scholarly journals Bayesian maintenance decision optimisation based on computing the information value from condition inspections

2021 ◽  
pp. 1748006X2097812
Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González
Keyword(s):  
Decision Making ◽  
Structural Integrity ◽  
Fatigue Cracking ◽  
Cost Effective ◽  
Offshore Structures ◽  
Information Value ◽  
Bayesian Decision ◽  
Maintenance Strategies ◽  
Optimal Maintenance ◽  
Maintenance Decision

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.

Optimization of equal-cycle maintenance strategy considering imperfect preventive maintenance

2021 ◽  
pp. 095440892110638
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Action Unit ◽  
Cost Rate ◽  
Equipment Reliability ◽  
Optimal Maintenance ◽  
Important Means ◽  
Maintenance Decision

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

scholarly journals Research on Multi-Attribute Decision-Making in Condition-Based Maintenance for Power Transformers Based on Cloud and Kernel Vector Space Models

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 5948
Author(s):  
Renxi Gong ◽  
Siqiang Li ◽  
Weiyu Peng
Keyword(s):  
Decision Making ◽  
Vector Space ◽  
Assessment System ◽  
Condition Based Maintenance ◽  
Power Transformers ◽  
Maintenance Strategy ◽  
Cloud Models ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
Vector Space Models

Decision-making for the condition-based maintenance (CBM) of power transformers is critical to their sustainable operation. Existing research exhibits significant shortcomings; neither group decision-making nor maintenance intention is considered, which does not satisfy the needs of smart grids. Thus, a multivariate assessment system, which includes the consideration of technology, cost-effectiveness, and security, should be created, taking into account current research findings. In order to address the uncertainty of maintenance strategy selection, this paper proposes a maintenance decision-making model composed of cloud and vector space models. The optimal maintenance strategy is selected in a multivariate assessment system. Cloud models allow for the expression of natural language evaluation information and are used to transform qualitative concepts into quantitative expressions. The subjective and objective weights of the evaluation index are derived from the analytic hierarchy process and the grey relational analysis method, respectively. The kernel vector space model is then used to select the best maintenance strategy through the close degree calculation. Finally, an optimal maintenance strategy is determined. A comparison and analysis of three different representative maintenance strategies resulted in the following findings: The proposed model is effective; it provides a new decision-making method for power transformer maintenance decision-making; it is simple, practical, and easy to combine with the traditional state assessment method, and thus should play a role in transformer fault diagnosis.

scholarly journals Optimal Maintenance Decision Method for Urban Gas Pipelines Based on as Low as Reasonably Practicable Principle

2018 ◽  
Vol 11 (1) ◽  
pp. 153 ◽  
Author(s):  
Peng Zhang ◽  
Guojin Qin ◽  
Yihuan Wang
Keyword(s):  
Decision Making ◽  
Risk Reduction ◽  
Cost Benefit Analysis ◽  
Optimization Theory ◽  
Cost Benefit ◽  
Maintenance Cost ◽  
Gas Pipelines ◽  
City Gas ◽  
Optimal Maintenance ◽  
Maintenance Decision

In the transportation process of urban gas pipelines, there are various uncontrollable risks and uncertainties possibly leading to the failure of gas pipelines and thereby serious consequences, such as city gas shutdown, nearby casualties, and environmental pollution. To avoid these hazards, numerous studies have been performed in identifying and evaluating the occurrence of risks and uncertainties to pipelines. However, discussions on risk reduction and other maintenance work are scarce; therefore, a scientific method to guide decision making is non-existent, thereby resulting in excessive investment in maintenance and reduced maintenance cost of other infrastructures. Therefore, the as low as reasonably practicable (ALARP) principle combined with optimization theory is used to discuss pipeline maintenance decision-making methods in unacceptable regions and ALARP regions. This paper focuses on the analysis of pipeline risk reduction in the ALARP region and proposes three optimization decision models. The case study shows that maintenance decision making should consider the comprehensive impact of maintenance cost to reduce risk and loss cost caused by pipeline failure, and that the further cost–benefit analysis of measures should be performed. The proposed pipeline maintenance decision-making method is an economical method for pipeline operators to make risk decisions under the premise of pipeline safety, which can improve the effectiveness of the use of maintenance resources.

