A Methodology for Determining the Return on Investment Associated With Prognostics and Health Management

Dept. of Mech. Eng., Univ. of Maryland, College Park, MD
IEEE Transactions on Reliability (Impact Factor: 1.66). 07/2009; DOI: 10.1109/TR.2009.2020133
Source: IEEE Xplore

ABSTRACT Prognostics and Health Management (PHM) provides opportunities for lowering sustainment costs, improving maintenance decision-making, and providing product usage feedback into the product design and validation process. However, support for PHM is predicated on the articulation of clear business cases that quantify the expected cost and benefits of its implementation. The realization of PHM requires implementation at different levels of scale, and complexity. The maturity, robustness, and applicability of the underlying predictive algorithms impact the overall efficacy of PHM within an enterprise. The utility of PHM to inform decision-makers within tight scheduling constraints, and under different operational profiles likewise affects the cost avoidance that can be realized. This paper discusses the calculation of Return on Investment (ROI) for PHM activities, and presents a study conducted using a stochastic discrete event simulation model to determine the potential ROI offered by electronics PHM. The case study of a multifunctional display in a Boeing 737 compares the life cycle costs of a system employing unscheduled maintenance to the same system using a precursor to failure PHM approach.

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    ABSTRACT: Most engineered systems are designed with a passive and fixed design capacity and, therefore, may become unreliable in the presence of adverse events. Currently, most engi-neered systems are designed with system redundancies to ensure required system reliabil-ity under adverse events. However, a high level of system redundancy increases a system's life-cycle cost (LCC). Recently, proactive maintenance decisions have been enabled through the development of prognostics and health management (PHM) methods that detect, diagnose, and predict the effects of adverse events. Capitalizing on PHM technology at an early design stage can transform passively reliable (or vulnerable) sys-tems into adaptively reliable (or resilient) systems while considerably reducing their LCC. In this paper, we propose a resilience-driven system design (RDSD) framework with the goal of designing complex engineered systems with resilience characteristics. This design framework is composed of three hierarchical tasks: (i) the resilience alloca-tion problem (RAP) as a top-level design problem to define a resilience measure as a function of reliability and PHM efficiency in an engineering context, (ii) the system reliability-based design optimization (RBDO) as the first bottom-level design problem for the detailed design of components, and (iii) the system PHM design as the second bottom-level design problem for the detailed design of PHM units. The proposed RDSD framework is demonstrated using a simplified aircraft control actuator design problem resulting in a highly resilient actuator with optimized reliability, PHM efficiency and re-dundancy for the given parameter settings. [DOI: 10.1115/1.4004981]
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    ABSTRACT: Pushed by digital systems development and the pressure to reduce costs, in the last 40 years health monitoring (Hm) capabilities evolved from simple Built In Tests to system health prognostics, causing the development of new maintenance and operation concepts and new business models. Hm functions allow business growth by maximizing availability, optimizing the logistics, improving productivity and reducing maintenance costs and nowadays they have assumed a central role in aviation business. This role has to be captured by Hm system providers in order to fully exploit the opportunities provided by the market. To define Hm requirements is a very complex task as it necessitates considering many complex interrelated aspects such as costs reduction, concept of operations and business models. Nevertheless very little guidance exists about Hm requirements capture and this gap represents one of the main blockers to the diffusion of Hm systems. This work will then try defining a structured way to produce good Hm high level requirements. House of Quality (HoQ) has been identified as a structured but flexible methodology, which allows taking into account all the complexity of Hm and integrating business, maintenance and operational aspects. The research guideline for the design of the Hm HoQ matrices is based on the understanding of the economic value created by Hm and on the results of the total life asset cost analysis. The use of the proposed method has been demonstrated and validated through case studies where the high level Hm requirements for a metering valve and a landing gear monitoring system have been investigated. The results obtained in this phase proved that the methodology is credible as it confirmed some of the conclusions previously obtained by using traditional approaches; in addition to this new aspects are brought into consideration, making the requirements definition process more complete.
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    ABSTRACT: Purpose ‐ Prognostics and health management (PHM) can support product-service systems (PSS) contracts, especially in the case of high technology products where their condition and performance can be monitored. The purpose of this paper is to investigate how PHM can support effective execution of some PSS contracts and to set out the future research agenda for the development of an online simulation modelling framework that will further harness the interaction between PHM and PSS. Design/methodology/approach ‐ The research methodology commenced by collating facts and figures from the existing body of knowledge, from which a set of key findings is presented from both technical and business perspectives. Analysis of the key findings highlights the current state of PHM-PSS interaction, the capability of existing tools and techniques and a comprehensive analysis of PSS performances, with and without PHM. Findings ‐ Increased demand for total asset performance from the customers has been the main driver for PSS providers to adopt PHM technology. In the case of high value assets, PHM is used to capture the condition of the assets and to feed this information back to the PSS operations management which, in turn, will be used to plan a maintenance regime, spare parts provision, as well as to mitigate the dynamic behaviour which commonly occurs in PSS. Simulation modelling, driven by asset health condition, shows a considerable potential as an effective tool to control the execution of the PSS contract. In addition to the benefits from the maintenance services, the PHM-PSS interaction can increase the controllability of the PSS contract execution and allow future modifications to PSS contracts. Originality/value ‐ The value of this paper lies in the comprehensive analysis of the interaction between PHM and PSS, especially focusing on the interaction during the PSS contract execution. This paper demonstrates the strengths and weaknesses of existing research in the research domain, and highlights the opportunities for future research.
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