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The Preventive Maintenance (PM) program at Stennis Space Center (SSC) evolved from an ineffective and poorly organized state to a highly organized state in which it became capable of tracking equipment, planning jobs with man hour estimates, and supporting outsourcing. This viewgraph presentation traces the steps the program took to improve itself.
Operation and maintenance costs for nuclear power plants are very large. Reactors are starting to shut down even after their operating licenses have been extended, because they are not price competitive compared to other energy sources. The nuclear industry is witnessing early closure of nuclear power plants due to economic reasons despite excellent safety records. Therefore, it is imperative to reduce costs to prevent these early closures. This paper showcases recent research into advanced fault diagnostics techniques and preventative maintenance optimization to reduce these maintenance costs. This report focuses on the condensate and feedwater system for both pressurized and boiling water reactor systems. The computerized maintenance management system, which contains the plant’s digital record of all the corrective- and preventative-maintenance work orders, was used as a ground truth to locate potential faults and label the process data as healthy or faulty. Various feature extraction techniques were utilized to further differentiate the faults from the healthy data. Support vectors machines were used to categorize other test sets of process data as healthy or faulty through a cross validation procedure. Similar faults were not found within this system leading to preventative maintenance optimization. Unnecessary amounts of preventative maintenance lead to inflated maintenance costs. This paper summarizes the steps for preventative maintenance optimization from component health determination to recommendation for action. This optimization was completed for condensate pumps, condensate booster pumps, and the respective motors that drive them.
A model is formulated to describe the effect of the time interval chosen for preventive maintenance upon the frequency of failure and frequency of total maintenance. Trade-offs between these two frequencies are determined by computation of an optimal interval in the case where the failure distribution is known. For unknown distributions, an adaptive statistical technique is developed that converges to an optimal preventive maintenance interval. A numerical illustration is given.
Preventive maintenance instructions for bonding and electrical grounding systems to prevent equipment damage by electrical faults, lightning, and radiation - Vol. 3
Reliability equation for complex system with preventive maintenance
To maximize reliability of a spacecraft which performs long-life (over 10-year), deep-space mission (to outer planet), a fault-tolerant environment incorporating automatic on-board preventive maintenance is highly desirable.
Initial data for optimal duration of preventive maintenance in system with possible fault
The nuclear industry is beginning to see reactors shut down—even after their operating licenses have been extended—because they are not economically competitive with other energy sources. These early closures happen primarily due to economic reasons, despite excellent safety records. Therefore, it is imperative to reduce costs in order to prevent these early closures. One of the contributors to these economic reasons is the large operations and maintenance costs. This paper showcases recent research on advanced fault diagnostics techniques and preventative maintenance optimization (PMO) for reducing NPP maintenance costs. Specifically, it focuses on the feedwater and condensate system (FWCS) for both pressurized- and boiling-water reactor (BWR) systems. The computerized maintenance management system (CMMS), which contains the plant’s digital record of all corrective maintenance (CM) and preventative maintenance (PM) work orders, provided the ground truth for locating potential faults and labeling the process data as either healthy or faulted. Various feature extraction techniques were used to further differentiate the faulted data from the healthy data. Through a cross-validation procedure, support vectors machines were used to label other test sets of process data as either healthy or faulted. With relatively few faults identified in the BWR system, the potential for PMO opens up, since an unnecessary amount of PM leads to inflated maintenance costs. The steps for PMO are summarized, from component health determinations to recommendations for action. An example of PMO assessment is presented for condensate pumps, condensate booster pumps, and the respective motors that drive them.
The nuclear industry is beginning to see reactors shut down—even after their operating licenses have been extended—because they are not economically competitive with other energy sources. These early closures happen primarily due to economic reasons, despite excellent safety records. Therefore, it is imperative to reduce costs in order to prevent these early closures. One of the contributors to these economic reasons is the large operations and maintenance costs. This paper showcases recent research on advanced fault diagnostics techniques and preventative maintenance optimization (PMO) for reducing NPP maintenance costs. Specifically, it focuses on the feedwater and condensate system (FWCS) for both pressurized- and boiling-water reactor (BWR) systems. The computerized maintenance management system (CMMS), which contains the plant’s digital record of all corrective maintenance (CM) and preventative maintenance (PM) work orders, provided the ground truth for locating potential faults and labeling the process data as either healthy or faulted. Various feature extraction techniques were used to further differentiate the faulted data from the healthy data. Through a cross-validation procedure, support vectors machines were used to label other test sets of process data as either healthy or faulted. With relatively few faults identified in the BWR system, the potential for PMO opens up, since an unnecessary amount of PM leads to inflated maintenance costs. The steps for PMO are summarized, from component health determinations to recommendations for action. An example of PMO assessment is presented for condensate pumps, condensate booster pumps, and the respective motors that drive them.
The long-life deep-space missions associated with NASA's X2000 Advanced Flight Systems Program creates many unprecedented challenges for us.
With respect to the long-life missions associated with NASA's X2000 Advanced Deep-Space System Development Program, reliability implies a system's continuous operation for many years in an unsurveyed radiation-intense environment.
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Maintenance program which is concise and inexpensive to operate adapts to almost any system that has a FORTRAN compiler. Program operates on a stored data base with an output consisting of scheduling information and various management reports.
