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NASA NTRS1972

Space shuttle maintenance program planning document

A means for developing a space shuttle maintenance program which will be acceptable to the development centers, the operators (KSC and AF), and the manufacturer is presented. The general organization and decision processes for determining the essential scheduled maintenance requirements for the space shuttle orbiter are outlined. The development of initial scheduled maintenance programs is discussed. The remaining maintenance, that is non-scheduled or non-routine maintenance, is directed by the findings of the scheduled maintenance program and the normal operation of the shuttle. The remaining maintenance consists of maintenance actions to correct discrepancies noted during scheduled maintenance tasks, nonscheduled maintenance, normal operation, or condition monitoring.

Brown, D. V.↗

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization

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.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗

NASA NTRS2023

An Analysis of Barriers Preventing the Widespread Adoption of Predictive and Prescriptive Maintenance in Aviation

The aviation industry has long recognized the potential benefits of predictive maintenance, a maintenance strategy that leverages sensor and operational data to predict the future degradation of components. Prescriptive maintenance takes this a step further and considers the entire aviation ecosystem to schedule maintenance actions optimally. With the ability to reduce maintenance costs by up to 30%, as reported by the Department of Energy, these maintenance strategies have been identified to be an important investment to reduce a airline costs. However, despite great interest and technological advances in areas such as diagnostics, prognostics, sensing, computation, and machine learning, the adoption of predictive and prescriptive maintenance has not been widely applied in aviation. To shed light on this issue, we conducted an analysis of the barriers preventing or limiting the adoption of predictive and prescriptive maintenance in aviation. Through discussions with subject matter experts across industry, academia, standards bodies, and government, we identified five key challenges: complexity of prediction; validation, safety assurance, and regulatory challenges; cost of adoption; difficulty in quantifying impact and informing decisions; and data availability, quality, and ownership challenges. This study provides a detailed overview of these barriers and areas where stakeholders could invest to overcome them, aiming to support the scaled adoption of predictive and prescriptive maintenance in aviation.

Christopher Teubert↗

DOE OSTI2020

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 1

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.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Markov Process to Evaluate the Value Proposition of a Risk-Informed Predictive Maintenance Strategy

To achieve high-capacity factors, the nuclear fleet has relied on labor-intensive and time-consuming operation and preventive maintenance programs for plant systems. Manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies, along with time-based replacement of assets irrespective of condition, have resulted in a costly, labor-centric business model. Fortunately, there are technologies that can eliminate unnecessary preventive maintenance activities by deploying risk-informed predictive maintenance, enabling the transition to a technology-centric business model. The technology-centric business model will enable plants to optimize and automate maintenance activities, leading to cost reductions since labor is a rising cost and technology is a declining cost. The implementation of scalable technologies and methodologies across plant systems and across the nuclear fleet is critical for successful deployment of a risk-informed predictive maintenance strategy at commercial nuclear power plants. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report describes the technical basis using the Markov Process to evaluate the value proposition for the risk-informed predictive maintenance strategy for the circulating water system. The plant process data from the Salem nuclear plant’s circulating water system is utilized to develop a Markov chain risk models and formulation to estimate the loss and gain in revenue based on plant availability. The outcomes presented in this report provides the technical basis for extensive quantitative evaluation of a scalable risk-informed predictive maintenance strategy as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Well Design, Operation and Maintenance and Proactive Rehabilitation to Optimize Remediation Well Performance - 18605

