`Maintenance Conference
`Maintaining Reliable Electric Generation
`
`1004660
`
`Proceedings, August 2001
`
`EPRI Project Managers
`M. Perakis
`M. DeCoster
`
`EPRI • 3412 Hillview Avenue, Palo Alto, California 94304 • PO Box 10412, Palo Alto, California 94303 • USA
`800.313.3774 • 650.855.2121 • askepri@epri.com • www.epri.com
`
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`DISCLAIMER OF WARRANTIES AND LIMITATION OF LIABILITIES
`
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`Copyright © 2001 Electric Power Research Institute, Inc. All rights reserved.
`
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`CITATIONS
`
`This report was prepared by
`
`Portal Solutions
`279 Sims Road
`Santa Cruz, CA 95060
`
`Principal Investigator
`Lew Rubin
`
`This report describes research sponsored by EPRI.
`
`The report is a corporate document that should be cited in the literature in the following manner:
`
`2001 EPRI International Maintenance Conference: Maintaining Reliable Electric Generation,
`EPRI, Palo Alto, CA: 2001. 1004660.
`
`
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`REPORT SUMMARY
`
`
`EPRI’s Energy Conversion Division organized and presented a three-day conference on fossil
`and nuclear generation plant maintenance during August 2001, in Houston, Texas. This CD
`presents the proceedings of that conference.
`
`Background
`Maintenance of generation assets is a key challenge for the electricity generation industry as it
`moves to a future of competition, changing asset ownership, and new business goals. Modern
`maintenance techniques and technologies—as well as business management processes
`supporting the maintenance function—will be increasingly important to the generation fleet. This
`will be especially true as competition grows and as the drive to improve reliability and
`performance with fewer resources intensifies. Optimizing maintenance practices and
`coordinating with plant and system operations will be critical to (1) ensure reliability when it is
`most needed and most profitable, (2) save costs and increase performance, (3) effectively deal
`with the realities of aging equipment and work-force, and (4) balance reliability and availability
`when factoring risk into the maintenance function.
`
`Objective
`To explore ways of optimizing maintenance practices in fossil and nuclear generation plants.
`
`Approach
`EPRI’s Energy Conversion Division (ECD) targets organized the conference around a broad
`range of maintenance-related issues. Venues for presentations included strategic and technical
`sessions, panel discussions, and special topic workshops. ECD designed the conference for a
`wide range of power generation professionals, including engineering, operations, maintenance
`and management personnel, equipment manufacturers, vendors, architect- engineers, and
`consultants.
`
`Key Points
`The conference focused primarily on fossil and nuclear generating assets, but also included
`topics applicable to other assets. Specific sessions included the following:
`• Keynote Session: Emerging Pressures of the New Marketplace
`• Panel Discussion: Strategic and Tactical Guidance for Power Plant Maintenance Practices
`• Plenary Sessions: Predictive and Preventive Maintenance Approaches
`Focus on Plant and Component Reliability
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`Innovations in Component Maintenance
`
`Help for Predictive Maintenance Processes
`• Parallel Sessions: Materials Issues and Innovations
`Innovative Maintenance and Repair Practices
`
`Diagnostic Techniques
`
`Innovative Predictive Methods
`• Plenary Session: Tales from the Field—Stories of Successful Innovation
`
`EPRI Perspective
`This conference is part of EPRI’s efforts under Target 69, Plant Maintenance Optimization
`(PMO). The PMO mission is to lead the industry by developing and demonstrating products and
`services that will improve use of power plant maintenance resources and increase profitability
`for generation businesses. The previous EPRI International Maintenance Conference was held in
`1999 at Atlanta.
