Picture of rolled up £5 note

Open Access research that shapes economic thinking...

Strathprints makes available scholarly Open Access content by the Fraser of Allander Institute (FAI), a leading independent economic research unit focused on the Scottish economy and based within the Department of Economics. The FAI focuses on research exploring economics and its role within sustainable growth policy, fiscal analysis, energy and climate change, labour market trends, inclusive growth and wellbeing.

The open content by FAI made available by Strathprints also includes an archive of over 40 years of papers and commentaries published in the Fraser of Allander Economic Commentary, formerly known as the Quarterly Economic Commentary. Founded in 1975, "the Commentary" is the leading publication on the Scottish economy and offers authoritative and independent analysis of the key issues of the day.

Explore Open Access research by FAI or the Department of Economics - or read papers from the Commentary archive [1975-2006] and [2007-2018]. Or explore all of Strathclyde's Open Access research...

Towards a methodology for design of prognostic systems

Aizpurua, Jose Ignacio and Catterson, Victoria M. (2015) Towards a methodology for design of prognostic systems. In: Annual Conference of the Prognostics and Health Management Society 2015, 2015-10-18 - 2015-10-24.

[img]
Preview
Text (Aizpurua-Catterson-PHMS2015-towards-methodology-design-prognostic-systems)
Aizpurua_Catterson_PHMS2015_towards_methodology_design_prognostic_systems.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (276kB) | Preview

Abstract

An effective implementation of prognostic technology can reduce costs and increase availability of assets. As a result of the rapidly growing interest in prognostics, researchers have independently developed a number of applications for asset-specific modelling and prediction. Consequently, there is some inconsistency in the understanding of key concepts for designing prognostic systems. This further complicates the already-challenging design of new prognostic systems. In order to progress from application-specific solutions towards structured and efficient prognostic implementations, the development of a comprehensive and pragmatic methodology is essential. Prognostic algorithm selection is a key activity to achieve consistency throughout the design process. In this paper we present a design decision framework which guides the designer towards a prognostic algorithm through a cause-effect flowchart. Failure modes, application characteristics, and qualitative and quantitative metrics are used to determine an appropriate approach for the stated problem. The application of the methodology can reduce the time and effort required to develop a prognostic system, ensure that all the possible design options have been considered, and provide a means to compare different prognostic algorithms consistently. The framework has been applied to different prognostic problems within the power industry to illuminate its effectiveness. Case studies are presented to show how the framework guides designers through the choice of prognostic algorithm according to system requirements. The results demonstrate the applicability of the methodology to the design of prognostic systems which consistently meet the established requirements.