Optimizing performance of extraction, injection and monitoring wells, which are integral components of groundwater remediation systems, result in lower life cycle costs and a higher probability of meeting project objectives. These wells provide the means to extract contaminated groundwater, inject reagents, treated water and clean water to create groundwater reaction/flushing zones, and to provide groundwater level, contaminant concentration and geochemical data. Initial costs associated with well installation and associated pipelines and treatment systems are significant project expenditures related to site remediation. However, the life cycle costs for wells are dominated by the long-term operation and maintenance (O and M) expenditures. Remediation wells are particularly susceptible to various types of fouling that impact well performance and, therefore, drive up operating costs. Simply defined, fouling is the result of any biological, geochemical or physical process that negatively impacts the intended performance of a remediation well. Fouling decreases well performance by effectively reducing hydraulic communication between the well and the surrounding formation. Oftentimes this occurs via clogging screens and/or gravel pack/formation pore space by bacterial or chemical byproducts and gases, which can lead to corrosion of metal components and spreading fouling deposits to pipelines and surface treatment systems. Ultimately, this results in reduced hydraulic performance in extraction and injection wells and result in erroneous water level and chemical parameter concentration measurements in monitoring wells. Remediation well fouling cannot be eliminated, and natural fouling processes are exacerbated by the installation and operation of remedial systems. Steps required to extend the life of remediation wells and to lower life cycle costs are discussed in this paper in order to establish the required approach to effective system management. These optimization approaches have been developed through years of operation and maintenance of complex large-scale plume remediation systems utilizing a variety of subsurface in-situ and ex-situ technologies. Remediation well performance can be improved by: - careful site characterization, - appropriate well design, - proper well installation and development, - thoughtful and adaptable operation and maintenance, - well performance maintenance tracking and, - proactive well rehabilitation. Clear understanding of the site hydro-stratigraphy and geochemical settings places constraints on the compatibility of well materials and the configurations of well screens. Proper well design, including collection and analysis (sieve/grain-size) of screen zone formation samples, assures that wells can be optimally installed, developed and redeveloped during well rehabilitation. Design considerations should include proper sizing of filter packs and well screens, casing/screen diameter, well material selection/compatibility, expected life/use, and well head configuration to allow for future access. Applying appropriate and effective well installation and development methods are of paramount importance and rely on a good understanding of site characteristics (e.g., geologic setting) as well as local drilling company expertise and experience. Different approaches to operation and maintenance can greatly affect the degree of fouling, these include limiting reagent concentrations, maintaining submerged well screens and filtering injection water to prevent the introduction of fouling enhancing constituents. Tracking well performance by monitoring changes in system operation and metrics such as specific capacity or injectivity for extraction and injection wells, respectively, or turbidity and chemical analyses for monitoring wells is key to identifying well maintenance issues early when well rehabilitation can be most effective. Proactive well rehabilitation can include mechanical brushing, surging and jetting, chemical treatment or other specialized approaches; however, the approach needs to be based on a site-specific understanding of the predominant fouling mechanisms. Collection and analyses of fouling deposits can provide guidance for selection of rehabilitation methods and chemicals that will be most effective. Application of these approaches have led to extended operational life for reagent injection wells, which can foul quickly, from months to years. Additionally, proper maintenance will often lead to increased and extended productivity of the well. For extraction wells, this translates to a higher sustainable yield, which means shorter cleanup times. Similarly, for injection wells, proper maintenance allows for the introduction of a greater volume of reagents over a shorter period, thus, shorter cleanup times that reduce overall project costs. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1992

Toward full life cycle control: Adding maintenance measurement to the SEL

Organization-wide measurement of software products and processes is needed to establish full life cycle control over software products. The Software Engineering Laboratory (SEL)--a joint venture between NASA GSFC, the University of Maryland, and Computer Sciences Corporation--started measurement of software development more than 15 years ago. Recently, the measurement of maintenance was added to the scope of the SEL. In this article, the maintenance measurement program is presented as an addition to the already existing and well-established SEL development measurement program and evaluated in terms of its immediate benefits and long-term improvement potential. Immediate benefits of this program for the SEL include an increased understanding of the maintenance domain, the differences and commonalities between development and maintenance, and the cause-effect relationships between development and maintenance. Initial results from a sample maintenance study are presented to substantiate these benefits. The long-term potential of this program includes the use of maintenance baselines to better plan and manage future projects and to improve development and maintenance practices for future projects wherever warranted.

Rombach, H. Dieter↗

NASA NTRS1993

Test, Control and Monitor System maintenance plan

The maintenance requirements for Test, Control, and Monitor System (TCMS) and the method for satisfying these requirements prior to First Need Date (FND) of the last TCMS set are described. The method for satisfying maintenance requirements following FND of the last TCMS set will be addressed by a revision to this plan. This maintenance plan serves as the basic planning document for maintenance of this equipment by the NASA Payloads Directorate (CM) and the Payload Ground Operations Contractor (PGOC) at KSC. The terms TCMS Operations and Maintenance (O&M), Payloads Logistics, TCMS Sustaining Engineering, Payload Communications, and Integrated Network Services refer to the appropriate NASA and PGOC organization. For the duration of their contract, the Core Electronic Contractor (CEC) will provide a Set Support Team (SST). One of the primary purposes of this team is to help NASA and PGOC operate and maintain TCMS. It is assumed that SST is an integral part of TCMS O&M. The purpose of this plan is to describe the maintenance concept for TCMS hardware and system software in order to facilitate activation, transition planning, and continuing operation. When software maintenance is mentioned in this plan, it refers to maintenance of TCMS system software.

