Condition Based Maintenance Plus Research Articles

A Study on the Collection of Degradation Data and Anomaly Detection Based on Artificial Neural Network for the Application of Condition-Based Maintenance Plus (CBM+) in Single Board Computer

A Study on the Collection of Degradation Data and Anomaly Detection Based on Artificial Neural Network for the Application of Condition-Based Maintenance Plus (CBM+) in Single Board Computer

Feasibility and foundational elements of CBM+ technology application in weapon systems

The maintenance strategies of weapon systems have evolved from corrective maintenance post-failure to time-based preventive maintenance, driven by the growing adoption of diagnostic technologies and data utilization. Currently, there is a transition to Condition-Based Maintenance (CBM) and, where applicable, Condition-Based Maintenance Plus (CBM+). This study investigated the feasibility of applying CBM+ technology using sensor data from weapon systems and explored methods for implementing the related foundational elements. First, the feasibility of CBM+ technology was confirmed by integrating data collection devices into the engine components of selected weapon systems, enabling sensor data collection and monitoring. Second, empirical evidence was gathered on the foundational elements necessary for the broader adoption of CBM+ technology. Practical application methods were proposed based on this evidence, including criteria for implementing CBM+ technology in major operational weapon systems, estimation of sensor data capacity, network methods for data transmission and collection, and the standardization of sensor data. The study’s findings are expected to provide reference points for selecting target weapon systems for the development and application of CBM+ technology, as well as outline essential foundational elements, such as security, networking, and data standardization, critical for leveraging related technologies.

A Study on Method for Applying CBM+ in Missile for Effective Health Management

The objective of condition-based maintenance plus(CBM+) is to improve the availability and maintenance efficiency of missiles, bolstering national defense capabilities. This study proposes an application of CBM+ to enhance the reliability and the safety of missiles, which are the devices typically stored for long durations. CBM+ does not only contribute to defense capabilities, but it also aims to reduce maintenance costs. This study focuses particularly on the dormant stage of the missile life-cycle, in which various failure modes and environmental impacts on failure mechanisms are investigated. The effectiveness of maintenance strategies and the implementation of CBM+ is evaluated using simulation data.

Comparative Vacuum Monitoring Solutions to Advance U.S. Air Force KC-46A Condition-Based Maintenance Plus

The KC-46A Pegasus, a Boeing 767 (B767) commercial derivative aircraft (CDA), is a key part of the United States Air Force’s (USAF) efforts to modernize their aging tanker fleet. The Department of Defense (DoD) and the USAF have heavily emphasized the desire and need for Condition-Based Maintenance Plus (CBM+) to improve aircraft maintenance programs such as the KC-46A. This study reviews existing CBM+ practices on B767 and related aircraft fleets at Delta Air Lines to identify initial steps for implementing CBM+ in the KC-46 maintenance program. Specifically, comparative vacuum monitoring (CVM) sensors are proposed for KC-46A structural health monitoring (SHM) as a Federal Aviation Administration (FAA)-certified CBM+ technology. As demonstrated at Delta Air Lines Technical Operations (Delta TechOps), CVM sensors satisfy the technological, procedural, financial, and regulatory requirements to advance KC-46A SHM and serve as a template for future CBM+ initiatives.

수소충전소 설비운영 안전관리 상용화를 위한 CBM+활용 방안 연구

Purpose: This study aims to meet the functional safety requirements using condition-based maintenance plus (CBM+) to ensure the safe operation of equipment, such as chillers, compressors, and dispensers, used in hydrogen refueling facilities. BRMethods: For the commercialization of the safety management of hydrogen refueling stations, we demonstrate an approach for detecting equipment abnormalities during operation by measuring sound, vibration, and current. CBM+ is used for fault diagnosis; the results are compared with those of the traditional fault diagnosis methods.BRResults: At hydrogen refueling stations in South Korea, 90.48% of accidents occurred due to hydrogen leakage from 2005 to 2014. During the same period, 7 (31.82%) out of 22 such accidents were caused by human errors in the United States. Through structural analysis of vertical axis, lateral sides, and height of the hydrogen charging stations, we propose a method that uses sensor nodes, sensor systems, and communication systems for CBM+.BRConclusion: Only a few empirical studies have reported the use of CBM+ for hydrogen refueling stations in South Korea. Effective strategies for CBM+ have also not been presented. Through technical research and institutional improvement, including this study, it is necessary to secure functional safety and PHM technology for CBM for the safe operation of hydrogen refueling stations in South Korea. In addition, data based on several factors, including the equipment component type, failure, and safety risk level, must be acquired in a standard format. However, to eliminate the safety risks of hydrogen refueling stations, hydrogen leakage accidents must be primarily avoided.