`
`Keywords
`Fossil
`Nuclear
`Power
`Plant
`Maintenance
`
`
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`SESSIONS AND PAPERS
`
`2001 EPRI International Maintenance Conference
`
`Maintaining Reliable Electric Generation
`
`1. Keynote Session: Emerging Pressures of the New Marketplace
`
`Welcome by David Tees, Senior Vice President, Reliant Energy
`
`Philip Curtis, President, EPRISolutions
`
`Vicki Bier, University of Wisconsin
`
`Glen Schinzel, South Texas Project
`
`Robert McQueen, Organizational Learning Center
`
`2. Panel Discussion: Strategic and Tactical Guidance for Power Plant Maintenance
`Practices
`
` Panelists: Keynote session speakers
`
`3. Plenary Session: Predictive and Preventive Maintenance Approaches
`
`Distributed Knowledge-Based Maintenance Assistance for Nuclear Power Plant
`Components
`Benoit Ricard, Electricite de France
`
`The EPRI Preventive Maintenance Database
`David Worledge, Applied Resource Management
`
`Manufacturing’s High-Tech Revolution
`Noah Bethel, PdMA Corporation
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`Sustain Reduced Maintenance Costs with Management Processes and Practices
`Frank Frisina, New York Power Authority
`
`Precision Lubrication for the Power Generation Industry
`Drew Troyer, Noria Corporation
`
`4. Plenary Session: Focus on Plant and Component Reliability
`
`Managing Gas Turbine Maintenance Risks
`Jason Makansi, Pearl Street, Inc.
`
`Asset Reliability for the Deregulated Electric Power Economy
`Robert Matusheski, Meridium, Inc.
`
`Boiler Reliability Optimization
`Pat Abbott, EPRI
`
`Applying RCM to Optimize Maintenance
`Jim August, Operations Management Engineering, Inc.
`
`5. Plenary Session: Innovations in Component Maintenance
`
`Boiler Automated Welding System
`Charles Giancola, Dynegy Midwest Generation, Inc.
`
`
`
`Automatic Motor Winding Dry-Out Machine
`Jerry Honeycutt, TVA
`
`Condition-Based Maintenance of Reactor Coolant Pumps
`R. Chevalier, Electricite de France
`
`Reliable Plant Performance: Labor Solutions for the 21st Century
`David Joiner, Welding Services
`
`6. Plenary Session: Help for Predictive Maintenance Processes
`
`Field Experience of a Novel Monitoring System for Improved Control of Power Plant
`Steam-Water Chemistry
`Jose Bueno, Norcontrol Soluziona/Union Fenosa (Spain)
`
`EMI Diagnostics Provides Condition Based Information for Triggered Maintenance in the
`Nuclear Environment
`James Timperley, American Electric Power
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`PlantView – An Automated Tool for Maintenance Optimization
`Rich Colsher, EPRI M&D Center
`
`7A. Parallel Session: Materials Issues and Innovations
`
`A New Stainless Steel for Erosion-Corrosion Control in Power Plants
`William Schumacher, AK Steel Research
`
`Deep Cryogenic Tempering
`Michael Stickney, 300 Below, Inc.
`
`Fitness for Service Program and Local Thin Area Repair Component for Pressure
`Retaining Items
`Paul Manzon, Asta Engineering
`
`7B. Parallel Session: Innovative Maintenance and Repair Practices
`
`Cost Effective Repairs of a Loop Stop Isolation Valve: A Unique Approach
`Brian Schumel, PCI Energy Services
`
`Control of Suspended Sediment Concentration of Intake Channel at Yongkwang Nuclear
`Power Plant, Korea
`Hyoseob Kim, Kookmin University (Korea)
`
`Troubleshooting a Centrifugal Charging Pump – A Rotordynamics Analysis Approach
`Mammar Maghraoui, Duke Engineering
`
`8A. Parallel Session: Diagnostic Techniques
`
`Infrared Thermography – Past, Present and Future
`Robert Hammaker, EPRISolutions
`
`Ultrasonic Test Technique on Insulation Hose of Generator
`Hideo Tanahashi, Hitachi Ltd. (Japan)
`
` Case Studies in Maintaining Piping Reliability by Economical Predictive Methods for
`Inspection Planning
`Peter Jackson, Tetra Engineering
`
`8B. Parallel Session: Innovative Predictive Methods
`
`Development of Expert System with Bayesian Networks for Application in Nuclear Power
`Plants
`Bilge Yildiz, MIT
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`Fuzzy Diagnosis System to Generators
`Wang Shizheng, Shanghai Second Polytechnic University (China)
`
`Gaining Strategic Leverage through Planning & Scheduling
`Kirk Samsel, EPRISolutions
`
`9. Plenary Session: Tales from the Field – Stories of Successful Innovation
`
`Inspection Data Interactive Processing System
`Paula Cortizo, Norcontrol Soluziona/Union Fenosa (Spain)
`
`Overhauling the Plant Maintenance Process
`Dennis Watson, Hoosier Energy R.E.C.
`
`Exelon Nuclear Proactive Maintenance Program and Best Practices
`Steve Maloney, Exelon Nuclear Corp.