Buehler, David P.↗

NASA NTRS1992

Determining maintenance cost ratios

This paper reports on the wide range of costs involved in maintaining equipment and discusses methods that different industries use to measure and report their maintenance cost. Results are presented of the study of maintenance costs in the NASA Deep Space Network (DSN) and of a comparison of DSN maintenance cost with the maintenance costs of a number of other reports. A comparison of the maintenance costs in terms of the maintenance cost ratio (annual maintenance cost/capital replacement cost) shows that DSN has the lowest maintenance cost ratio of the industries and organizations surveyed.

Remer, Donald S.↗

NASA NTRS1996

Understanding and Predicting the Process of Software Maintenance Releases

One of the major concerns of any maintenance organization is to understand and estimate the cost of maintenance releases of software systems. Planning the next release so as to maximize the increase in functionality and the improvement in quality are vital to successful maintenance management. The objective of this paper is to present the results of a case study in which an incremental approach was used to better understand the effort distribution of releases and build a predictive effort model for software maintenance releases. This study was conducted in the Flight Dynamics Division (FDD) of NASA Goddard Space Flight Center(GSFC). This paper presents three main results: 1) a predictive effort model developed for the FDD's software maintenance release process; 2) measurement-based lessons learned about the maintenance process in the FDD; and 3) a set of lessons learned about the establishment of a measurement-based software maintenance improvement program. In addition, this study provides insights and guidelines for obtaining similar results in other maintenance organizations.

Basili, Victor↗

NASA NTRS1973

Phase 111A Crew Interface Specifications Development for Inflight Maintenance and Stowage Functions

This report presents the findings and data products developed during the Phase IIIA Crew Interface Specification Study for Inflight Maintenance and Stowage Functions, performed by General Electric for the NASA, Johnson Space Center with a set of documentation that can be used as definitive guidelines to improve the present process of defining, controlling and managing flight crew interface requirements that are related to inflight maintenance (including assembly and servicing) and stowage functions. During the Phase IIIA contract period, the following data products were developed: 1) Projected NASA Crew Procedures/Flight Data File Development Process. 2) Inflight Maintenance Management Process Description. 3) Preliminary Draft, General Specification, Inflight Maintenance Management Requirements. 4) Inflight Maintenance Operational Process Description. 5) Preliminary Draft, General Specification, Inflight Maintenance Task and Support Requirements Analysis. 6) Suggested IFM Data Processing Reports for Logistics Management The above Inflight Maintenance data products have been developed during the Phase IIIA study after review of Space Shuttle Program Documentation, including the Level II Integrated Logistics Requirements and other DOD and NASA data relative to Payloads Accommodations and Satellite On-Orbit Servicing. These Inflight Maintenance data products were developed to be in consonance with Space Shuttle Program technical and management requirements.

Carl, John G.↗

NASA NTRS2007

A Study to Estimate the Effectiveness of Visual Testing Training for Aviation Maintenance Management

The Air Commerce Act of 1926 set the beginning for standards in aviation maintenance. Even after deregulation in the late l970s, maintenance standards and requirements still have not changed far from their initial criteria. After a potential candidate completes Federal Aviation Administration training prerequisites, they may test for their Airframe and Powerplant (A&P) certificate. Performing maintenance in the aviation industry for a minimum of three years, the technician may then test for their Inspection Authorization (IA). After receiving their Airframe and Powerplant certificate, a technician is said to have a license to perform. At no time within the three years to eligibility for Inspection Authorization are they required to attend higher-level inspection training. What a technician learns in the aviation maintenance industry is handed down from a seasoned technician to the new hire or is developed from lessons learned on the job. Only in Europe has the Joint Aviation Authorities (JAA) required higher-level training for their aviation maintenance technicians in order to control maintenance related accidents (Lu, 2005). Throughout the 1990s both the General Accounting Office (GAO) and the National Transportation Safety Board (NTSB) made public that the FAA is historically understaffed (GAO, 1996). In a safety recommendation the NTSB stated "The Safety Board continues to lack confidence in the FAA's commitment to provide effective quality assurance and safety oversight of the ATC system (NTSB, 1990)." The Federal Aviation Administration (FAA) has been known to be proactive in creating safer skies. With such reports you would suspect the FAA to also be proactive in developing more stringent inspection training for aviation maintenance technicians. The purpose of this study is to estimate the effectiveness of higher-level inspection training, such as Visual Testing (VT) for aviation maintenance technicians, to improve the safety of aircraft and to make recommendations to management with regard to the value of such training.

