Inspection Frequency Research Articles

The Value of Negative Urinary Dipstick Tests for Haematuria in Patients Undergoing Surveillance for Low-grade Ta Urothelial Cancer: A Two-stage Prospective Clinical Study in 524 Patients

Background and objectiveThe risk of first recurrence beyond 5 yr for patients with low-grade (LG) Ta non–muscle-invasive bladder cancer (NMIBC) is low enough to consider discontinuing cystoscopic surveillance at that point. However, a positive urinary dipstick test for haematuria (UDH) during and beyond the period of cystoscopic surveillance can disrupt plans to cease surveillance because the association between UDH positivity and recurrence in LG Ta NMIBC is unknown. In a two-stage study, we evaluated this association and explored the role of UDH negativity in predicting the absence of recurrence. MethodsBecause of previously demonstrated changes in recurrence patterns over time, two prospective cohorts were assessed: an “exploratory” cohort (January 2007–March 2008) and a “validation” cohort (November 2017–August 2018). UDH was performed before flexible cystoscopy. Patient, operative, and surveillance data have been recorded prospectively using standard pro forma sheets since 1978 in our institution. Only patients with primary LG Ta pTa NMIBC were included for analysis. Key findings and limitationsWe assessed 231 patients in the exploratory group and 293 in the validation group. The proportion of smokers (67% vs 70%; p = 0.5) and mean follow-up (72.2 vs 79.9 mo; p = 0.2) were similar between the groups. The recurrence rate was higher in the exploratory group (19% vs 11%; p = 0.009), as was the UDH positivity rate (37% vs 11%; p < 0.001). The specificity and negative predictive value were 64% and 83% in the exploratory group, and 90% and 90%, respectively, in the validation group. These values increased further for the subgroup with solitary primary tumours the subgroup without recurrence for 3 yr. Conclusions and clinical implicationsUDH negativity has a high probability of being associated with the absence of recurrence in small LG Ta NMIBC and could be an inexpensive adjunct during surveillance. Ongoing validation, which started in 2019, is being performed in a now-nationalised Scottish protocol in which UDH replaces cystoscopy in years 2 and 4 for patients in the low-risk group. Patient summaryWe investigated the accuracy of a dipstick test for blood in the urine for patients undergoing surveillance for low-grade noninvasive bladder cancer. We found that a negative dipstick test result was highly associated with the absence of tumour recurrence, particularly for patients with the lowest risk. These findings have been introduced into a national protocol designed to reduce the frequency of telescopic inspection of the bladder during surveillance to reduce the burden for patients.

The frequency of inspections of economic facilities to reduce risks

The frequency of inspections of economic facilities to reduce risks

Linking farmers to markets: Assessing small-scale farmers' preferences for an official phytosanitary regime in the Kyrgyz Republic

Small-scale farmers are integral to Kyrgyz agriculture, contending with challenges such as low productivity, market entry barriers, and financial constraints. Most of these farmers are hindered by phytosanitary restrictions preventing direct exports of their products. Granting smallholders direct access to regional markets could significantly enhance their economic prospects. However, the specific policy measures that can encourage smallholders to participate in the official phytosanitary regime remain unclear. This study employs a randomized conjoint experiment, creating a hypothetical policy to measure the preferences of Kyrgyz fruit farmers regarding an official phytosanitary regime. Presenting choice sets with two randomly generated policy alternatives and an opt-out option, we collect data from 378 farmers across five villages. Each policy alternative comprises six attributes: (1) type of service provision, (2) provision of production inputs, (3) provision of interest-free loans, (4) provision of market information, (5) provision of phytosanitary inspection frequency, and (6) annual fees. The results reveal that attributes such as market information, interest-free loans, and production inputs—particularly virus-free seedlings—significantly increase farmers’ participation probability in systematization. However, farmers prefer the private sector as service provider over the government. Additionally, higher annual fees negatively impact the favorability of systematization. Overall, farmers express a preference for the hypothetical policy and are willing to pay at least 14,000 Kyrgyz som to participate in systematization. This study addresses the practical challenges faced by Kyrgyz farmers in meeting stringent phytosanitary standards, indicating the potential of a systematization policy to enhance market access. It lays the groundwork for future research investigating the economic impacts of specific policy attributes for Kyrgyz farmers.

