scholarly journals Optimal Prognostics and Health Management-driven inspection and maintenance strategies for industrial systems

2021 ◽  
Vol 210 ◽  
pp. 107536 ◽  
Author(s):  
A. Mancuso ◽  
M. Compare ◽  
A. Salo ◽  
E. Zio
Keyword(s):  
Health Management ◽  
Prognostics And Health Management ◽  
Maintenance Strategies ◽  
Industrial Systems ◽  
Inspection And Maintenance

scholarly journals Challenges and Opportunities of System-Level Prognostics

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7655
Author(s):  
Seokgoo Kim ◽  
Joo-Ho Choi ◽  
Nam H. Kim
Keyword(s):  
Health Management ◽  
System Level ◽  
Prognostics And Health Management ◽  
Health Index ◽  
System Operation ◽  
Component Level ◽  
Industrial Systems ◽  
Multiple Components ◽  
Challenges And Opportunities ◽  
Essential Function

Prognostics and health management (PHM) has become an essential function for safe system operation and scheduling economic maintenance. To date, there has been much research and publications on component-level prognostics. In practice, however, most industrial systems consist of multiple components that are interlinked. This paper aims to provide a review of approaches for system-level prognostics. To achieve this goal, the approaches are grouped into four categories: health index-based, component RUL-based, influenced component-based, and multiple failure mode-based prognostics. Issues of each approach are presented in terms of the target systems and employed algorithms. Two examples of PHM datasets are used to demonstrate how the system-level prognostics should be conducted. Challenges for practical system-level prognostics are also addressed.

scholarly journals PHM Survey : Implementation of Diagnostic Methods for Monitoring Industrial Systems

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Abdenour Soualhi ◽  
Bilal Elyousfi ◽  
Yasmine Hawwari ◽  
Kamal Medjaher ◽  
Guy Clerc ◽  
...  
Keyword(s):  
Life Cycle ◽  
Health Management ◽  
Fault Isolation ◽  
Diagnostic Methods ◽  
Condition Based Maintenance ◽  
Prognostics And Health Management ◽  
Isolation And Identification ◽  
Industrial Systems ◽  
Industrial Sectors ◽  
Processing Step

The modernization of industrial sectors involves the use of complex industrial systems and therefore requires condition based maintenance. This one aims at increasing the operational availability and reducing the life-cycle while increasing the reliability and life expectancy of industrial systems. This maintenance also called predictive maintenance is a part of an emerging philosophy called PHM ‘Prognostics and Health Management’. In this paper, the PHM will be emphasized on the existing diagnostic methods used for fault isolation and identification. This depicts an important part of the PHM as it exploits the data given by the signal-processing step and its output is treated by the prognostic part. The diagnostic is mainly classified in three categories that will be highlighted in this paper.

scholarly journals Present Status and Future Growth of Advanced Maintenance Technology and Strategy in US Manufacturing

2020 ◽  
Vol 7 (3) ◽  
Author(s):  
Xiaoning Jin ◽  
Brian A. Weiss ◽  
David Siegel ◽  
Jay Lee
Keyword(s):  
Health Management ◽  
Manufacturing Firms ◽  
Future Trends ◽  
Prognostics And Health Management ◽  
Present Level ◽  
Maintenance Strategies ◽  
Manufacturing Enterprises ◽  
Specific Factors ◽  
The Impact ◽  
Future Growth

The goals of this paper are to 1) examine the current practices of diagnostics, prognostics, and maintenance employed by United States (U.S.) manufacturers to achieve productivity and quality targets and 2) to understand the present level of maintenance technologies and strategies that are being incorporated into these practices. A study is performed to contrast the impact of various industry-specific factors on the effectiveness and profitability of the implementation of prognostics and health management technologies, and maintenance strategies using both surveys and case studies on a sample of U.S. manufacturing firms ranging from small to mid-sized enterprises (SMEs) to large-sized manufacturing enterprises in various industries. The results obtained provide important insights on the different impacts of specific factors on the successful adoption of these technologies between SMEs and large manufacturing enterprises. The varying degrees of success with respect to current maintenance programs highlight the opportunity for larger manufacturers to improve maintenance practices and consider the use of advanced prognostics and health management (PHM) technology. This paper also provides the existing gaps, barriers, future trends, and roadmaps for manufacturing PHM technology and maintenance strategy.

scholarly journals A Review of Prognostics and Health Management Applications in Nuclear Power Plants

2020 ◽  
Vol 6 (3) ◽  
Author(s):  
Jamie Coble ◽  
Pradeep Ramuhalli ◽  
Leonard Bond ◽  
J. Wesley Hines ◽  
Belle Upadhyaya
Keyword(s):  
Nuclear Power ◽  
Power Plants ◽  
Situational Awareness ◽  
Health Management ◽  
The State ◽  
Prognostics And Health Management ◽  
Original Design ◽  
Operating Cycle ◽  
The Us ◽  
Inspection And Maintenance

