Opportunistic perfect preventive maintenance policy in presence of masked data

In this paper, the maintenance optimization problem of multi-component system is considered. It is assumed that the exact cause of system failure might be masked. That is, the exact cause of failure is unknown, and we only know that it belongs to a set called mask set. Both opportunistic perfect preventive maintenance (OPPM) and perfect corrective maintenance are considered. Threshold of OPPM and inter-inspection interval are considered as decision parameters which are optimized using long-run cost rate criteria. The applicability of the proposed maintenance policy is investigated using an illustrative example.

Development of Structural Risk-Based Underwater Inspection (RBUI) based on Agile and Dynamic Inspection Data Analysis

Mubadala Petroleum operates offshore platforms in a southern Makassar Straits that needs to be periodically inspected. The cost for the inspection is massive due to the high cost of mobilization and demobilization of vessels including crew and equipment. In response of a new approach to reduce cost, a Risk-Based Underwater Inspection (RBUI) methodology is developed. This RBUI purpose is to reduce the inspection interval of the offshore platform, from every 2 years to a longer period. There are existing RBUI methodologies, which are already developed and implemented in other companies. Purpose of this paper is to develop further detailed and more accurate RBUI methodology based on data analysis and the agile development method. Offshore platforms condition is dynamic and always changing from time to time. In this paper, a new methodology and approach is developed using data analysis from previous inspection data. This dynamic inspection data is analysed using agile methodology to respond offshore platforms dynamic condition. The inspection data that considered are related to offshore platform strength and remaining life, such as; corrosion, marine growth, scour, cathodic protection, joint close visual inspection (CVI), and other detailed inspection methods. All collected inspection data of offshore platform conditions will produce an accurate risk register of the platform. Thus, accurate risk register will give the best inspection interval time, considering its safety and economical benefit. From the RBUI analysis using this method, inspection interval can be deferred from 2 (two) years to range of 4-9 years, depending on the condition and risk of the platform. The operating cost of each platform also reduced up to US$ 425,000 per year.

Transitioning from Time Based to Risk Based Inspection (RBI) for Static Equipment at Banyu Urip Facility

This paper discusses the strategies, implementation, and benefits of the transition from time-based to risked-based inspections (RBI) for static equipment in Banyu Urip Facility. A review of facility integrity programs was conducted to pressure vessel (PV) and tank inspection results to assess the effectiveness of associated integrity programs. This data was utilized as a basis for risk assessment to determine if an RBI program was fit for the purpose to extend inspection intervals for static equipment. The implementation of RBI in Banyu Urip Facility began with carbon steel pressure vessels and tanks. These static equipment were jointly evaluated by multiple functions to ensure seamless execution and timely analysis of data. Inspection packages were developed, which considered applicable degradation mechanisms to select representative test points and ensure consistency for future inspection. All inspection packages consisted of general arrangement drawings depicting vessels and associated test points. Once reviewed and approved, this information was documented in Asset Integrity Management Software to streamline future campaigns. Each vessel was independently evaluated for RBI suitability including the identification of credible failure mode and details of potential future inspection requirements. Outcomes of this evaluation were transmitted into fit for risk inspection interval that provides cost reduction opportunity while maintaining equipment integrity. Furthermore, it also help to drive focus toward higher criticality equipment. This approach is also being considered for other types of static equipment, including piping and PSV.

Condition-based Maintenance Optimization for Gamma Deteriorating Systems under Performance-based Contracting

With the further development of service-oriented, performance-based contracting (PBC) has been widely adopted in industry and manufacturing. However, maintenance optimization problems under PBC have not received enough attention. To further extend the scope of PBC’s application in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model to maximize the profit and improve system performance at a relatively low cost under PBC. In the proposed CBM model, the first inspection interval has been considered in order to reduce the inspection frequency and the cost rate. Then, a particle swarm algorithm (PSO) and related solution procedure are presented to solve the multiple decision variables in our proposed model. In the end, a numerical example is provided so as to demonstrate the superiority of the presented model. By comparing the proposed policy with the conventional ones, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted in order to research the effect of corrective maintenance cost and time required for corrective maintenance on optimization policy. A comparative study is given to illustrate the necessity of distinguishing the first inspection interval or not.