`
`Reliability-Centered Maintenance
`G.P. Singh, National Thermal Power Corporation (India)
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`PREVENTIVE MAINTENANCE STRATEGIES FOR DEREGULATION
`
`Vicki M. Bier
`University of Wisconsin-Madison
`1513 University Avenue
`Madison, WI 53706
`
`J. David Glyer
`Laurits R. Christensen Associates, Inc.
`4610 University Avenue, Suite 700
`Madison, WI 53705
`
`Abstract
`
`Companies do not emerge into a competitive environment knowing immediately how to compete
`safely and effectively, and can therefore inadvertently make excessive cutbacks in preventive
`maintenance. In particular, some electric utilities have suffered adverse consequences in recent
`years because of such cutbacks. Companies interested in re-optimizing their preventive
`maintenance programs should eliminate activities that have little value added, look for ways to
`accomplish their current maintenance activities at lower cost, and consider alternative activities
`to meet the same goals. Moreover, successful re-optimization requires increased economic
`sophistication. In a competitive market, where electricity prices can vary by more than two
`orders of magnitude, optimal economic performance requires moving beyond simple
`engineering-oriented figures of merit such as capacity factor. Better economic decision-making
`tools can improve plant economic performance while maintaining safety and reliability.
`
`1. Possible Pitfalls in Preventive Maintenance Strategies
`
`This paper discusses how deregulation affects preventive maintenance strategies. As noted by
`Carroll et al. (1998), “In the short run, a plant can always cut preventive maintenance; the
`problems emerge later because preventive maintenance is an investment in the future.” In other
`words, “Sparse allocation of resources to maintenance is not a rational strategy for the
`organization as a whole,” but can nonetheless occur.
`
`Under economic regulation, most preventive maintenance costs were recoverable in regulated
`rates. However, in a deregulated environment, changes in costs go directly to the bottom line.
`Therefore, deregulation increases the incentive to cut preventive maintenance costs, at the same
`time as it increases the potential impact of inadequate preventive maintenance programs. This
`makes it more important to get the tradeoffs right. For example, companies can (perhaps
`inadvertently) adopt policies that lead to cost savings in the short run, but result in problems
`later. Carroll et al. note, “Preventive maintenance…seems to be a low priority in the face of
`immediate demands to keep the machines running at lower cost,” partly because “the ultimate
`effects of deferred maintenance can be denied, ignored, or blamed on others.”
`
`The experiences at the Millstone nuclear power plant in the late 1990’s show that cuts can in fact
`go too far. As the General Accounting Office (1998) noted about Millstone, “The need to trim
`
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`costs in the face of future competition resulted in managers’ choosing to defer maintenance and
`allow backlogs of corrective actions to grow, eventually creating a situation that led to a
`shutdown and several hundred million dollars worth of repairs.” The shutdown also resulted to
`opportunity costs of lost sales during the period of the shutdown. One reason that such problems
`can arise is because the feedback for cutbacks is delayed and ambiguous, so plants that do not
`heed early warning signs could cut too far.
`
`Some plants are turning to reliability-centered maintenance (RCM) to avoid such problems.
`However, appropriate use of RCM creates increased demands for testing (e.g., non-destructive
`evaluation), data collection, and analysis. The lack of such data collection and analysis appears
`to have been a problem in the electricity distribution outages in Chicago in summer 1999. In
`reviewing those outages, the Department of Energy Power Outage Study Team (2000) noted that
`“Many fixed, periodic, substation maintenance programs had been scaled back or discontinued in
`transition to a ‘reliability-centered maintenance’ philosophy. However, the collection of data
`and measurements necessary for successful reliability-centered maintenance was not fully in
`place.” As a result, “the ability to predict possible component failures from the inspections that
`were performed and data that were collected was limited.”
`
`Another area in which companies can inadvertently make excessive cuts is maintenance of
`spares. Under economic regulation, spares might have seemed like an obvious place for
`cutbacks when cuts were needed. After all, spares obviously cannot be safety-critical (since they
`are not even installed); moreover, they are not used in routine operation, and some spares may
`not have been used at all in many years. This combination of factors makes spares appear to be
`an easy target for cutbacks. However, this is actually an old way of thinking that is no longer
`appropriate in a deregulated environment, where generating companies can no longer expect
`ratepayers to cover the cost of outages, even if they do not result from “imprudence” per se. The
`transformer fire at the Hope Creek nuclear power plant on May 24, 2000, showed that spares
`maintenance could be critical to managing outage duration. In that instance, the spare
`transformer and spare oil pumps had not been in working order at the time of the fire, and as a
`result ended up being on the critical path in what became a 28-day forced outage that lasted into
`the peak summer season.
