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: 1.93). 07/2009; 58(2):305 - 316. DOI: 10.1109/TR.2009.2020133
Source: IEEE Xplore


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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    • "Economic assessments of PHM applications have been discussed by many authors (e.g. Banks et al., 2005; Feldman et al., 2009; Leao et al., 2007; Sandborn & Wilkinson, 2007; Scanff et al., 2007). Typical measures are lifecycle costs (LCC) or return-on-investment (ROI) estimates of the implementation costs and the potentials for cost avoidance (e.g. "
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    ABSTRACT: This paper provides a lifecycle cost-benefit analysis of the use of Prognostics and Health Management (PHM) systems in future or present commercial aircraft. The approach considers individual aircraft component's failure behavior, prognostic performance levels including prognostic errors, and condition-based maintenance (CBM) concepts. The proposed methodology is based on a discrete-event simulation for aircraft operation and maintenance and uses an optimization algorithm for the planning and scheduling of condition-based maintenance (CBM) tasks. In the study, a 150-seat short-/medium-range aircraft equipped with PHM and subject to a CBM program is analyzed. The simulation results are evaluated from an operational and economic perspective. The analysis results can support the derivation of technical and economic requirements for prognostic systems and CBM planning concepts.
    Annual Conference of the Prognostics and Health Management Society 2015, San Diego, California; 10/2015
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    • "Condition-based maintenance and predictive strategies based on cutting-edge technologies are arriving to the market and their continuous cost reduction opens wide opportunities, helping the operation and maintenance personnel to perform tasks more effectively. There are cost-effectiveness studies of different types of strategies, but it is normally difficult to measure with the existing tools the impact of predictive strategies [3] [4] [5] [6]. Fig. 1. "
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    ABSTRACT: Industries are increasingly paying attention to maintenance services, due to the relevance that maintenance is taking as a business and profit centre within the companies. Many of the improvements could be obtained using new technologies and strategies to maximize service level and to reduce the maintenance costs. Predictive maintenance (PdM) technologies, whether on-line or inspection, are key in this change as they provide supervision and control over assets condition. However, it is important to avoid risky upgrades that may have no positive effect on maintenance operations cost-benefits, and hence may serve to underestimate the potential of PdM and finally stop maintenance progress. Here is important to pay attention to several aspects of the proposed upgrades, such as the maturity of the proposed technologies. Also, the culture and organization of the company should be taken into account, and in particular is very important to understand the existing level of information management at the company, where bottlenecks at information acquisition, transmission or processing concerning reliability and maintenance operations can be expected. This paper presents a methodology that provides a continuous assessment of PdM technologies with respect to specific business scenarios. The methodology integrates existing reliability and maintenance business analysis techniques and standards, always having in mind the positive impact that may have the implementation of these technologies. A critical simulation tool is also developed in order to compare different PdM strategies. The paper finally explains how this methodology has a positive impact not only on the cost-effectiveness of maintenance processes, but also on the maintenance information available.
    12/2013; 11:193-198. DOI:10.1016/j.procir.2013.07.038
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    • "We note that this cost element is associated with the primary benefit from the application of PHM to systems, i.e., failure avoidance [56]. System failures are very undesirable due to the extremely high failure costs, and the failure avoidance can be realized by capitalizing on PHM to provide an early anticipation and warning of future failure that allows preventative maintenance to be performed at a convenient place and time [56]. "
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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]
    Journal of Mechanical Design 10/2011; 133(10):101011(15). DOI:10.1115/1.4004981] · 1.25 Impact Factor
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