maintenance, which affect the age at which an operating system is replaced, were used to formulate the expected cost and limiting availability functions for repairable systems. Keywords: repairable system; failure distribution; availability; replacement maintenance Citation: International Journal of Reliability and Safety, Vol. 14, No. 1 (2020) pp. 1 - 13 PubDate: 2020-03-16T23:20:50-05:00 DOI: 10.1504/IJRS.2020.105888 Issue No:Vol. 14, No. 1 (2020)

Authors:Palaniappan Ramu, Harshal Kaushik Pages: 14 - 38 Abstract: Normal transformations are often used in reliability analysis. A Third order Polynomial Normal Transformation (TPNT) approach is used in this work. The underlying idea is to approximate the Cumulative Distribution Function (CDF) of the response in probit space using a third order polynomial while imposing monotonicity constraints. The current work proposes to apply log transformation to the ordinate of the transformed CDF and hence names the approach Log-TPNT. The log transformed data assists in improved fitting to the tails of the distribution resulting in better predictions of extreme values. Log-TPNT is demonstrated on a suite of statistical distributions covering all types of tails and analytical examples that cover aspects of high dimensions, non-linearity and system reliability. Results reveal that Log-TPNT can predict the response values corresponding to high reliability, with samples as scarce as 9. Finally, the variations associated with the response estimates are quantified using bootstrap. Keywords: reliability; cumulative distribution function; normal transformation; polynomial fit; bootstrap Citation: International Journal of Reliability and Safety, Vol. 14, No. 1 (2020) pp. 14 - 38 PubDate: 2020-03-16T23:20:50-05:00 DOI: 10.1504/IJRS.2020.105890 Issue No:Vol. 14, No. 1 (2020)

Authors:Preeti Wanti Srivastava, Manisha Pages: 39 - 57 Abstract: This paper deals with the design of optimal modified ramp-stress Accelerated Degradation Test (ADT) using the assumption that the product's degradation path follows Wiener process. In an ADT, failure occurs when the performance characteristic crosses the critical value the first time. The model parameters are estimated using method of maximum likelihood. The optimum plan consists of finding the optimum number of specimens, optimum stress change point(s), and optimum stress rates by minimising asymptotic variance of estimate of q-th quantile life at use condition, subject to the constraint that total testing or experimental cost does not exceed a pre-specified budget. A numerical example is given to demonstrate the proposed model. Sensitivity analysis is carried out to examine the robustness of the proposed plan. A comparative study is performed to highlight the merit of the proposed plan. Keywords: accelerated degradation test; modified ramp-stress; wiener process; inverse Gaussian distribution; variance optimality criterion Citation: International Journal of Reliability and Safety, Vol. 14, No. 1 (2020) pp. 39 - 57 PubDate: 2020-03-16T23:20:50-05:00 DOI: 10.1504/IJRS.2020.105900 Issue No:Vol. 14, No. 1 (2020)

Authors:Sahar Mohammad Al Mashaqbeh, Jose Eduardo Munive-Hernandez, Mohammed Khurshid Khan, Awni Al Khazaleh Pages: 58 - 84 Abstract: In a constantly changing business environment, a systematic approach is needed for risk assessment in order to allow for a more long-term strategic view. The System Dynamics (SD) modelling technique can be applied as an effective approach to understand the dynamic behaviour of a system over time. This understanding can be subsequently explicitly reflected on policies, strategic plans and operational procedures. This paper presents a SD model to assess environmental risks in power plants. The model helps to understand the long-term behaviour of the system under study. A questionnaire and focus group interviews have been conducted to understand the relationship among various risks. The SD model has been validated with two power plants in the Middle East. The developed model highlighted the impact of environmental risks on the performance of power plants. Although the SD model focuses on risk assessment in power plants, it can be easily adapted to other industry sectors. Keywords: system dynamic; non-technical risks; environmental risks; FMEA and EWGM Citation: International Journal of Reliability and Safety, Vol. 14, No. 1 (2020) pp. 58 - 84 PubDate: 2020-03-16T23:20:50-05:00 DOI: 10.1504/IJRS.2020.105902 Issue No:Vol. 14, No. 1 (2020)