Effective health age resulting from metabolic condition changes and lifestyle maintenance program

Condition based maintenance (CBM) improves decision-making performances for a maintenance program through machinery condition monitoring. Therefore, it is a key step to trace machinery health condition for CBM. In this paper, a novel method is proposed to establish a health evaluation index named automatic evaluation index (AEI) and its corresponding dynamic threshold using Wavelet Packet Transform (WPT) and Hidden Markolv Model (HMM). In this process, WPT is used to decompose signal into detail signals and exhibits prominent gear fault features. In addition, HMM employed here is to recognize two concerned states of gear in the whole life validation, including normal gear state and early gear fault state. It is also important to build a dynamic threshold to differentiate the two states automatically. The proposed dynamic threshold not only renews by itself according to the history values of AEI but also easily and automatically detects occurrence of gear early fault. Finally, a set of whole life time data ending in gear failure is used to verify the proposed method effectively. Further, some related parameters included in this method are discussed and the obtained results show that condition monitoring performance of the proposed method is excellent in detection of gear failure.

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Architecting “Maintenance Program” for Piping and Pipe Support

Volume 1: Plant Operations, Maintenance, Engineering, Modifications, Life Cycle and Balance of Plant; Nuclear Fuel and Materials; Radiation Protection and Nuclear Technology Applications ◽

10.1115/icone21-16674 ◽

2013 ◽

Author(s):

Koichi Tsumori ◽

Yoshizumi Fukuhara ◽

Hiroyuki Terunuma ◽

Koji Yamamoto ◽

Satoshi Momiyama

Keyword(s):

Nuclear Power ◽

Power Plants ◽

Nuclear Industry ◽

Maintenance Management ◽

3D Cad ◽

Cad System ◽

Nuclear Disaster ◽

Safety Regulations ◽

Maintenance Program

A new inspection standard that enhanced quality of operating /maintenance management of the nuclear power plant was introduced in 2009. After the Fukushima Daiichi nuclear disaster (Mar. 11th 2011), the situation surrounding the nuclear industry has dramatically changed, and the requirement for maintenance management of nuclear power plants is pushed for more stringent nuclear safety regulations. The new inspection standard requires enhancing equipment maintenance. It is necessary to enhance maintenance of not only equipment but also piping and pipe support. In this paper, we built the methodology for enhancing maintenance plan by rationalizing and visualizing of piping and pipe support based on the “Maintenance Program” in cooperating with 3D-CAD system.

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Using Risk Based Maintenance Optimization RBMO to Save Costs

10.2118/208026-ms ◽

2021 ◽

Author(s):

Khaled Ahmed Farouk Mohamed

Keyword(s):

Risk Mitigation ◽

Critical Item ◽

Cost Benefit ◽

Maintenance Cost ◽

Maintenance Strategy ◽

Critical Systems ◽

Risk Matrix ◽

Monetary Value ◽

Maintenance Program ◽

Systems Maintenance

Abstract Maintenance is a crucial pillar in plant integrity and availability. Saving money in maintenance should be established without affecting the asset's integrity. Based on this, the core of work is to maximize the maintenance return on investment (ROI). Maintenance ROI is the ratio between invested money in maintenance to mitigated risks due to maintenance actions. The objective is to minimize maintenance cost while maximizing assets integrity and availability. RBMO starts with ‘Maintenance Criticality Assessment’ (MCA) at unit/system level to define high (20 % of systems that represent 80% of risks), medium (20% of systems that represent 15% of risks), and low critical systems (60% of systems that represent only 5% of risks). Based on system criticality, a dedicated risk assessment is implemented to evaluate risks at tag level to define the worst maintenance action/s. High critical systems’ maintenance programs are developed using ‘Reliability-Centered Maintenance’ (RCM). Medium critical system maintenance program is developed using ‘Failure Mode, Effects and criticality analysis’ (FMECA). "Maintenance strategy for Low Critical item" guideline document is developed to define the best maintenance strategy for low critical units. All risks are evaluated using the standard ADNOC risk matrix. The risk is converted to monetary value in $ to evaluate maintenance actions using a formula. A special program was developed to facilitate MCA evaluation for each system and represent risk as monetary value using ADNOC Risk Matrix taking into consideration the redundancy and demand on a system during operation. MCAs were completed for all ADNOC Onshore Assets, see results below. Optimization starts by evaluating maintenance programs for low critical systems to save costs where low critical systems represent 50% to 60% of total systems in ADNOC Onshore. Based on this the total number of work orders has decreased by 6856, which is equivalent to saving $1M annually. In parallel, RCMs are conducted on high critical systems. Risk mitigation calculator in $ value was developed and embedded in the RCM information sheet to calculate cost benefit from implementing maintenance programs that were developed. RBMO is a systematic and traceable methodology to minimize maintenance cost and at the same time maximize system integrity and availability. This work showed the importance of reviewing the low critical systems’ maintenance program, as a first step in RBMO after implementing MCA, where low critical systems represent 50% to 60% of total assets and only 5% of total risks. ADNOC Onshore developed a dedicated guideline document "Maintenance Strategy for Low Critical Item" to facilitate decision making for proper maintenance strategy for low critical systems. Adding RCM risk mitigation calculator to RCM to calculate RCM cost benefit.

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