IMPLEMENTING CONDITION-BASED MAINTENANCE PLUS AS A GROUND MAINTENANCE STRATEGY IN THE MARINE CORPS

In 2020, Marine Corps Order 4151.22 and Commandant White Letter 2–20 was published to implement Condition-Based Maintenance Plus (CBM+) as a ground maintenance strategy to improve operational availability and reduce life-cycle costs. The Fleet Marine Force is still operating under preventative and corrective maintenance strategies instead of CBM+ strategies. Organizational inertia, such as competing priorities, legacy processes, and inspections, has slowed the integration of CBM+ strategies. We reviewed key policy documents and interviewed fifteen subject-matter experts relevant to Marine Corps ground transport maintenance policies and practices. Based on this information, we conducted a thematic analysis using an organizational change approach to identify barriers and opportunities that impact CBM+ implementation. We found that immediate gains from CBM+ implementation in the Marine Corps can be achieved through a focus on people and process improvements while technology integration continues. The CBM+ strategy supports Force Design 2030 and Talent Management 2030 objectives and emphasizing this alignment can build momentum for CBM+. In this paper, we make six specific recommendations that apply organizational change concepts to enable effective CBM+ implementation as a ground maintenance strategy in the Marine Corps.NPS Naval Research ProgramThis project was funded in part by the NPS Naval Research Program.Major, United States Marine CorpsMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

Enabling electronic prognostics using thermal data

Prognostics is a process of assessing the extent of deviation or degradation of a product from its expected normal operating condition, and then, based on continuous monitoring, predicting the future reliability of the product. By being able to determine when a product will fail, procedures can be developed to provide advanced warning of failures, optimize maintenance, reduce life cycle costs, and improve the design, qualification and logistical support of fielded and future systems. In the case of electronics, the reliability is often influenced by thermal loads, in the form of steady-state temperatures, power cycles, temperature gradients, ramp rates, and dwell times. If one can continuously monitor the thermal loads, in-situ, this data can be used in conjunction with precursor reasoning algorithms and stress-and-damage models to enable prognostics. This paper discusses approaches to enable electronic prognostics and provides a case study of prognostics using thermal data.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Piezoelectric Sensor Crack Detection on Airframe Systems

In 2008, the Department of Defense published a guidebook for a methodology named Condition-Based Maintenance Plus (CBM+) which capabilities include improving productivity, shortening maintenance cycles, lowering costs, and increasing availability and reliability. This push replaces existing inspection criteria, often conducted as non-destructive testing (NDT), with structural health monitoring (SHM) systems. The SHM system addressed utilizes guided Lamb waves generated by piezoelectric wafer active sensors (PWAS) to detect the existence, size, and location of damage from through-thickness cracks around a rivet hole. The SHM field lacks an experiment testing how small changes in receiver sensor distances affect damage detection. In addition, prior research has shown that transmitter and receiver PWAS angles significantly affected the received signal. Experiments here used existing damage detection metrics to establish thresholds for detection. Tests with two transmitter angles θ = 9°; 27° and three receiver distances, linearly incremented by 5mm, illustrated that damage detection capabilities significantly changed as the receiver distances were incremented at both 50mm and 1000mm transmitter distances. For 1000mm, the PWAS was able to detect the damage at certain geometries. This work validates of the PWAS detection capabilities for small changes and motivates further pursuits for varying PWAS geometries for long distances

INCORPORATING PREDICTIVE MAINTENANCE BEST PRACTICES INTO MARINE CORPS TRAINING AND OPERATIONS

The Marine Corps currently utilizes a traditional time-based strategy for ground equipment maintenance, conducting preventative maintenance at specified time intervals and corrective maintenance when failure occurs. In 2020, the Marine Corps initiated the transition from this maintenance strategy to a Condition Based Maintenance Plus (CBM+) strategy, which detects subcomponent anomalies in advance through data analytics so maintenance can be conducted before failure occurs. Hypothetically, CBM+ will generate increased cost-savings, reduce man-hour requirements, and improve operational availability for Marine Corps ground systems. Using a case study methodology, this project highlights best practices within the commercial mining, railroad, and heavy equipment industries by interviewing maintenance professionals and supplementing these discussions with existing literature. We then used a thematic analysis across five themes: organizational structure, asset classification, information technology (IT) infrastructure, data management, and maintenance decision making. By highlighting commonalities across the cases and evaluating best practices, we drew three key conclusions. First, some Marine Corps ground systems are not CBM+ compatible. Second, significant upgrades to existing maintenance infrastructure are necessary. Finally, CBM+ should be used as a decision-making framework to maximize cost-savings and combat readiness.Captain, United States Marine CorpsMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