Обоснование оптимальной периодичности проведения плановых проверок противопожарного состояния социально значимых объектов органами ГПН МЧС России

Проведен анализ статистической информации о пожарах и их последствиях в целях установления зависимости количества пожаров от периодичности проведения плановых проверок. Получены математические модели, описывающие зависимость числа пожаров на социально значимых объектах защиты от периодичности плановых проверок их противопожарного состояния. Разработана методика обоснования оптимальной периодичности проведения плановых проверок противопожарного состояния социально значимых объектов защиты органами ГПН. Обоснована оптимальная периодичность проведения таких проверок. The purpose of the paper was to analyze statistical information on fires in order to establish the dependence of the number of fires at socially important facilities on the frequency of scheduled inspections as well as to develop a methodology for justifying the optimal frequency of scheduled inspections of their fire safety condition by the State Fire Supervision bodies of EMERCOM of Russia. As a result of the conducted research, mathematical models were initially obtained to determine the number of fires at socially important facilities depending on the time that has elapsed since their last inspection, as well as to determine the number of fires at these facilities depending on the frequency of scheduled inspections. The scientific novelty of the paper lies in the fact that the original methodology for substantiating the optimal frequency of scheduled inspections of the fire safety condition of socially important facilities has been clarified and tested for the first time on a scientific basis. The practical significance of the paper lies in the fact that the initially obtained data allow us to substantiate on a scientific basis the following: the optimal frequency of scheduled inspections of the fire-fighting condition of socially important facilities; the necessity to assign these facilities to the appropriate risk category, depending on the optimal frequency of their scheduled inspection; the necessary number of personnel of the State Fire Supervision bodies of EMERCOM of Russia for timely and qualitative inspection of supervised facilities. The results of the paper also make it possible to substantiate the expediency of introducing amendments in accordance with Part 6 of Clause 25 of Federal Law No. 248-FZ dated 31 July 2020 to the “Regulations on Federal State Fire Supervision” approved by Decree of the Government of the Russian Federation No. 290 dated 12 April 2012, in order to establish a new method for justifying the frequency of planned control (supervisory) measures in relation to socially important facilities and their assignment to the appropriate risk category.

Defect detection of spherical heads by time-of-flight diffraction

Inspecting spherical heads with ultrasonic time-of-flight diffraction (TOFD) is restricted in quantitative accuracy, since the travel path of lateral wave is not along with the structured surface. Meanwhile, a layered dead zone related to lateral wave generates at the near-surface zone and is greater than that in flat plate. In this paper, the vertical inner-wall defects outside and inside the dead zone in the girth weld of spherical head are detected and located by establishing the quantitative relationship between concerned signals (diffracted longitudinal wave or mode-converted wave) and defect depths. Focusing on the aluminum alloy spherical head with 60.0 mm curvature radius and 20.0 mm thickness, the positioning errors of defects with depths of 15.0 mm and 5.0 mm in simulation and experiments are no more than 9.6 % at 5 MHz inspection frequency. Finally, we verify the theoretical relationship by combining simulated and experimental images, analyze the variation of the dead zone in spherical head with the scanning position under different curvature radii and discuss the influence of curvature radius on location accuracy.

Best practices for implementing biosafety inspections in a clinical laboratory: Evidence from a multi-site experimental study.

To explore the key components when designing best practice inspection interventions, so as to induce high compliance with safety guidelines for laboratory workers. Five key components of an inspection intervention, identified from a focus group discussion, were used as the attributes of a discrete choice experiment (DCE). In the DCE, participants were presented with two hypothetical scenarios and asked to choose the scenario in which they were more willing to comply with the laboratory safety guidelines. Data were collected from 35 clinical laboratories in seven healthcare institutes located in Chengdu, China. In total, 188 laboratory workers completed the DCE. The collected data were analyzed using conditional logit regression and latent class analysis. Five key attributes were identified as the most important ones to best ensure laboratory safety: the inspector, the inspection frequency, the inspection timing, the communication of the inspection outcome, and a follow-up with either a reward or a punishment. By investigating the laboratory workers' responses to the attributes, properly implementing the five attributes could improve the workers' compliance from 25.86% (at the baseline case) to 74.54%. Compliance could be further improved with the consideration of the laboratory workers' heterogeneous reactions. In this study, two classes of workers, A and B, were identified. Compliance percentages for Classes A and B would be improved to 85.48% and 81.84%, respectively, when the key attributes were properly implemented for each class. The employment type and the size of the laboratory could be used to predict class membership. The findings indicate the importance of an employee-centered approach in encouraging a worker's compliance. This approach also supports the design of tailored interventions by considering the laboratory workers' heterogeneous responses to the interventions.

