Reliability and Risk Centered Maintenance: A Novel Method for Supporting Maintenance Management

da Silva, Renan Favarão; Melani, Arthur Henrique de Andrade; Michalski, Miguel Angelo de Carvalho; de Souza, Gilberto Francisco Martha

doi:10.3390/app131910605

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…By conducting thorough inspections, testing, and analysis, verification processes identify potential failure modes, degradation mechanisms, and operational deficiencies that could affect asset performance. Proactive risk management measures, such as implementing preventive maintenance programs, asset monitoring systems, and reliability-centered maintenance (RCM) strategies, help mitigate these risks and prevent unplanned downtime, equipment failures, and production losses (da Silva, et al, 2023;Liu, 2013). Additionally, by ensuring compliance with regulatory requirements and industry standards, verification processes help maintain asset integrity, reliability, and availability over time.…”

Section: Asset Performancementioning

confidence: 99%

The Impact of Technical Safety and Integrity Verification on Project Delivery and Asset Performance

Patrick Oputa Odili,

Cosmas Dominic Daudu,

Adedayo Adefemi

et al. 2024

Eng. sci. technol. j.

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The oil and gas industry operates within a stringent regulatory framework and faces inherent risks associated with complex operations. Technical safety and integrity verification processes play a critical role in ensuring compliance with regulatory standards, minimizing risks, and enhancing asset performance. This review analyzes the influence of rigorous safety and integrity verification on project timelines, cost efficiency, and overall asset performance in the oil and gas industry. Safety and integrity verification processes encompass a comprehensive assessment of design, construction, and operational phases of oil and gas projects. These processes involve rigorous inspections, testing, and verification activities to ensure that assets meet regulatory requirements and industry standards. By adhering to these processes, operators can mitigate safety risks, prevent accidents, and safeguard human lives, as well as protect the environment. Moreover, rigorous safety and integrity verification contribute to efficient project delivery by identifying potential hazards and deficiencies early in the project lifecycle. Through proactive risk assessment and mitigation, operators can address issues promptly, thereby minimizing delays and cost overruns. Additionally, adherence to safety and integrity standards instills confidence among stakeholders, investors, and regulatory authorities, fostering trust and credibility in project execution. Furthermore, the impact of technical safety and integrity verification extends beyond project delivery to asset performance throughout its operational lifespan. Assets subjected to thorough safety and integrity verification processes exhibit higher reliability, availability, and operational efficiency. By identifying and addressing potential failure points, operators can prolong asset lifespan, optimize maintenance schedules, and reduce unplanned downtime. In conclusion, rigorous safety and integrity verification processes significantly influence project timelines, cost efficiency, and overall asset performance in the oil and gas industry. By prioritizing safety and integrity throughout the project lifecycle, operators can enhance operational excellence, mitigate risks, and achieve sustainable long-term success in the dynamic and challenging oil and gas landscape. Keywords: Impact, Technical Safety, Integrity Verification, Project Delivery, Asset Performance.

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Section: Asset Performancementioning

confidence: 99%

The Impact of Technical Safety and Integrity Verification on Project Delivery and Asset Performance

Patrick Oputa Odili,

Cosmas Dominic Daudu,

Adedayo Adefemi

et al. 2024

Eng. sci. technol. j.

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“…Thus, proposals that integrate maintenance plans that are oriented toward reliability, risk, and cost have been defined [6]. In circumstances where there are no training data, tools for general mechanical functional modeling have been developed [7].…”

Section: Introductionmentioning

confidence: 99%

Improvement of Industrial Maintenance Plans through Assistance-Driven Reliability-Centered Maintenance and Case-Based Reasoning Design

Rodríguez-Padial,

Marín,

Domingo

2024

Electronics

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The present work builds on studies where the industrial market is currently characterized by a highly variable demand in terms of the quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes that are required in the production systems, the effect of which results in an increase in the fatigue of the machines that make up the production systems. However, current production systems tend to use highly communicative and sensorized cyber–physical systems; these characteristics can be used to integrate them into decision-assisted systems to improve the availability of the industrial plant. The developed assisted system focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the reliability-centered maintenance (RCM) methodology and case-based reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans that are adjusted to the real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, because they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value by incorporating fuzzy logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance by incorporating natural language instead of a numerical score, resulting in increased precision in the calculation of the risk priority number (RPN) of the new cases that are incorporated into the assisted system. On the other hand, an attempt has been made to correct two of the main inherent and recognized weaknesses in the classic RPN calculation method by implementing an appropriate mix of fuzzy logic techniques.

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Improvement of Industrial Maintenance Plans through Assisted-Driven Design RCM-CBR

Rodríguez-Padial,

Marín,

Domingo

2023

Preprint

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The present work provides continuity with studies where currently the industrial market is characterized by a highly variable demand in terms of quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes required to the production systems, the effect of which results in an increase in the fatigue subjected to the machines that make up the production systems. On the other hand, current production systems tend to use highly communicative and sensorized cyber-physical systems; these characteristics can be used to integrate them into decision-assisted systems in order to improve the availability of the industrial plant. The assisted system developed focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the Reliability Centered Maintenance (RCM) methodology and Case-Based Reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans adjusted to a real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, as they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value to it by incorporating Fuzzy Logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance, by incorporating natural language, instead of a numerical score, resulting in increased precision in the calculation of the Risk Priority Number (RPN) of the new cases incorporated into the assisted system.

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Reliability and Risk Centered Maintenance: A Novel Method for Supporting Maintenance Management

Cited by 5 publications

References 33 publications

The Impact of Technical Safety and Integrity Verification on Project Delivery and Asset Performance

The Impact of Technical Safety and Integrity Verification on Project Delivery and Asset Performance

Improvement of Industrial Maintenance Plans through Assistance-Driven Reliability-Centered Maintenance and Case-Based Reasoning Design

Improvement of Industrial Maintenance Plans through Assisted-Driven Design RCM-CBR

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