`
`2. New Ways of Thinking about Preventive Maintenance
`
`Airline industry experience shows that companies can cut costs safely. A study of engine
`maintenance after deregulation by Kennett (1993) found “a significant increase in the number of
`engine hours between major overhauls following deregulation,” but noted, “engine ‘failures’
`…have not increased as a result of deregulation.” Kennett’s findings suggest that airlines may
`have been doing more maintenance than necessary prior to deregulation, and then optimized their
`maintenance programs after deregulation—“perhaps by improving the quality of service
`performed but paying less attention to minor problems between scheduled shop visits.”
`
`This is consistent with experiences after deregulation of the United Kingdom (U.K.) nuclear
`power industry. A recent study of the effects of economic deregulation on nuclear power safety
`(Bier et al., in press; see also Bier et al., 2001) found that in the U.K., electricity deregulation
`appears to have increased the emphasis on reliability and regulatory compliance (despite some
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`problems associated with extensive downsizing). In an interview summarized in Bier et al. (in
`press), a power plant site manager in the U.K. noted that managers now find themselves telling
`the staff not to rush: “Don’t make mistakes which can lead to a non-compliance with the
`regulations.” He emphasized, “We’d rather have the job done slowly but right.”
`
`These observations suggest several strategies for allocating resources to preventive maintenance:
`
`1) Identify those maintenance activities that are truly cost-effective and/or risk-significant.
`Cutbacks can then be considered in those activities that provide little real value added,
`and are done mainly because “that is the way we have always done maintenance around
`here.” For example, South Texas Project managers estimate that they will save roughly
`$1 million annually by “optimizing maintenance frequencies, [reevaluating] how detailed
`post-maintenance testing needs to be and reconsidering how detailed plant documentation
`packages need to be” on components with little or no risk significance (Stellfox, 1999).
`Those activities that contribute significantly to productivity may actually justify increased
`levels of resources after deregulation.
`
`2) Seek ways to accomplish needed maintenance at lower cost. For example, companies
`may seek competitive bids for activities that were formerly contracted to the original
`equipment manufacturer. With the economies of scale associated with consolidation,
`companies may also find it cost-effective to have their own staff perform work that had
`formerly been done by contractors—for example, to permit greater management control.
`
`3) Seek alternative ways to achieve the same goals. For example, careful use of non-
`destructive evaluation may make it possible to postpone or even eliminate some formerly
`routine overhauls.
`
`3. Conclusion
`
`Electricity deregulation changes the incentives for preventive maintenance at power plants, and
`increases the importance o getting the tradeoffs right. Therefore, generating companies will need
`more sophisticated measures and tools to meet this challenge. For example, generating
`companies used to focus on engineering-oriented figures of merit such as capacity factor and
`forced outage rate. Under economic regulation, annual average capacity factor made sense as a
`performance measure for use by electric utilities, especially since some regulators used it as a
`performance benchmark. However, in a competitive market, electricity prices can vary by more
`than two orders of magnitude between high-cost and low-cost hours, so achieving good annual
`average capacity factors is no longer sufficient. Instead, the timing of when a plant is available
`also becomes critical to its economic performance.
`
`Under these situations, reliability is more important to profitability than it used to be. Thus,
`avoiding a day of forced outage (which could occur at a costly time of year) may be worth
`several days of planned outage at a low-cost time of year. In fact, as future electricity markets
`evolve, forced outage rates may have yet another direct financial consequence for utilities, since
`they may affect the cost of required reserves to cover possible forced outages (equivalent to an
`insurance premium).
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`Moreover, controlling the duration and timing of forced outages is as important as controlling
`their frequency. One way to control the duration of forced outages is through effective spares
`maintenance. This obviously does not mean that an organization should not cut maintenance of
`spare parts—only that it should not do so blindly, under the erroneous assumption that spares
`maintenance is unimportant. Rather, optimal spares maintenance must carefully weigh the
`savings from any cutbacks against the possibility that failure to maintain spare parts in working
`condition could extend the duration of a forced outage. In this context, arrangements with other
`plants or vendors (to ensure that spares will be available on short notice) can provide one
`mechanism for reducing spares maintenance with diminished downside risk.