INCREASING THE RELIABILITY OF ELECTRIC POWER FACILITIES THROUGH THE USE OF UNMANNED AERIAL VEHICLES

The issue of increasing the reliability of the operation of facilities in the energy system of Ukraine is being considered. It is shown that the electric power complex of Ukraine has significant levels of depreciation, which, in turn, leads to an increase in the number of emergency conditions, an increase in the time of post-accident recovery, and as a result, a decrease in the reliability of power supply in general. Accordingly, the loss of electrical energy will be the more, the higher the wear of systems and equipment. Maintenance costs must also increase to keep the power system within regulatory requirements for high wear equipment. Outdated and worn-out equipment leads to an increase in energy losses, an increase in the cost of maintaining the state of working capacity and, as a result, financial losses. Reduction of electricity losses on worn-out equipment cannot be carried out instantly and radically due to the impossibility of the Ukrainian economy to upgrade power equipment in a short time. The authors propose to reduce financial losses by reducing the cost of maintaining existing equipment. And it is proposed to do this through the use of modern technologies, namely the use of UAVs for monitoring power equipment. It is proposed to pay attention to only one parameter, namely the uninterrupted operation of power facilities. Thus, for network companies monitoring the technical condition of lines and control of isolation means is the main type of monitoring. Density of failures of equipment operation is built in graphical form, where a normalized number of inspections is presented, based on reliability requirements. The number of inspections is calculated according to regulatory documents. The paper shows that the graph of the change in the probability of failure-free operation is not straight. Therefore, the frequency of inspections cannot use the frequency that is not related to the wear and tear of the equipment. And to maintain the level of reliability, it is necessary to increase the number of inspections to ensure the standard level of reliability. Therefore, the authors propose to reduce costs with an increased number of inspections using UAVs. The above economic calculations show the high economic efficiency of such a proposal.

Operational Risk Management: Optimal Inspection Policy

Major banks around the world lost nearly $210 billion during the period of 2011–2016 due to operational risk events. To mitigate the severe consequences that can arise from such events, the Basel Regulatory Committee has mandated that financial institutions worldwide conduct inspections on operational risk. In light of the importance of operational risk and its current regulation in the industry, this paper proposes a continuous-time principal-agent model that explores the optimal inspection policy of a financial firm (principal) and the effort of its employees (agent) to reduce the occurrence of risk events. First, we characterize the optimal inspection strategy under two commonly used policies in practice, namely random and periodic policies. This characterization reveals the conditions for two different modes of inspection (effort inducement and error correction), as well as the nuanced interactions among the inspection frequency, the penalty charged for errors, and the wage paid to employees. Next, by comparing random and periodic policies, we find that the random policy outperforms the periodic policy if and only if the inspection cost is high. Furthermore, we propose a hybrid policy that strictly dominates the random policy and weakly dominates the periodic policy, suggesting that a proper reduction of the random element in the inspection policy, in the manner of our proposed hybrid policy, can always improve its performance. Finally, we examine the complete information benchmark (without moral hazard), supplemental mitigation strategies, and numerical studies to provide further insights and show the robustness of our main findings. This paper was accepted by Vishal Gaur, operations management. Supplemental Material: The e-companion is available at https://doi.org/10.1287/mnsc.2021.00322 .

Automating daily inspection for Expressways using anomaly detection model

Because of the high speed at which vehicles travel on highways, even small irregularities on the road surface can lead to serious accidents. It is important to conduct daily visual inspections to detect these abnormalities at an early stage and to repair them quickly. We are considering replacing a part of visual inspection with automatic classification using image recognition. Automating inspections will make it possible to increase inspection frequency and expected to reduce the variation in quality due to the skill of inspectors. In this paper, we report on an AI-based inspection system and evaluation results using actual highway driving video captured by an in-vehicle camera.