The US operating fleet of light water reactors (LWRs) is currently undergoing life extensions from the original 40- year license to 60 years of operation. In the US, 74 reactors have been approved for the first round license extension, and 19 additional applications are currently under review. Safe and economic operation of these plants beyond 60 years is now being considered in anticipation of a second round of license extensions to 80 years of operation. Greater situational awareness of key systems, structures, and components (SSCs) can provide the technical basis for extending the life of SSCs beyond the original design life and supports improvements in both safety and economics by supporting optimized maintenance planning and power uprates. These issues are not specific to the aging LWRs; future reactors (including Generation III+ LWRs, advanced reactors, small modular reactors, and fast reactors) can benefit from the same situational awareness. In fact, many small modular reactor (SMR) and advanced reactor designs have increased operating cycles (typically four years up to forty years), which reduce the opportunities for inspection and maintenance at frequent, scheduled outages. Understanding of the current condition of key equipment and the expected evolution of degradation during the next operating cycle allows for targeted inspection and maintenance activities. This article reviews the state of the art and the state of practice of prognostics and health management (PHM) for nuclear power systems. Key research needs and technical gaps are highlighted that must be addressed in order to fully realize the benefits of PHM in nuclear facilities.

scholarly journals A Framework for System Design Optimization Based on Maintenance Scheduling With Prognostics and Health Management

2013 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Health Management ◽  
Operating Conditions ◽  
Maintenance Scheduling ◽  
Prognostics And Health Management ◽  
Maintenance Strategies ◽  
Design Component ◽  
Trade Offs ◽  
Design Variables ◽  
System Design Optimization ◽  
High Level

The optimal maintenance scheduling of systems with degrading components is highly coupled with the design of the system and various uncertainties associated with the system, including the operating conditions, the interaction of different degradation profiles of various system components, and the ability to measure and predict degradation using prognostics and health management (PHM) technologies. Due to this complexity, designers need to understand the correlations and feedback between the design variables and lifecycle parameters to make optimal decisions. A framework is proposed for the high level integration of design, component degradation, and maintenance decisions. The framework includes constructing screening models for rapid design evaluation, defining a multi-objective robust optimization problem, and using sensitivity studies to compare trade-offs between different design and maintenance strategies. A case example of power plant condenser is used to illustrate the proposed framework and advise how designers can make informed comparisons between different design concepts and maintenance strategies under highly uncertain lifecycle conditions.

Maintenance for Improving Manufacturing Equipments Availability Using Prognostics and Health Management

2011 ◽  
Vol 199-200 ◽  
pp. 543-547 ◽  
Author(s):  
Jiang Long ◽  
Wei An Jiang
Keyword(s):  
Health Monitoring ◽  
Health Management ◽  
Cost Effective ◽  
Prognostics And Health Management ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Key Issues ◽  
Reliability And Availability

There is a growing need for improving manufacturing equipments availability to achieve high levels of productivity. As a key complement to CBM and RCM, PHM is becoming a key enabler for achieving cost effective ultra-reliability and availability in tomorrow’s manufacturing equipments at an affordable cost. Based on traditional maintenance strategies, key issues pertaining to PHM application to manufacturing equipments, including health monitoring, diagnostics and prognostics, are discussed in this paper. As an example, a method for dynamic MFOP based maintenance strategy optimization using PHM and RUL estimation is presented.

A Review on Prognostics and Health Management : 2013~2018

2019 ◽  
Vol 19 (1) ◽  
pp. 68-84 ◽  
Author(s):  
Hyun Su Sim ◽  
Jun-Gyu Kang ◽  
Yong Soo Kim
Keyword(s):  
Health Management ◽  
Prognostics And Health Management

Remaining useful life estimation: a review on stochastic process-based approaches

2020 ◽  
Vol 14 ◽  
Author(s):  
Dangbo Du ◽  
Jianxun Zhang ◽  
Xiaosheng Si ◽  
Changhua Hu
Keyword(s):  
Stochastic Process ◽  
Health Management ◽  
Remaining Useful Life ◽  
Future Trends ◽  
Prognostics And Health Management ◽  
Inverse Gaussian ◽  
Life Estimation ◽  
Inverse Gaussian Process ◽  
Pros And Cons ◽  
Useful Life

Background: Remaining useful life (RUL) estimation is the central mission to the complex systems’ prognostics and health management. During last decades, numbers of developments and applications of the RUL estimation have proliferated. Objective: As one of the most popular approaches, stochastic process-based approach has been widely used for characterizing the degradation trajectories and estimating RULs. This paper aimed at reviewing the latest methods and patents on this topic. Methods: The review is concentrated on four common stochastic processes for degradation modelling and RUL estimation, i.e., Gamma process, Wiener process, inverse Gaussian process and Markov chain. Results: After a briefly review of these four models, we pointed out the pros and cons of them, as well as the improvement direction of each method. Conclusion: For better implementation, the applications of these four approaches on maintenance and decision-making are systematically introduced. Finally, the possible future trends are concluded tentatively.

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