This paper illustrates using Markov models to establish system and maintenance requirements for small electronic controllers where the goal is a high probability of continuous service for a long period of time. The system and maintenance items considered are quality of components, various degrees of simple redundancy, redundancy with reconfiguration, diagnostic levels, periodic maintenance, and preventive maintenance. Markov models permit a quantitative investigation with comparison and contrast. An element of special interest is the use of conditional probability to study the combination of imperfect diagnostics and periodic maintenance.
Due to continuing global energy market trends, driven heavily by the abundant preserves of natural gas, there is an immediate need to reduce costs associated with operation and maintenance (O&M) for the current domestic nuclear power industry and for future reactor developments. This is to ensure that nuclear power generation remains an economically competitive and viable option in the energy market. O&M costs include labor-intensive preventive maintenance (PM) programs, which involve manually-performed inspection, calibration, testing, and maintenance of plant assets at periodic frequency and time-based replacement of assets, irrespective of their condition. This has resulted in an expensive, labor-centric business model to achieve high capacity factors. Fortunately, there are technologies (advanced sensors, data analytics, and risk assessment methodologies) that can enable the transition from a labor-centric business model to a technology-centric business model. The technology-centric business model will result in a significant reduction of PM activities, laying the foundation for real-time condition assessment of plant assets, reducing overall labor and part costs. To enable this transition, PKMJ Technical Services LLC is partnering with the U.S. Department of Energy’s Idaho National Laboratory (operated by the Battelle Energy Alliance, LLC) and the Public Services Enterprise Group (PSEG) Nuclear, LLC in the Integrated Risk-Informed Condition-Based Maintenance Capability and Automated Platform Project. In this report, the configuration of a digital cloud platform using Microsoft Azure is discussed, data from the PSEG Salem Nuclear Generating Station Units 1 & 2 are imported into a digital cloud platform, and the data is used for an evaluation of several key areas: cost impact analysis, risk-informed model development, and preventive maintenance strategy optimization. First, the cost impact analysis reviews which plant assets are potential good candidates for condition-based monitoring. Next, INL utilized the data in their local environment to develop the risk-informed model; which provides estimates of failure rates and probability of failures of assets based upon their past performance. The developed model is performed on assets selected from the cost impact analysis. Lastly, engineers assess the preventive maintenance strategy for the selected assets at PSEG against maintenance strategies in the nuclear industry for similar assets to potentially identify acceptable justification for the extension of current maintenance frequencies.
Preventive maintenance, calibration procedures, system verification, system operating procedures, systems software fundamentals, data base (program files), and patchboard layout are discussed.
It is essential that management and engineering understand the need for an availability requirement for the customer's space transportation system as it enables the meeting of his needs, goal, and objectives. There are three types of availability, e.g., operational availability, achieved availability, or inherent availability. The basic definition of availability is equal to the mean uptime divided by the sum of the mean uptime plus the mean downtime. The major difference is the inclusiveness of the functions within the mean downtime and the mean uptime. This paper will address tIe inherent availability which only addresses the mean downtime as that mean time to repair or the time to determine the failed article, remove it, install a replacement article and verify the functionality of the repaired system. The definitions of operational availability include the replacement hardware supply or maintenance delays and other non-design factors in the mean downtime. Also with inherent availability the mean uptime will only consider the mean time between failures (other availability definitions consider this as mean time between maintenance - preventive and corrective maintenance) that requires the repair of the system to be functional. It is also essential that management and engineering understand all influencing attributes relationships to each other and to the resultant inherent availability requirement. This visibility will provide the decision makers with the understanding necessary to place constraints on the design definition for the major drivers that will determine the inherent availability, safety, reliability, maintainability, and the life cycle cost of the fielded system provided the customer. This inherent availability requirement may be driven by the need to use a multiple launch approach to placing humans on the moon or the desire to control the number of spare parts required to support long stays in either orbit or on the surface of the moon or mars. It is the intent of this paper to provide the visibility of relationships of these major attribute drivers (variables) to each other and the resultant system inherent availability, but also provide the capability to bound the variables providing engineering the insight required to control the system's engineering solution. An example of this visibility will be the need to provide integration of similar discipline functions to allow control of the total parts count of the space transportation system. Also the relationship visibility of selecting a reliability requirement will place a constraint on parts count to achieve a given inherent availability requirement or accepting a larger parts count with the resulting higher reliability requirement. This paper will provide an understanding for the relationship of mean repair time (mean downtime) to maintainability, e.g., accessibility for repair, and both mean time between failure, e.g., reliability of hardware and the system inherent availability. Having an understanding of these relationships and resulting requirements before starting the architectural design concept definition will avoid considerable time and money required to iterate the design to meet the redesign and assessment process required to achieve the results required of the customer's space transportation system. In fact the impact to the schedule to being able to deliver the system that meets the customer's needs, goals, and objectives may cause the customer to compromise his desired operational goal and objectives resulting in considerable increased life cycle cost of the fielded space transportation system.
The maintenance data base collected for 15 weeks of recent unattended and automated operation of DSS 13 is summarized. During this period, DSS 13 was receiving spacecraft telemetry while being controlled remotely from JPL in Pasadena. Corrective and preventive maintenance manhours are reported by subsystem for DSS 13 including the equipment added for the automation demonstration. The corrective and preventive maintenance weekly manhours at DSS 13 averaged 22 and 40, respectively. The antenna hydraulic and electronic systems accounted for about half of the preventive and corrective maintenance manhours for a comparable attended DSN station, DSS 11.