Аналитическая методика обоснования оптимальной периодичности плановых проверок противопожарного состояния производственных и складских зданий

The purpose of the work is to analyze the statistical information about fires to establish the dependence of the number of fires in the industrial and warehouse buildings on the frequency of scheduled inspections and, on this basis, to develop a methodology for justifying the optimal frequency of scheduled inspections of their fire safety status by the federal state fire supervision authorities of the Ministry of Emergency Situations of Russia. For the first time, the mathematical models were obtained to determine the number of fires at industrial and warehouse protection facilities depending on the time elapsed since the last inspection, as well as to determine the number of fires at these protection facilities depending on the frequency of their scheduled inspections. The scientific novelty of the work lies in the fact that for the first time, on a scientific basis, an original method for substantiating the optimal frequency of scheduled fire safety inspections of industrial and warehouse protection facilities was developed and tested. The data obtained allows to substantiate on a scientific basis: the optimal frequency of scheduled inspections of the fire safety condition of industrial and warehouse buildings; the belonging of these objects of protection to the appropriate risk category, depending on the required frequency of their scheduled inspection; the required number of personnel of the federal state fire supervision bodies of the Ministry of Emergency Situations of Russia for timely and high-quality inspection of the supervised protection objects. The results of the work also make it possible to justify the need to amend the Regulations on the Federal State Fire Supervision, approved by Decree of the Government of the Russian Federation dated April 12, 2012, № 290, in terms of establishing an alternative method to the Federal Law dated July 31, 2020, № 248-FZ for justifying the frequency of scheduled control (supervision) activities in relation to the objects of control and their assignment to the appropriate risk category.

Probability of detection curve for the automatic visual inspection of steel bridges

AbstractThe damage tolerant design philosophy is based on periodical inspections and provides safe bridge operation preventing fatigue cracks from growing up to a critical size. It is possible to optimize the management costs of a bridge throughout its life by designing the inspection frequency, which depends on the capabilities of the inspection method. However, such optimization requires knowledge about the performance of inspections that are envisioned to take place during the use of the bridge. Regular visual inspections is the most frequently applied type of inspection of bridge structures. Recent advances in computer vision technologies provide a strong basis for the development of automatic damage detection systems that can support regular visual inspection, thus increasing the reliability of the inspection. Several automatic crack detection systems have been developed in the past years. However, the performances of such systems have not been evaluated in the way as for traditional non‐destructive inspection methods, i.e. in terms of probability of detection curves and detectability limits. This restricts the applicability of automatic visual inspections for inspection planning and damage tolerant design. This paper proposes an encoder‐decoder neural network for segmentation of cracks on images of steel bridges. A probability of detection curve is calculated for this neural network.

Automated IBEX crawler for PAUT inspection for in-service ferromagnetic assets

In order to guarantee the safety of the gas production plants, Air Liquide conducts NDT inspections regularly closely following the assets’ maintenance plans. One high criticality asset is the Pressure Swing Adsorber (PSA), found in the last stages of the hydrogen production process, where product purification takes place. These adsorbers are pressure vessels and need to be inspected for hydrogen enhanced fatigue cracks. Conventional inspection would require stopping site operation, building scaffolding for the totality of the height, which depending on design can be up to 15 meters tall and 6 meters in diameter, grinding of the inspection surface to remove the paint, conducting the inspection manually by 2 operators, and repainting once inspections are concluded. Commonly, inspection plans for these high-criticality assets outline a high inspection frequency, resulting in elevated costs associated with logistics, personnel and time and monetary resources required to plan and execute each inspection. This necessity is what drove Air Liquide R&amp;D and INTACT to create a partnership and develop an automated crawler that can be deployed on in-service ferromagnetic assets for Phased Array Ultrasonic Testing (PAUT) inspection, using Total Focusing Method (TFM) with INTACT proprietary imaging and software. The robot, named IBEX Crawler, is deployed at the lowest part of the vessel and controlled safely at the ground level by a single operator. It is able to change directions to accommodate the inspection of longitudinal and circular welds. It includes an encoding system that enables operators to exactly locate any indications present. The crawler’s payload includes an electronic 128 elements PAUT board controlled by fiber optics, laser tracking and machine vision camera. The inspection results are analyzed by 3D reconstruction and managed by mechanical integrity assessments proprietary technology, calculating the stability of the found indications and using fracture mechanics and Fitness-For-Service (FFS) to estimate the residual lifetime of the indications and in consequence, the interval between inspections to develop a more accurate maintenance plan. Today INTACT’s IBEX crawlers travel worldwide between Air Liquide sites to ensure the integrity of the assets.

Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources.

