Inspection Schedule Research Articles

Inducing Environmental Disclosures: A Dynamic Mechanism Design Approach

This paper studies the design of voluntary disclosure regulations for a firm that faces a stochastic environmental hazard. The occurrence of such a hazard is known only to the firm. The regulator, if finding a hazard, collects a fine and mandates the firm to perform costly remediation that reduces the environmental damage. The regulator may inspect the firm at any time to uncover the hazard. However, because inspections are costly, the regulator also offers a reward to the firm for voluntarily disclosing the hazard. The reward corresponds to either a subsidy or a reduced fine, depending on whether it is positive or negative. Thus, the regulator needs to dynamically determine the reward and inspection policy that minimizes expected societal cost in the long run. We model this problem as a dynamic adverse selection problem with costly state verification in continuous time. Despite the complexity and generality of this setup, we show that the optimal regulation policy follows a very simple cyclic structure, which we fully characterize in closed form. Specifically, the regulator runs scheduled inspections periodically. After each inspection, the reward level decreases over time until a subsequent inspection takes place. If a hazard is not revealed, the reward level is reset to a high level, restarting the cycle. In contrast to the reward level, the mandated remediation level is constant over time. Nonetheless, when subsidies are not allowed in the industry, we show that the regulator should dynamically adjust this remediation level, which then acts as a substitute for a subsidy. Our analysis further reveals that optimal inspection frequency increases not only when the inspection accuracy decreases, but also when the penalty for not disclosing the hazard increases.

Recursive Inspection Games

We consider a sequential inspection game where an inspector uses a limited number of inspections over a larger number of time periods to detect a violation (an illegal act) of an inspectee. Compared with earlier models, we allow varying rewards to the inspectee for successful violations. As one possible example, the most valuable reward may be the completion of a sequence of thefts of nuclear material needed to build a nuclear bomb. The inspectee can observe the inspector, but the inspector can only determine if a violation happens during a stage where he inspects, which terminates the game; otherwise the game continues. Under reasonable assumptions for the payoffs, the inspector’s strategy is independent of the number of successful violations. This allows to apply a recursive description of the game, even though this normally assumes fully informed players after each stage. The resulting recursive equation in three variables for the equilibrium payoff of the game, which generalizes several other known equations of this kind, is solved explicitly in terms of sums of binomial coefficients. We also extend this approach to nonzero-sum games and “inspector leadership” where the inspector commits to (the same) randomized inspection schedule, but the inspectee acts legally (rather than mixes as in the simultaneous game) as long as inspections remain.

Formation of maintenance economic safety enterprise system

The article examines the issues of economic security. The operation of enterprises is being implemented in a volatile market environment, which requires a comprehensive assessment of not only the individual factors affecting the operation of the enterprise, but also encourages the need to develop a comprehensive system for the enterprise to ensure economic security. The purpose of this study is to examine the theoretical and methodological approaches to assessing and ensuring the economic security of the enterprise, the development of a mechanism to ensure the economic security of the enterprise. Measures to ensure the safety of personnel suggest preventive work with the personnel, training personnel of the security services division, formation of personnel reserve of security personnel, the organization of work with new employees, reducing staff turnover. Preventive measures to minimize include activities not directly related to the activities of security units, but to minimize losses of commercial enterprise in the course of maintenance operations: control of inventories; control document; scheduled and unscheduled inspections during the reception of the goods; selection and organization of the movement control risk goods. Development of guidelines and regulations involves the planning of a clear legal regulation of all processes for the operation of commercial facility, potentially dangerous from the point of view of any commercial activity or threats to the security risks. The success of the activities is largely determined by the speed and accuracy of enterprise responses to emerging threats, where a key determinant of the effectiveness of business, is to create a system to ensure the economic security of the enterprise.