Law, Lewis Lyle↗

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization

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.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Nuclear Power Fault Diagnostics and Preventative Maintenance Optimization NPIC presentation

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2018

Demand Response-Driven Production and Maintenance Decision-Making for Cost-Effective Manufacturing

Manufacturers consume about 27% of the total electricity in the U.S. and are among the main contributors in the rising electricity demand. End-user electricity demand response is an effective demand side management tool that can help energy suppliers reduce electricity generation expenditures while providing opportunities for manufacturers to decrease operating costs. Several studies on demand response for manufacturers have been conducted. However, there lacks a unified production model that balances production capability degradation, maintenance requirements, and time-of-use (TOU) electricity prices simultaneously such that the interaction between production, maintenance, and electricity costs is considered. In this paper, a cost-effective production and maintenance scheduling model considering TOU electricity demand response is presented. Additionally, an aggregate cost model is formulated, which considers production, maintenance, and demand response parameters in the same function. The proposed models provide manufacturers with tools for implementing feasible and cost-effective demand response while meeting production targets and efficiently allocating maintenance resources. A case study is performed and illustrates that 19% in cost savings can be achieved when using the proposed model compared to solely minimizing the electricity billing cost. In addition, 14% in cost savings can be achieved when using the proposed model compared to a strategy where only the maintenance cost is minimized. Finally, the benefits of demand response driven production and maintenance scheduling under different cost and parameter settings are investigated; where the rated power, production rate, and initial machine production capability show to have the largest impact on the cost effectiveness of implementing demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

A LEAN SYSTEMS APPROACH TO IMPROVING MAINTENANCE OUTPUT AND CONFIGURATION MANAGEMENT

The purpose of this capstone paper is to apply a lean systems approach to the current maintenance planning program in the Assembly/Disassembly Organization. This capstone will take a two-pronged approach to address both output rate in maintenance planning and accurate configuration management resulting from maintenance work orders. In short, the current system suffers from waste in the planning process due lack of procedures to address varying maintenance packages, including maintenance packages which include changes to configuration managed systems. The capstone will detail a lean systems approach to proper characterization of maintenance jobs and integration of change management into the maintenance process in order to retain proper control of the systems used to produce in this nuclear facility.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Machine learning models for maintenance cost estimation in delivery trucks using diesel and natural gas fuels

The maintenance costs can represent about 15%–60% of the cost of produced goods depending on the type of goods transported. To comply with stringent emissions regulations, diesel engines are incorporated with complex after-treatment systems that demand increased maintenance. The availability of alternative fuels such as natural gas and propane has fostered the natural gas and propane powertrain systems as well as electrification options for heavy- and medium-duty vehicles. A critical barrier to adopting alternative fuel vehicles has been the lack of knowledge on comparative vehicle maintenance/repair costs with conventional diesel. Moreover, the region of operation, the type of vehicle operation, and seasonal temperature changes also affect the duty cycle which impacts the maintenance and repair costs. This study focuses on estimating the cost-per-mile for heavy-duty vehicles using machine learning models such as random forest, xgboost, neural networks, and a super-learner model. The super-learner model achieved an error as low as 0.0068 $/mile for mean absolute error and 0.0086 $/mile for root mean square error with a coefficient of determination/R-Squared of 97.28%. Specifically, the paper investigates the data collected from the maintenance and repair costs associated with delivery trucks using diesel and natural gas fuels. Since the availability of data is the major constraint, we leveraged the data collected by West Virginia University and the partnership with fleet companies. This allows for additional information related to maintenance costs and fleet-specific maintenance practices of alternative fuel vehicles. This study promotes clean fuel technologies and enables fleet management companies to adopt alternative fuel vehicles in case of similar or lower cost of maintenance compared to diesel vehicles resulting in reduced emissions and total cost of ownership.

Katreddi, Sasanka↗