scholarly journals Development of Fuzzy Multi Criteria Decision Making Method for Selection of Optimum Maintenance Alternative

2012 ◽  
pp. 206-211
Author(s):  
Arun Nagar
Keyword(s):  
Decision Making ◽  
Manufacturing Industry ◽  
Model Development ◽  
Cost Effective ◽  
Multi Criteria Decision Making ◽  
Maintenance Strategy ◽  
Fuzzy Decision ◽  
Optimal Maintenance ◽  
Frame Work ◽  
Selection Of

An optimal maintenance strategy is a key support to production in the manufacturing industry. This paper present a fuzzy approach based on Multi-Criteria Decision-Making (MCDM) methodology for selecting the optimal maintenance alternative. In the present work the criticality of each equipment is achieved by ranking (based on production loss).It is very difficult to quantify the qualitative factors in exact numerical value. These factors can be expressed in the linguistics terms which can be translated into mathematical measures by using fuzzy sets & system theory. The study problem to develop a fuzzy decision approach to rank the suitable maintenance alternative. The objective of this paper is to propose fuzzy frame work based on fuzzy number theory to solve optimal maintenance alternative which includes decision criteria analysis, weight assessment & decision model development. The approach can aid formulating a cost-effective maintenance strategy for a manufacturing plant.

Maintenance Strategies for Sewerage Systems

1987 ◽  
Vol 19 (3-4) ◽  
pp. 603-611
Author(s):  
A. S. Câmara ◽  
D. Pereira ◽  
A. Fonseca ◽  
S. Sequeira
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Urban Areas ◽  
Maintenance Strategies ◽  
Periodic Inspection ◽  
Societal Needs ◽  
Hydraulic Conditions ◽  
Maintenance Decision ◽  
Timely Topic ◽  
Sewerage Network

The problem of decaying sewerage systems is a timely topic in many urban areas, due to its importance to societal needs and to the large amounts of capital expeditures needed to bring the concerned systems to an adequate level of serviceability. Thus, there is a need for better maintenance decision-making related to periodic inspection and cleaning, repair, rehabilitation or replacement of the equipment. In this paper, an approach offering integrated solutions to upgrade such systems, taking into account existing and foreseen structural and hydraulic conditions, is presented. The methodology relies upon a heuristic algorithm scheduling maintenance events. An application to the Almada sewerage network illustrates the method. Future improvements including the use of statistical maintenance theoretic concepts and artificial intelligence approaches are also discussed.

The State-of-the-Art in Structural Integrity Management: A Review and Proposed Data-Driven Approach

2019 ◽  
Author(s):  
YeongAe Heo
Keyword(s):  
Risk Management ◽  
Environmental Conditions ◽  
Structural Integrity ◽  
State Of The Art ◽  
Cost Effective ◽  
Offshore Structures ◽  
Data Driven ◽  
Future Research ◽  
Network Systems ◽  
Management Approaches

Abstract Probabilistic risk-based approaches have been used for cost-effective structural design and maintenance guidelines. The effectiveness of these provisions, however, has yet to be adequately validated. Also, current risk management approaches are hardly adaptable to changes in operational and environmental conditions as well as structural properties over the service life of structures. As the need and demand of real-time monitoring systems have increased dramatically for high-value and high-risk facilities such as offshore structures particularly, it is important to discuss directions for future research to advance the risk-based management approaches by utilizing the invaluable “big-scale” field data obtained from sensor network systems. Therefore, knowledge gaps in the current state-of-the-art structural risk management approaches are discussed in this paper. Subsequently, a novel risk management framework is presented in this paper integrating physics-based data into a data-driven decision model. The proposed decision framework will improve system adaptability to future performance requirements due to changing operational and environmental conditions and will be applicable to any structural systems instrumented by sophisticated SHM systems such as complex naval and marine systems.