`
`The idea of controlling the timing of forced outages at first would appear to be a contradiction in
`terms. After all, if an outage is truly forced, how can a plant be expected to control the timing of
`that outage? However, the timing of forced outages can in fact be influenced by paying careful
`attention to the circumstances that can cause such outages—for example, by limiting on-line
`maintenance to times when outages would not be excessively costly.
`
`Optimizing financial performance rather than conventional engineering figures of merit requires
`increased economic sophistication. Moreover, with the advent of electricity deregulation,
`responsibility for making economic decisions is now being pushed down to lower and lower
`levels within power plant management structures and organizations. The types of decisions
`where economic considerations are important range from relatively long-term decisions (such as
`deciding which work to include in a particular outage), to short-term decisions (such as whether
`to call in a maintenance crew on overtime versus waiting until the next weekday), to general
`decision rules (such as whether and when to perform on-line maintenance). While the specifics
`of these decisions are often unique, certain categories of decisions arise over and over.
`Therefore, it is important for power plants to develop better tools for economic analysis of such
`situations. Better economic decision-making can result in plant performance that is more
`consistent with corporate financial goals and policies, while still incorporating the technical
`knowledge of plant decision-makers.
`
`4. References
`
`Vicki Bier, James Joosten, David Glyer, Jennifer Tracey, and Michael Welsh (in press), Effects
`of Deregulation on Safety: Implications Drawn from the Aviation, Rail, and United Kingdom
`Nuclear Power Industries, Washington, D.C., U.S. Nuclear Regulatory Commission
`
`Vicki Bier, James Joosten, David Glyer, Jennifer Tracey, and Michael Welsh (2001),
`”Deregulation and Nuclear Power Safety: What Can We Learn from Other Industries?”,
`Electricity Journal, May, pp. 49-60
`
`John S. Carroll, John Sterman, and Alfred A. Marcus (1998), “Playing the Maintenance Game:
`How Mental Models Drive Organizational Decisions,” in Debating Rationality—Nonrational
`Aspects of Organizational Decision Making (Jennifer J. Halpern and Robert N. Stern, editors),
`Ithaca, New York, ILR Press
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`General Accounting Office (1998), Nuclear Regulatory Commission—Preventing Problem
`Plants Requires More Effective Action by NRC, Washington, D.C.
`
`D. Mark Kennet (1993), “Did Deregulation Affect Aircraft Engine Maintenance? An Empirical
`Policy Analysis,” RAND Journal of Economics, Vol. 24, No. 4, pp. 542-558
`
`Power Outage Study Team (2000), Report of the U.S. Department of Energy’s Power Outage
`Study Team—Findings from the Summer of 1999, Washington, D.C., U.S. Department of Energy,
`http://tis.eh.doe.gov/post/postfinal.pdf
`
`David Stellfox (1999), “STP Finds Risk Ranking Components Pays, Even Before NRC
`Changes,” Inside N.R.C., December 20, pp. 3-4
`
`Author Information
`
`Vicki M. Bier, Director
`Center for Human Performance and Risk Analysis
`University of Wisconsin-Madison
`Email address: bier@engr.wisc.edu
`Web address: http://www.engr.wisc.edu/centers/chpra/
`
`Vicki Bier is an Associate Professor in the Departments of Industrial Engineering and
`Engineering Physics at the University of Wisconsin-Madison, where she is the Director of the
`Center for Human Performance and Risk Analysis. She has extensive experience as a consultant
`in probabilistic risk analysis for nuclear power plants. She received a Ph.D. in Operations
`Research from the Massachusetts Institute of Technology in 1983.
`
`J. David Glyer, Senior Consultant
`Laurits R. Christensen Associates, Inc.
`Email address: daveg@lrca.com
`Web address: http://www.lrca.com
`
`David Glyer is a Senior Economist at Laurits R. Christensen Associates, an economic consulting
`company specializing in creative solutions to business challenges and high-caliber economic
`analysis. He specializes in applied microeconomics, program design, and statistics. He is an
`expert on competitive pricing in the electric utility industry. He has held faculty appointments at
`Oregon State University and the University of Colorado-Denver, and received a Ph.D. in
`Economics from the Claremont Graduate School in 1990.