Inspection interval optimization of aircraft landing gear component based on risk assessment using equivalent initial flaw size distribution method

The nondestructive inspection interval is highly related with both system reliability and maintenance burden. Conventional inspection interval decision criteria based on the deterministic crack propagation analysis could require too much frequent inspection or sometimes occur structural failure owing to the rapid crack propagation than expected. The stochastic crack growth analysis method was proposed to compensate for the shortcomings of the deterministic analysis. This research studied the crack growth of aircraft landing gear components based on the equivalent initial flaw size distribution algorithm, and then we assessed failure risk. The calculated risk was validated using Monte-Carlo simulation, and finally, the optimum inspection interval was proposed to satisfy the US Airforce risk management criteria.

Application and Limitation of Safety Valves Inspection Codes in China

Safety valves are important devices to protect system by relieving pressure in oil refining and chemical equipment. According to API 576-2017 and API 510, the inspection interval for safety valves should not be more than 10 years. Also, TSG ZF001–2006 in China specifies the inspection interval for safety valves is only 1 year. However, the maintenance interval for petrochemical units normally is 3∼5 years, which thus results in the inconsistency between its inspection interval and the maintenance interval. This study firstly conducts contrastive analysis about the difference of major regulations and standards for safety valves inspection between China and API standards, and then performs thorough investigation of the operational management and regulation about the extension for safety valves inspection interval in the typical Chinese petrochemical enterprises. Besides, the failure modes and risk level of safety valves are investigated by quantitative analysis of 44,692 safety valves engineering application data in oil refining and chemical plants based on Risk-Based Inspection (RBI) technology. The result indicates that the overall risk level of safety valves is low, as the percentage of safety valves with a high-risk level is less than 1%, and the accident rate caused by safety valves failure is less than 0.005%. In addition, this study analyzes the limitations of specification such as TSG ZF001–2006 in terms of safety valves inspection and the application of regulation extension. Based on above analysis, the specifications and standards about safety valves should be revised and introduce the RBI technology to extend the inspection interval.

Condition-based Maintenance Optimization for Gamma Deteriorating Systems under Performance-Based Contracting

As a new form of support contract, performance-based contracting (PBC) has been extensively adopted in industry and manufacturing recent years. However, maintenance optimization problems under PBC have not received enough attention. In order to further expand the application of PBC in the field of maintenance optimization, we investigate the condition-based maintenance (CBM) optimization for gamma deteriorating systems under PBC. Considering the repairable single-component system subject to the gamma degradation process, this paper proposes a CBM optimization model with an objective of maximizing the profit and improving system performance at a lower cost under PBC. In the proposed CBM model, first inspection interval is considered to reduce the inspection frequency and the cost. Then, a particle swarm algorithm (PSO) and related solution procedure are presented in order to solve the multiple decision variables in our proposed model. Finally, a numerical example is provided to illustrate the applicability and effectiveness of our proposed model. Through comparing the proposed policy with the conventional one, the superiority of our proposed policy is proved, which can bring more profits to providers and improve performance. Sensitivity analysis is conducted to investigate the effect of corrective maintenance cost and time required for corrective maintenance to optimization policy. Comparative study is given to illustrate the necessity of distinguishing first inspection interval and repeat inspection interval.

Inspection optimization of load-sharing systems

In this thesis, periodic inspection of a load-sharing k-out-of-n system has been studied to obtain the optimal inspection interval using the analytical and simulation approaches. The components of a load-sharing system are stochastically dependent, which makes the analysis of these systems more complex than those with independent components. In order to acquire the optimal inspection interval for the system, two models have been developed to study load-sharing systems with Tampered Failure Rate (TFR) and Cumulative Exposure (CE). The former considers only the current load of the components and the later accounts for the history of load. Various load intensities are examined to study the effects of this parameter on each model. It is observed that as the load intensity increases, the system needs more frequent inspections. The results also reveal that a system with the CE model requires a shorter inspection interval in comparison to that with the TFR model.

Inspection optimization of load-sharing systems

In this thesis, periodic inspection of a load-sharing k-out-of-n system has been studied to obtain the optimal inspection interval using the analytical and simulation approaches. The components of a load-sharing system are stochastically dependent, which makes the analysis of these systems more complex than those with independent components. In order to acquire the optimal inspection interval for the system, two models have been developed to study load-sharing systems with Tampered Failure Rate (TFR) and Cumulative Exposure (CE). The former considers only the current load of the components and the later accounts for the history of load. Various load intensities are examined to study the effects of this parameter on each model. It is observed that as the load intensity increases, the system needs more frequent inspections. The results also reveal that a system with the CE model requires a shorter inspection interval in comparison to that with the TFR model.