Prognostics for electronic equipment: an economic perspective

Hecht, H.

doi:10.1109/rams.2006.1677368

Cited by 20 publications

(11 citation statements)

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“…Banks and Merenich (2007) apply a trade space visualization software to CBA, which accounts for the cost associated with operational unavailability, a significant cost for NPPs. Hecht (2006) investigated application of PHM to electronic equipment and identified several general results that may be widely applicable, including the use of broad spectrum sensors to cover a large number of failure mechanisms with minimal hardware; targeted application of PHM sensors and algorithms to those where the difference in cost between pre-planned and unanticipated maintenance is high; and managing the cost of sensors and implementation to ensure some savings are realized if prognostic coverage is not as high as expected. Tian et al (2011a; give a methodology to economically optimize maintenance planning of multi-component systems based on condition monitoring results.…”

Section: Business Case For Phmmentioning

confidence: 99%

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Coble¹,

Ramuhalli²,

Bond³

et al. 2012

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Recent years have seen a resurgence of nuclear power worldwide, with interest in extending the operating life of the approximately 436 reactors currently in service (as of March, 2012), 61 new reactors being constructed, and as many as 162 under consideration. Renewed worldwide interest in nuclear power has been somewhat tempered by the March 2011 incident at Fukushima Dai-ichi in Japan. However, nuclear power is still considered a key element in meeting future worldwide sustainable energy, energy security, and emissions goals. Currently, three separate thrusts to safe and economical nuclear power development for energy security are being pursued in the United States: (i) longer term operation for the legacy fleet, from 40-60 and possibly 60-80 years; (ii) near-term new nuclear plants with a 60-year design life; and (iii) small modular reactors, which are expected to employ light water reactor technology at least in the medium term. Within these activities, attention is turning to enhanced methods for plant component and structural health management.The operating U.S. fleet includes 104 light water reactors. In addition, there are now (as of May 2012) four new nuclear power plants (AP-1000 plants) under construction in the United States, and two delayed plants are being completed by the Tennessee Valley Authority. There is also interest in the United States in small modular reactors (SMRs), which could be easier to match to existing grid infrastructure and which could replace aging coal fired plants. The current low price for natural gas presents a challenge to the economics of nuclear power, at least in the short term; however, some recent studies have demonstrated that nuclear generation will be competitive in the longer term (at least in some markets) when anticipated escalation in gas prices and the cost of building, operating, and maintaining gas-fired plants are considered over those same time periods.This report reviews the current state of the art of prognostics and health management (PHM) for nuclear power systems and related technology currently applied in field or under development in other technological application areas, as well as key research needs and technical gaps for increased use of PHM in nuclear power systems. The historical approach to monitoring and maintenance in nuclear power plants (NPPs), including the Maintenance Rule for active components and Aging Management Plans for passive components, are reviewed. An outline is given for the technical and economic challenges that make PHM attractive for both legacy plants through Light Water Reactor Sustainability (LWRS) and new plant designs. There is a general introduction to PHM systems for monitoring, fault detection and diagnostics, and prognostics in other, non-nuclear fields. The state of the art for health monitoring in nuclear power systems is reviewed. A discussion of related technologies that support the application of PHM systems in NPPs, including digital instrumentation and control systems, wired and wireless sensor techno...

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Section: Business Case For Phmmentioning

confidence: 99%

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Coble¹,

Ramuhalli²,

Bond³

et al. 2012

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“…(1) In order to calculate the benefit gain for the implementation of battery prognostics, the maintenance savings was calculated for maintenance conducted with a prognostic capability and also without a prognostic capability. This parameter was computed using a methodology developed by Hebert Hecht, which multiplies the cost avoidance per correct prognostic event times the number of correct prognostic events within the time horizon [6].…”

Section: Battery Prognostics Cost Benefit Analysismentioning

confidence: 99%

“…The cost avoidance is calculated using the time reduction factor from the implementation of prognostics (equation 2) multiplied by the mean time to restore (MTTR) times the labor rate as prescribed by Hecht [6].…”

Section: Roi = (Benefit Gain -Technology Cost)/technology Costmentioning

confidence: 99%

“…ground vehicle, aircraft, ship) is operationally unavailable, so a more useful parameter to use instead of labor rate would be the cost of operational unavailability. As Hecht notes in his paper [6], the challenge is calculating this variable, which is difficult to quantify in terms of dollars and is greatly dependant upon the platform type (i.e. M1A2 Abrams, HMMWV), mission (i.e.…”

Section: Roi = (Benefit Gain -Technology Cost)/technology Costmentioning

confidence: 99%

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Cost Benefit Analysis for Asset Health Management Technology

Banks

Merenich

2007

2007 Proceedings - Annual Reliability and Maintainability Sympsoium

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Individuals who work in the field of Prognostics and Health Management (PHM) technology have come to understand that PHM can provide the ability to effectively manage the operation, maintenance and logistic support of individual assets or groups of assets through the availability of regularly updated and detailed health information. Naturally, prospective customers of PHM technology ask, 'How will the implementation of PHM benefit my organization?' Typically, the response by individuals in the field is, 'Anecdotal evidence indicates that PHM decreases maintenance costs, increases operational availability and improves safety'. This information helps the prospective customer understand the practical benefits of the technology but that customer stills needs more information to justify their investment into the technology. The information that is most useful to the customer is a calculated return on investment (ROI) figure for their particular asset that provides financial assessment of the benefit of the investment.The purpose of this paper is to show the advantages of using trade space analysis software to conduct a cost benefit analysis (CBA) for the implementation of PHM technology. The trade space software was designed to graphically display the results of multi-variant problems in a 3-D space made up of discrete solutions. This format provides the ability to evaluate many variables simultaneously, which facilitates data analysis and the ability to detect trends and complex relationships between multiple parameters. Using this tool, we can examine the correlations between several PHM variables including: technology cost, component failure rate, and logistic delay time and their effect on ROI. A CBA model was developed for estimating the benefits of implementing battery prognostics on military ground combat vehicles which was then analyzed using the trade space tool.

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“…These efforts have produced Return-on-Investment (ROI) estimates of the costs of PHM implementation and the potential for cost avoidance, [5,6]. However, these models quantify neither the reduction in life cycle costs nor the increase in operational reliability or availability gained from PHM and lack the necessary generality to evaluate PHM incorporation for application-specific helicopter avionics.…”

Section: Introductionmentioning

confidence: 99%

Life cycle cost impact of using prognostic health management (PHM) for helicopter avionics

Scanff¹,

Feldman

Ghelam³

et al. 2007

Microelectronics Reliability

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-Case studies were conducted using a stochastic model to predict the life cycle cost impact associated with the application of Prognostic Health Management (PHM) to helicopter avionics. The life cycle costs of systems that assumed unscheduled maintenance and fixed-interval scheduled maintenance were compared to the costs of precursor-to-failure and life consumption monitoring PHM approaches, and the optimal safety margins and prognostic distances were determined.

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Prognostics for electronic equipment: an economic perspective

Cited by 20 publications

References 0 publications

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Prognostics and Health Management in Nuclear Power Plants: A Review of Technologies and Applications

Cost Benefit Analysis for Asset Health Management Technology

Life cycle cost impact of using prognostic health management (PHM) for helicopter avionics

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