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`Utility Maintenance Applications
`Using Risk-Informed Insights
`
`2001 EPRI International Maintenance Conference
`Houston, Texas
`August 14-16, 2001
`
`Mr. Glen Schinzel
`Project Manager, Risk Implementation
`South Texas Project Nuclear Operating Company
`P.O. Box 289, Wadsworth, Texas USA 77483
`
`361-972-7854 361-972-8298 (fax) geschinzel@stpegs.com
`
`South Texas Project (STP) Overview
`
`• South Texas Project is a two unit, four-loop Westinghouse
`PWR rated at 1250MW each
`
`-Initial power generated-Unit 1 in 1988, Unit 2 in 1989
`-Each unit is physically separate-few common systems
`-Reactor package includes a rapid-refueling design
`-Main Turbine Deck is open to the atmosphere
`
`(cid:127)
`
`South Texas Project is located about 85 miles southwest of
`Houston, Texas - located near the Gulf of Mexico
`
`(cid:127) South Texas Project Nuclear Operating Company is co-owned by
`four power companies
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`Why a Risk-Informed Approach?
`
`A risk-informed approach to safety-related maintenance activities:
`(cid:127) Allows a documented basis for identifying what components are
`important (safety significant) and what components are not important
`(non-safety significant)
`
`(cid:127) Once identified, maintenance resources can be focused on the safety
`significant components
`
`(cid:127) This results in:
`– Reduced burden for the power plant
`
`– Reduced burden for the regulator
`
`– Improved overall safety
`
`(cid:127) This approach does requires a change in the ‘nuclear culture’
`
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`Importance Determination Flowchart
`
`PRA RISK RANKING
`High
`Medium
`Low
`
`STATION & INDUSTRY PERFORMANCE
`
`EXPERT PANEL
`Reviews W. G. performance data analyses
`Considers risk ranking
`Injects deterministic knowledge/insight
`
`DOCUMENTED EXPERT
`PANEL DECISIONS
`
`ONGOING FEEDBACK
`
`WORKING GROUP
`Analyzes performance data
`Considers risk ranking
`Injects deterministic knowledge / insight
`Develops recommendations regarding
`levels of programmatic control and
`activity oversight
`
`Documented recommendations
`& rationale to Expert Panel
`
`Program controls are
`established or modified
`
`Levels of overview are
`established or modified
`
`5
`
`Importance Determination Controls
`
`(cid:127) Decision-Making process is made up of two groups - a Working Group
`and an Expert Panel
`– both groups use experienced, qualified personnel
`– both groups use personnel from maintenance, operations,
`engineering, licensing, and quality organizations
`
`(cid:127) Procedures govern the component importance determination process
`
`(cid:127) Through this process, components are placed into one of four
`categories:
`– HSS - high safety significant
`– MSS - medium safety significant
`– LSS - low safety significant
`– NRS - not risk significant
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`Importance Determination Approach at STP
`
`(cid:127)
`
`Importance Determination Process for components consists of
`probabilistic and deterministic insights:
`– PRA
`(cid:127) PRA models about 1200 components for Unit 1
`(cid:127) PRA categorization based on importance measures of Fussel-
`Vesely (FV) and Risk Achievement Worth (RAW)
`– Deterministic
`(cid:127) Identify functions performed by the system
`(cid:127) Determine risk importance of each function using five ‘critical
`questions’ as a guide
`(cid:127) Identify functions supported by each component
`(cid:127) Determine resulting risk importance of each component
`(cid:127) Overall importance based on the higher of PRA and deterministic risk
`(cid:127) Working Group identifies component risk; Expert Panel independently
`reviews and approves
`
`Categorization Results
`
`(cid:127) 29 systems (43,688 components) categorized to date
`
`(cid:127) Components have been categorized as follows:
`–HSS -
`3%
`–MSS -
`7%
`–LSS - 15%
`–NRS - 75%
`