Distributions of methane emission rates originating from oil and gas production facilities are highly skewed and span 6-8 orders of magnitude. Traditional leak detection and repair programs have relied on surveys with handheld detectors at intervals of 2 to 4 times a year to find and fix emissions; however, this approach may lead unintended emissions to be active for the same interval independently of their magnitude. In addition, manual surveys are labor intensive. Novel methane detection technologies offer opportunities to further reduce emissions by quickly detecting the high-emitters, which account for a disproportionate fraction of total emissions. In this work, combinations of methane detection technologies with a focus of targeting high-emitting sources were simulated in a tiered approach for facilities representative of the Permian Basin, a region with skewed emission rates where emissions above 100 kg/h account for 40-80% of production site-wide total emissions, which include sensors on satellites, aircraft, continuous monitors, and optical gas imaging (OGI) cameras, with variations on survey frequency, detection thresholds, and repair times. Results show that strategies that quickly detect and fix high-emitting sources while decreasing the frequency of OGI inspections, which find the smaller emissions, achieve higher reductions than quarterly OGI and, in some cases, reduce emissions further than monthly OGI.

Kalypso Autonomous Underwater Vehicle: A 3D-Printed Underwater Vehicle for Inspection at Fisheries

Abstract In fish farms, a major issue is the net cage wear, resulting in fish escapes and negative impact on fish quality, due to holes and biofouling of the nets. To minimize fish losses, fisheries utilize divers to inspect net cages on a weekly basis. Aquaculture companies are looking for ways to maximize profit, and reducing maintenance costs is one of them. Kefalonia Fisheries spend 250,000 euros yearly on diver expenses for net cages maintenance. This work is about the design, fabrication, and control of an inexpensive autonomous underwater vehicle (AUV) intended for inspection in net cages at Kefalonia Fisheries S.A. in Greece. Its main body is 3D printed, and its eight-thruster configuration grants it six degrees-of-freedom. The main objective of the vehicle is to limit maintenance costs by increasing inspection frequency. The design, fabrication, electronic components, and software architecture of the AUV are presented. In addition, the forces affecting kalypso, mobility realization, navigation, and modeling are quoted along with a flow simulation and the experimental results. The proposed design is adaptable and durable while remaining cost-effective, and it can be used for both manual and automatic operations.

The Role of Surveillance Inspections in Reducing False-Positives of SARS-CoV-2 Omicron Variants during the COVID-19 Epidemic.

This study aims to assess the effectiveness of surveillance inspections conducted by the provincial health committee in Quanzhou city during a COVID-19 outbreak in reducing false-positive results in SARS-CoV-2 RT-PCR assays. The team conducted on-site inspections of laboratories that participated in mass screening, recording any violations of rules. The positive cases in five rounds of mass screening were 23, 173, and 4 in Licheng District, Fengze District, and Luojang District, respectively. The false-positive rates in the five rounds of mass screening were 0.0099%, 0.0063%, 0.0018%, 0.0006%, and 0%, respectively. The study also recorded that the number of violations in the seven selected laboratories was 36, 68, 69, 42, 60, 54 and 47. The corresponding false-positive rates were 0.0012%, 0.0060%, 0.0082%, 0.0032%, 0.0060%, 0.0027%, and 0.0021%, respectively. The study found a positive correlation between false-positive rates and the number of violations (r = 0.905, P=0.005), and an inverse correlation between false-positive rates and the frequency of surveillance inspections (r = -0.950, P < 0.001). Daily surveillance inspection in laboratories can remind laboratories to strictly comply with standard procedures, focus on laboratory quality control, and reduce the occurrence of false-positive cases in SARS-CoV-2 nucleic acid tests to some extent. This study recommends that government decision-making departments establish policies and arrange experts to conduct daily surveillance inspections to improve laboratory quality control.

Failure Mode and Effect Analysis (FMEA) of a Taurus 60 Gas Turbine Power Plant System (GTPPS), in Mowe, Nigeria

Failure Mode and Effect Analysis (FMEA) is an approach used for maintenance system reliability analysis. FMEA is applied to the Taurus 60 Gas Turbine Power Plant System (GTPPS). The unexpected failures with the associated maintenance costs are major problems in most power plants. In this study, critical components of the Taurus 60 gas turbine power plant were identified. Twenty-five sub-assemblies were identified and the probable failure modes of the main sub-assemblies. Failure analysis and the Risk Priority Numbers (RPN) of the critical sub-assemblies were determined using failure modes and effect analysis method. Failure analysis and the Risk Priority Numbers (RPN) of the critical sub-assemblies were determined using failure modes and effect analysis method. Based on criticality analysis, six (6) critical sub-assemblies were identified. These are fuel gas supply, air filter package, air trap package, gearbox, compressor rotor assembly and fuel injector with criticality numbers 12.5, 20.83, 20.83, 20.83, 16.67 and 20.83 respectively. The failure analysis for these critical sub-assemblies specified the failure modes, failure effects, maintenance tasks, frequency of inspection and strategies. The ranges of the Risk Priority Number (RPN) for the components of fuel gas supply, air filter package, air trap package, gearbox, compressor rotor assembly and fuel injector were 54-126, 60-90, 75-90, 72-84, 36-112 and 90-120 respectively. The critical sub-assemblies should be given close attention in terms of monitoring, routine checks which can be monitored using prepared checklists. The semi- critical and non- critical assemblies should not be neglected either.