Exploring the Application of CBM+ in an ISR Weapon System, Thermal Observation Device

Purpose: This study suggests a method to apply the condition-based maintenance plus (CBM+) concept, known to improve system availability, by introducing a deep learning model on the thermal observation device (TOD)—representative of an intelligence, surveillance, and reconnaissance (ISR) weapon system.BRMethods: The temperature was chosen as a health index, and the data (normal/abnormal) was acquired by operating the device in a controlled laboratory and from the manufacturer.BRResults: The criteria to classify the abnormal condition were established regarding time and temperature. The following deep learning models were introduced: the convolution neural network (CNN) model for detecting the abnormality and long short-term memory (LSTM) for predicting remaining useful life (RUL). The models proved that the accuracy and loss were fine. Thus, the logic flow of CBM+ for the TOD was suggested by incorporating the models.BRConclusion: The data collected had limitations due to the highly controlled data acquisition. Nevertheless, the possibility of applying the CBM+ logic to similar weapon systems that employ the cooled-type detector could be confirmed.

A Review on the Advanced Maintenance Approach for Achieving the Zero-Defect Manufacturing System

Recently, a revolutionary change is taking place in manufacturing and production systems thanks to the development of various advanced technologies such as IIoT (Industrial Internet of Things), CPPS (Cyber-Physical Production System), digital twins, big data analytics, AI (Artificial Intelligence), and so on. One of the change is that manufacturing and production systems are now trying to transform into the ZDM (Zero-Defect Manufacturing) system. For a manufacturing company, quality takes precedence over any other competitive factors, so the implementation of a ZDM system is very important. For the implementation of ZDM, many fundamental technologies are required. Among them, the advanced maintenance approach for the facilities/equipment of the manufacturing and production system is much more important because it could support the zero-defect and high-efficiency operation of manufacturing and production systems. The advanced maintenance approach, which is often called by various terms such as predictive maintenance, condition-based maintenance plus (CBM+), and PHM (Prognostics and Health Management), requires various interdisciplinary knowledge and systematic integration. In this study, we will review previous works mainly focusing on advanced maintenance subject among ZDM research works, and briefly discuss the challenging issues for applying PHM technologies to the ZDM.

Cost-Wise Readiness Enabled Through Condition Based Maintenance Plus (CBM+)


 
 
 As Department of Defense (DoD) budgets continue to decrease through automatic spending cuts, Army Commands are pressured to develop, implement and manage new ways to reduce spending. The high cost of operation and sustainment (O&S) associated with the helicopters required to support the US Army’s global presence significantly increases this pressure. Reducing costs within O&S activities, while managing operational readiness is achieved through Cost Wise Readiness (CWR) initiatives. Goals and objectives are to increase efficiencies, thereby increasing the value of each budgeted dollar. Even as the budgetary environment becomes more challenging, the purpose of Army maintenance remains unchanged—to generate combat power. In support of continuing this capability, Army Aviation is leading the way with ongoing efforts to implement, measure and communicate efficiencies leading to benefits. The AMCOM Logistics Center (ALC) functions as the logistics component of the US Army’s Aviation and Missile Life Cycle Management Command (AMCOM) headquartered at Redstone Arsenal, Alabama. The ALC develops, acquires, fields and sustains logistics support for Army Aviation and Missile systems and associated support equipment to ensure weapon system readiness in any operation worldwide. The ALC, in support of Program Executive Offices, Project Managers, Army Depots, and partnering with industry are dedicated to provide real-time logistics support to the Soldier, Airman and Marine in training and combat. The ALC is dedicated to the development and implementation of CWR initiatives through the identification and pursuit of opportunities and investment in projects focused on reducing cost. Multiple Army offices have been instrumental in the development of technological capabilities in support of the CWR mission. One such high-tech capability includes the integration of systems which incorporate Condition Based Maintenance Plus (CBM+) into the management of logistics and airworthiness aspects of the Army’s helicopter fleets. Managing costs within O&S activities is achievable through the remediation of maintenance enabled through CBM+ initiatives.
 
 

Bridging design and implementation for a more practical condition-based maintenance plus (CBM+) solution embedded vehicle diagnostics on the mini-vehicle computer system (VCS)

This paper is a technology update of the newest vehicle diagnostics system, the Smart Wireless Internal Combustion Engine (SWICE) At Platform Test System interface, which can be used as a mini-vehicle computer system (Mini-VCS). SWICE consists of hardware devices, software applications, and other interface components and supports the Army's product director-test measurement and diagnostic equipment (PD-TMDE) division. The objective of this system is to further enhance Condition-Based Maintenance Plus (CBM+) secure diagnostics, data logging, prognostics and sensor integration to support improvement of the U.S. military ground vehicle fleet's uptime to enhance operational readiness.