`(cid:127) HSS/MSS components are safety significant (important)
`
`(cid:127) LSS/NRS components are not-safety-significant (least important)
`
`2-4
`
`CiM Ex. 1004 Page 20
`
`
`
`Results Broken Down Further
`
`RISC - 1
`
`Safety-Related,
`Safety Significant
`
`4,104
`(9.4%)
`
`RISC - 3
`
`RISC - 2
`
`Non-Safety Related,
`Safety Significant
`
`374
`(0.9%)
`
`RISC - 4
`
`Safety-Related,
`Not Safety Significant
`
`Non-Safety Related,
`Not Safety Significant
`
`12,611
`(28.7%)
`
`26,599
`(60.9%)
`
`COMPONENT RISK SIGNIFICANCE -
`MAINTENANCE APPLICATION BREAKDOWN
`As of 4/16/01 (See Note 1)
`Component Risk Significance Breakdown
`% of
`Safety Related
`SSC’s
`09 %
`16 %
`29 %
`46%
`
`Risk Significance
`
`16,715
`
`1482 High
`2,622 Medium
`4,780 Low
`7,831 NRS
`Commercial
`Issue
`
`75% of Safety Related SSC’s
`Available for Process Optimization
`
`See Note 2
`
`See Note 1
`
`Total Evaluated
`SSC Population
`29 Systems
`43,688 TPNS
`
`Non-
`Safety
`Related
`SSCs
`62%
`
`Safety
`Related
`SSCs
`38%
`
`Total SSC Breakdown
`High - 1,502 (3%)
`Medium - 2,976 ( 7%)
`Low - 6,457 (15%)
`NRS - 32,753 (75%)
`
`Medium
`
`High
`
`LOW
`
`NRS
`
`% of Non-Safety Related SSC’s
`
`26,973
`
`Safety Issue
`
`24,922 NRS
`
`1,677 Low
`
`354 Medium
`20 High
`
`93 %
`
`6 %
`
`1 %
`<1 %
`
`<2% of Non-Safety
`Related SSC’s
`requiring Process
`Enhancement
`
`Inclusive of Systems AF, CC, CH01, CV, DG, DI, DO, DX, EW, FC, FW,
`Note 1:
`HC, HE, HF, HG, HM, IA, JW, LU, MS, PS,RA, RC, RH, SB, SD, SI, WL and XG.
`
`Note 2: Includes Augmented
`Quality Related 7F, 7S, 7P and 7R.
`
`10
`
`2-5
`
`CiM Ex. 1004 Page 21
`
`
`
`Why is it okay to categorize components and
`treat them differently?
`
`(cid:127) Commercial practices have been demonstrated to be acceptable
`through improved power plant capability and reliability factors
`
`(cid:127) Safety-related/non-safety related component failure rates are generally
`the same
`
`(cid:127)
`
`It is expected that the least important components will continue to
`function when demanded
`
`(cid:127) Even if one of these components were to fail, it would result in little to
`no impact on safety
`
`Special Treatment Requirements
`
`(cid:127) Special Treatment Requirements (STR) provide additional
`assurance that safety-related components will function beyond
`what commercial practices provide
`
`(cid:127) STR may provide benefit for the most important components,
`but not for the least important components
`
`(cid:127) The least important components (LSS/NRS) only need
`reasonable assurance that the design functional requirements
`will be met
`
`(cid:127) The least important components must still perform their
`functions when demanded
`
`2-6
`
`CiM Ex. 1004 Page 22
`
`
`
`Scope of the STP Exemption Request
`
`10CFR Part 21 (Vendor Notification)
`(cid:127)
`10CFR50.49 (Equipment Qualification)
`(cid:127)
`10CFR50.55 (ASME / ISI, IST)
`(cid:127)
`10CFR50.59 (Change Control)
`(cid:127)
`10CFR50.65 (Maintenance Rule)
`(cid:127)
`(cid:127) Appendix B (Quality Assurance Program)
`(cid:127) Appendix J (Containment Leak-tightness)
`(cid:127)
`10CFR Part 100 (Seismic)
`
`What Will the Exemption Mean to STP?
`
`• An opportunity for STP to adjust the treatment on the least important
`safety-related components:
`
`– failed components could be replaced with commercial
`replacement parts
`
`– ASME Class 2 and 3 components could be repaired or replaced
`following an ANSI commercial code
`
`–components will generally be outside of the Maintenance Rule scope
`
`–seismic and environmental qualified parts could be replaced with non-
`qualified replacement parts
`
`–containment penetration leakage tests could be eliminated
`
`–maintenance documentation could be reduced
`
`14
`
`2-7
`
`CiM Ex. 1004 Page 23
`
`
`
`Summary
`
`(cid:127)
`
`Importance determination (categorization) allows the importance of
`components to be recognized - not all safety-related components are
`equally important
`
`(cid:127) Some non-safety-related components are actually more important than
`saf