scholarly journals Rough Set Theory-Based Multi-Class Decision Making Framework for Cost Effective Treatment of COVID-19 Suspected Patients

2021 ◽  
Author(s):  
Sandip Majumder ◽  
Samarjit Kar
Keyword(s):  
Decision Making ◽  
Effective Treatment ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Real Life ◽  
Cost Effective ◽  
Bayesian Decision ◽  
Cost Effective Treatment ◽  
The Cost

Abstract Rough set theory approximates a concept by the three regions, namely positive, negative and boundary regions. The three regions enable us to derive three types of decisions, namely acceptance, rejection and deferment. The deferment decision gives us the flexibility to further examine suspicious objects and reduce misclassification. The main objective of this paper is to provide a cost effective treatment of a patient suspect to COVID-19 positive by using multiclass three-way decision making with the help of Rough set theory. The cost-based analysis of three-way decisions brings the theory closer to real-world applications where costs play an indispensable role. In our approach, we extend the three-way decision to three-way multiclass decision, offering a new framework of multiple classes. Different types of misclassification errors are treated separately based on the notation of loss function from Bayesian decision theory. In our cost sensitive classification approach, the cost caused by a different kind of error are not assumed to be equal. Finally, a numerical example for a cost effective treatment of a patient with COVID-19 disease is considered to demonstrate the practicability and efficacy of the developed idea in real-life applications.

Maintenance Decision-Making Under the Cost Criterion and the Competing Risks Approach

2017 ◽  
Vol 9 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Rima Oudjedi Damerdji ◽  
Myriam Noureddine
Keyword(s):  
Decision Making ◽  
Competing Risks ◽  
Preventive Maintenance ◽  
Optimal Operation ◽  
Maintenance Cost ◽  
Delay Model ◽  
Maintenance Policy ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
Optimal Maintenance Policy

The definition of an appropriated maintenance policy appears essential to avoid the system failures and ensure its optimal operation, while taking into account the criteria of availability and costs. This article deals with a maintenance decision-making for a system subject to two competing maintenance actions, corrective and preventive maintenance. To define this situation of dependent competing risks, the Alert Delay model seems well suited because it involves the notion of a delivered alert before system failure in order to perform preventive maintenance. This paper proposes an approach including both an extension of the Alert Delay model where the considered system follows an exponential distribution, and the total maintenance cost assessment of the system. These two concepts provide an aid decision-making to select the optimal maintenance policy based on the minimal cost. The proposed approach is validated in a computer system localized in a real industrial enterprise.

scholarly journals Application of Fieldbus Technology to Enable Enhanced Actuator Control of Automated Inspection for Offshore Structures

2019 ◽  
Vol 2 (3) ◽  
pp. 29
Author(s):  
Aman Kaur ◽  
Michael Corsar ◽  
Bingyin Ma
Keyword(s):  
Structural Integrity ◽  
Cost Effective ◽  
Offshore Structures ◽  
Inspection System ◽  
Automated Inspection ◽  
Destructive Testing ◽  
Control Units ◽  
Inspection Systems ◽  
Human Operators ◽  
Actuator Control

Due to extreme environmental loadings and aging conditions, maintaining structural integrity for offshore structures is critical to their safety. Non-destructive testing of risers plays a key role in identifying defects developing within the structure, allowing repair in a timely manner to mitigate against failures which cause damage to the environment and pose a hazard to human operators. However, in order to be cost effective the inspection must be carried out in situ, and this poses significant safety risks if undertaken manually. Therefore, enabled by advancements in automation and communication technologies, efforts are being made to deploy inspection systems using robotic platforms. This paper proposes a distributed networked communication system to meet the control requirements of a precision rotary scanner for inspection of underwater structures aimed at providing a robotic inspection system for structural integrity in an offshore environment. The system is configured around local control units, a fieldbus network, and a supervisory control system accounting for the environment conditions to provide enhanced control of actuators for automated inspection of offshore structures.

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