ARCHITECTURE FOR A CBM+ AND PHM CENTRIC DIGITAL TWIN FOR WARFARE SYSTEMS

The Department of the Navy’s continued progression from time-based maintenance into condition-based maintenance plus (CBM+) shows the importance of increasing operational availability (Ao) across fleet weapon systems. This capstone uses the concept of digital efficiency from a digital twin (DT) combined with a three-dimensional (3D) direct metal laser melting printer as the physical host on board a surface vessel. The DT provides an agnostic conduit for combining model-based systems engineering with a digital analysis for real-time prognostic health monitoring while improving predictive maintenance. With the DT at the forefront of prioritized research and development, the 3D printer combines the value of additive manufacturing with complex systems in dynamic shipboard environments. To demonstrate that the DT possesses parallel abilities for improving both the physical host’s Ao and end-goal mission, this capstone develops a DT architecture and a high-level model. The model focuses on specific printer components (deionized [DI] water level, DI water conductivity, air filters, and laser motor drive system) to demonstrate the DT’s inherent effectiveness towards CBM+. To embody the system of systems analysis for printer suitability and performance, more components should be evaluated and combined with the ship’s environment data. Additionally, this capstone recommends the use of DTs as a nexus into more complex weapon systems while using a deeper level of design of experiment.Outstanding ThesisCivilian, Department of the NavyCommander, United States NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Condition-Based Maintenance Implementation and Potential in USMC Ground Transport

NPS NRP Project PosterCondition-Based Maintenance (CBM) has been successfully implemented in private-sector operations to reduce maintenance costs and asset downtime. USMC is currently transitioning to a CBM+ approach to maintenance, addressing its unique organizational and operating environment. This project identifies private-sector best practices and lessons learned most applicable to USMC as well as important hurdles for USMC adoption. It identifies maintenance and readiness metrics changes that may be relevant in future USMC and joint sustainment operations, taking into account both CBM and maintenance in an expeditionary environment.HQMC Installations and Logistics (I&L)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Condition-Based Maintenance Implementation and Potential in USMC Ground Transport

NPS NRP Technical ReportCondition-Based Maintenance (CBM) has been successfully implemented in private-sector operations to reduce maintenance costs and asset downtime. USMC is currently transitioning to a CBM+ approach to maintenance, addressing its unique organizational and operating environment. This project identifies private-sector best practices and lessons learned most applicable to USMC as well as important hurdles for USMC adoption. It identifies maintenance and readiness metrics changes that may be relevant in future USMC and joint sustainment operations, taking into account both CBM and maintenance in an expeditionary environment.HQMC Installations and Logistics (I&L)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Condition-Based Maintenance Implementation and Potential in USMC Ground Transport

NPS NRP Executive SummaryCondition-Based Maintenance (CBM) has been successfully implemented in private-sector operations to reduce maintenance costs and asset downtime. USMC is currently transitioning to a CBM+ approach to maintenance, addressing its unique organizational and operating environment. This project identifies private-sector best practices and lessons learned most applicable to USMC as well as important hurdles for USMC adoption. It identifies maintenance and readiness metrics changes that may be relevant in future USMC and joint sustainment operations, taking into account both CBM and maintenance in an expeditionary environment.HQMC Installations and Logistics (I&L)This research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Degrader Analysis for Diagnostic and Predictive Capabilities: A Demonstration of Progress in DoD CBM+ Initiatives

This paper presents a modified reliability centered maintenance (RCM) methodology developed by The Applied Research Laboratory at The Pennsylvania State University (ARL Penn State) to meet challenges in decreasing life cycle sustainment costs for critical Naval assets. The focus of this paper is on the requirements for the development of the on-board Prognostics and Health Management (PHM) system with a discussion on the implementation progress for two systems: the high pressure air compressor (HPAC), and the advanced carbon dioxide removal unit (ACRU). Recent Department of Defense (DoD) guidance calls for implementing Condition Based Maintenance (CBM) as an alternative to traditional reactive and preventative maintenance strategies that rely on regular and active participation from subject matter experts to evaluate the health condition of critical systems. The RCM based degrader analysis utilizes data from multiple sources to provide a path for selecting systems and components most likely to benefit from the implementation of diagnostic and predictive capabilities for monitoring and managing failure modes by determining various options of possible CBM system designs that provide the highest potential ROI. Sensor data collected by the PHM system can be used with machine learning applications to develop failure mode predictive algorithms with greatest benefit in terms of performance, sustainment costs, and increasing platform operational availability. The approach supports traditional maintenance strategy development by assessing the financial benefit of the PHM technology implementation with promising potential for many industrial and military complex adaptive system applications

On the role of Prognostics and Health Management in advanced maintenance systems

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognized as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyze how maintenance will change by using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the Condition Based Maintenance (CBM) and (iii) how PHM can be integrated into Reliability Centered Maintenance (RCM) programs. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.EU Framework Programme Horizon 2020, 645733 - Sustain-Owner - H2020-MSCA-RISE-201