Electronic reliability prediction: a study over 25 years

This thesis describes research work that the author has undertaken and published in the field of electronic reliability prediction techniques over the last 25 years. Reliability prediction is an important area since it has been part of the backbone of reliability engineering in one form or another for over fifty years. The author has over 45 publications that are within the area of reliability prediction and 13 of these have been selected for review in this thesis. In order to show how the author’s work has contributed to the field of reliability prediction this document also contains information on the history of reliability prediction. This allows the author’s work to be placed in context with general developments in the field. The contributions to knowledge and innovations that have been made in reliability prediction include the development of statistical models for lifetime prediction using early life data (i.e. prognostics); the use of non-constant failure rates for reliability prediction; the use of neural networks for reliability prediction, the use of artificial intelligence systems to support reliability engineers’ decision making; the use of a holistic approach to reliability; the use of complex discrete events simulation to model equipment availability; demonstration of the weaknesses of classical reliability prediction; an understanding of the basic behaviour of no fault founds; the development of a parametric drift model; identification of the use of a reliability database to improve the reliability of systems; and an understanding of the issues that surround the use of new reliability metrics in the aerospace industry

State-of-the-art in managing reliability in mega railway projects.:A systematic literature review

Mega Railway Projects (MRPs) are expensive and account for an increasing per-centage of many a nation’s annual infrastructure expenditure. These MRPs fre-quently exceed their budget and schedule. The challenge of achieving reliability or availability targets stands out as a contributing factor to these overruns. A robust and targeted Reliability, Availability, and Maintainability (RAM) process, which covers systems and subsystems that comprise the railway, that is imbedded in the project from the outset and that is managed throughout the life cycle of the project, is crucial for success. However, a RAM process for MRPs is not readily available. While BS EN 50126-11sets out the required RAM related tasks there is no guidance on how these tasks are to be undertaken or managed. This omission is likely to increase the challenge faced by RAM or Systems engineers as they put forth their case for ring-fenced funds and labour at the outset of an MRP. It is therefore important that RAM on an MRP is reviewed so that next steps in devel-oping robust RAM process plan guidelines can be determined. The authors of this paper discuss why RAM is undertaken and the conceptualisation of RAM along with its fundamental features. Its application on railways focusing on RAM techni-ques and BS EN 50126-1 is outlined. A Systematic Literature Review (SLR) is under-taken to show the state-of-the-art by using a meta and content analysis within the context of railway systems, RAM techniques, RAM standards and Reliability levels. Furthermore, a set of Derived RAM requirements (DRR) based on BS EN 50126-1 are derived to determine the critical areas of RAM and are thus recommended for further development by researchers or RAM practitioner

State of the art in simulation-based optimisation for maintenance systems

Recently, more attention has been directed towards improving and optimising maintenance in manufacturing systems using simulation. This paper aims to report the state of the art in simulation-based optimisation of maintenance by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. The authors investigate application areas and published real case studies as well as researched maintenance strategies and policies. Much of the research in this area is focusing on preventive maintenance and optimising preventive maintenance frequency that will lead to the minimum cost. Discrete event simulation was the most reported technique to model maintenance systems whereas modern optimisation methods such as Genetic Algorithms was the most reported optimisation method in the literature. On this basis, the paper identifies the current gaps and discusses future prospects. Further research can be done to develop a framework that guides the experimenting process with different maintenance strategies and policies. More real case studies can be conducted on multi-objective optimisation and condition based maintenance especially in a production context

Modelling People's Behaviour using Discrete-Event Simulation:A Review

Purpose The purpose of this paper is to provide a contribution to the area of behavioural operations management (OM) by identifying key challenges in the use of discrete-event simulation (DES) to model people’s behaviour in OM. Design/methodology/approach A systematic literature review method is undertaken in order to assess the nature and scale of all publications relevant to the topic of modelling people’s behaviour with DES in OM within the period 2005-2017. Findings The publications identified by the literature review reveal key challenges to be addressed when aiming to increase the use of DES to model people’s behaviour. The review also finds a variety of strategies in use to model people’s behaviour using DES in OM applications. Research limitations/implications A systematic literature review method is undertaken in order to include all publications relevant to the topic of modelling people’s behaviour with DES in the OM domain but some articles may not have been captured. Originality/value The literature review provides a resource in terms of identifying exemplars of the variety of methods used to model people’s behaviour using DES in OM. The study indicates key challenges for increasing the use of DES in this area and builds on current DES development methodologies by presenting a methodology for modelling people’s behaviour in OM

Electronic reliability prediction : a study over 25 years

This thesis describes research work that the author has undertaken and published in the field of electronic reliability prediction techniques over the last 25 years. Reliability prediction is an important area since it has been part of the backbone of reliability engineering in one form or another for over fifty years. The author has over 45 publications that are within the area of reliability prediction and 13 of these have been selected for review in this thesis. In order to show how the author’s work has contributed to the field of reliability prediction this document also contains information on the history of reliability prediction. This allows the author’s work to be placed in context with general developments in the field. The contributions to knowledge and innovations that have been made in reliability prediction include the development of statistical models for lifetime prediction using early life data (i.e. prognostics); the use of non-constant failure rates for reliability prediction; the use of neural networks for reliability prediction, the use of artificial intelligence systems to support reliability engineers’ decision making; the use of a holistic approach to reliability; the use of complex discrete events simulation to model equipment availability; demonstration of the weaknesses of classical reliability prediction; an understanding of the basic behaviour of no fault founds; the development of a parametric drift model; identification of the use of a reliability database to improve the reliability of systems; and an understanding of the issues that surround the use of new reliability metrics in the aerospace industry.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

How is capability assessment related to risk assessment? Evaluating existing research and current application from a design science perspective

Several countries use capability assessments as a part of their efforts to manage risk. However, it is unclear how such assessments are connected to other risk management activities, e.g. risk assessment. Therefore, the aim of the present paper is to present a study of how capability assessment is related to risk assessment. Capability assessment methods were identified through a scoping study and the Swedish capability assessment method was investigated through interviews with Swedish public actors and analysis of legislative documents. The data was analysed using a design science perspective. The results of the analysis show that the purposes presented for some capability assessment methods are the same or similar to purposes common to risk assessment methods, and the actual form of some of the methods is similar to existing risk assessment methods. Nevertheless, the relationship between capability assessment and risk assessment is unclear. We conclude that if capability assessments are going to continue to be an important part of risk management activities more research is needed to better establish the relationship between risk assessment and capability assessment