Evolutionary Game and Simulation Analysis of Participating Subjects in Remediation of Heavy Metal Contaminated Cultivated Land under the Ladder Multiple Supervision Model

The heavy metal pollution of cultivated land in China is severe, requiring remediation. Introducing third-party governance subjects representing market resources is inevitable to realize the specialization and socialization of cultivated land remediation. However, due to the public nature of cultivated land, the confusion about participating parties’ responsibilities and difficulty coordinating interests restrict the expected effect of cultivated land remediation. To this end, a three-party evolutionary game model among the grassroots government, governance enterprises, and supervisory enterprises is constructed and virtually simulated, taking into account the influence of random checks by the higher-level government. We found that the reward and punishment mechanism of the grassroots government, the frequency of random inspection by the higher-level government, and the amount of deduction will influence the strategy selection of the participating parties. Strengthening the awareness of the responsibility of the grassroots government, optimizing the incentive system, establishing a regular spot-check system, and improving the cost of non-compliance by enterprises can effectively resolve conflicts of interest among the participants. The study results have practical significance for further enhancing the remediation efficiency of heavy metal-contaminated cultivated land.

Investigation of electrically isolated capacitive sensing skins on concrete to reduce structure/sensor capacitive coupling

Damage to bridges can result in partial or complete structural failures, with fatal consequences. Cracks develop in concrete infrastructure from fatigue loading, vibrations, corrosion, or unforeseen structural displacement. Effective long-term monitoring of civil infrastructure can reduce the risk of structural failures and potentially reduce the cost and frequency of inspections. However, deploying structural health monitoring technologies for crack detection on bridges is expensive, especially long-term, due to the density of sensors required to detect, localize, and quantify cracks. Previous research on soft elastomeric capacitors (SECs) has shown their viability for low-cost monitoring of cracks in transportation infrastructure. However, when deployed on concrete for strain monitoring, a structure/sensor capacitive coupling exists that may cause a significant amplification in the signal collected from the SEC sensor. This work provides a detailed experimental study of electrically isolating capacitive sensing skins for concrete structures to reduce the structure/sensor capacitive coupling of an electrically grounded sensor. The study illustrates that the use of rubber isolators effectively decreases the capacitive coupling between concrete, which inherently has capacitive properties, and sensors such as the SEC that utilize capacitance measurements. In addition, the required thickness of isolation for accurate strain monitoring using the SEC with geometry described in the paper is investigated and better strain correlation is observed between the rubber of isolation thickness 0.30 mm and 0.64 mm with rubber of isolation of approximately 0.40 mm having the best response. Tests were conducted on small-scale concrete beams, and results were validated on full-scale reinforced concrete bridge decks recently taken out of service. This study demonstrates that with proper isolation material, the SEC can accurately transduce strain from concrete within a 10 error for strain levels beyond 25 .

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.

Condition-based pavement management systems accounting for model uncertainty and facility heterogeneity with belief updates

Due to the tighter budget for pavement management, schedules of inspection activities should be jointly optimized with the maintenance and reconstruction (M&R) plans for pavement systems. Conducting inspections every year is unnecessary and will decrease the budget for M&R activities, while infrequent inspections may lead to suboptimal M&R planning due to the lack of accurate information. This paper presents a methodology for jointly optimizing the inspection scheduling and M&R planning for pavement systems, considering model uncertainty and facility-specific heterogeneity. The problem is defined as a Partially Observable Markov Decision Process (POMDP) model, accounting for the tradeoff between the information value and inspection costs. Moreover, a statistical learning method is used to update the prediction of pavement conditions using the collected inspection data and, eventually, improve the condition-based decisions. This “belief update” process can gradually reduce the model uncertainty as the dataset size increases. We demonstrate the proposed stochastic optimization framework through a numerical example with a system of fifty heterogenous pavement facilities under a combined budget for inspection and M&R activities. Several managerial insights and implications are discussed. For example, the optimal inspection frequencies are less sensitive to the budget; and the agency should perform fewer reconstructions and more rehabilitations when the budget is limited.