Need and Opportunities for a ‘Plan B’ in Rail Track Inspection Schedules

Track inspection is purposely performed to recover tracks from defects and damage and eliminate potential safety hazards. It is scheduled through an exhaustive process that usually integrates many disciplines such as optimization, statistics, risk management, etc. Spending so much of a monetary and an emotional investment in an original schedule (referred to as master schedule hereafter) that the scheduler wants to deliver might be a good excuse not to develop a solid ‘Plan B’. Plan B here refers to scheduler responses or a contingency plan when the master schedule does not go as expected. It is found that there is often low to moderate probability of a crisis occurring when a schedule is executed in a real environment. Nevertheless, its impact can leave transportation services to the mercy of the disruption as shown by the Christmas 2014 incident where a huge volume of passengers using King's Cross and Paddington services experienced both inconvenience and discomfort due to engineering delays and train disruption. Thus, this paper aims to discuss the potential of considering ‘Plan B’ or contingency plan if incidents arise that were not expected during track inspection schedule execution. Benefits, general guidelines and relevant strategies for creating a contingency plan are also discussed. We highlight the rationale to support the claim that an original schedule of track inspection jobs should be adapted to respond to a new context e.g. inspection vehicle machine breakdown, new inspection requests, man-made hazards, terrorist attack, extreme weather, climate change, etc. It is however proposed to develop an appropriate set of performance measure that is used to guide rescheduling in track inspection due to financial, equipment inventory, manpower, safety regulations, time and spatial constraints.

Integrated Inspection Scheduling and Maintenance Planning for Infrastructure Systems

AbstractOperation and maintenance of an infrastructure system rely on information collected on its components, which can provide the decision maker with an accurate assessment of their condition states. However, resources to be invested in data gathering are usually limited and observations should be collected based on their Value of Information (VoI). Assessing the VoI is computationally intractable for most applications involving sequential decisions, such as long‐term infrastructure maintenance. In this article, we propose an approach for integrating adaptive maintenance planning based on Partially Observable Markov Decision Process (POMDP) and inspection scheduling based on a tractable approximation of VoI. Two alternative myopic approaches, namely pessimistic and optimistic, are introduced, and compared theoretically and by numerical examples.

The performance of the Shewhart sign control chart for finite horizon processes

In many manufacturing environments, the production horizon of the same part code between two consecutive set-ups should be limited to a few hours or shifts. When 100 % sampling is not possible, on-line quality control on a quality characteristic should be immediately started by means of a control chart. In this paper, we investigate the statistical performance of a nonparametric (distribution-free) Shewhart Sign (SN) control chart for monitoring the location of a quality characteristic in a production process with a finite horizon and a small number of scheduled inspections. The observations taken from the process are assumed to be continuous random variables. By implementing a SN control chart, any model assumption about the distribution of observations is needless to guarantee a nominal in-control (IC) performance: after each process set-up, this overcomes the important problem of lack of information about the distribution of the observations collected for the quality characteristic to be monitored. An extensive simulation study is conducted to compare the statistical performance of the distribution-free Shewhart SN control chart to the normal theory-based Shewhart Student’s t control chart: several types of distributions of observations and different numbers of scheduled inspections are considered to show the advantages related to the implementation of the Shewhart SN control chart. An illustrative example presents the implementation of the Shewhart SN control chart on a real data set collected in a beverage company.

Remaining Creep Life Assessment of Service Superheat Tube Boiler

The demand of remaining life assessment of the boilers arises from technical, economic, and legal reasons. Creep is major damage mechanism of primary superheat tube boiler during prolong operation at high temperature and pressure in a water tube boiler. This paper presents the calculation method for the remaining life assessment due to creep damage. The service-exposed primary superheat tube made of 2.25Cr-1Mo steels. During scheduled inspection, wall thickness measurement, metallographic investigation by replica technique, design data and operating condition were used to estimate the remaining life in the form of creep damage accumulation rate calculated from life fraction using Larson-Miller Parameter. The results indicate that the primary superheat tubes satisfy in extension service life. By attaining an accurate and timely discussion of the results, the engineer can manage the maintenance and inspection schedule for the critical part in the boiler.

Developing an Inspection Optimization Model Based on the Delay-Time Concept

Infrastructures are considered as important facilities required for every country and society to be able to work properly. Aging and deterioration of such structures during their lifetime are a major concern both for maintenance researchers in the academic world and for the practitioners. This concern is mainly because the deterioration increases the maintenance costs dramatically and lowers the reliability, availability, and safety of the structural system. Preventive maintenance and inspection activities are the most usual means for keeping the structure in a good condition. This paper utilizes the concept of delay-time for developing the optimal inspection policy for deteriorating structures. In the proposed stochastic model, discrete times of inspection activities are taken as the decision variables of an optimization problem, in a way that the obtained aperiodic (nonuniform) inspection schedule minimizes the total downtime ratio of the structure. To illustrate the model capabilities, various numerical examples are solved and results are compared with the traditional periodic (uniform) inspection policies. The results indicate the substantial reduction in system downtime due to the wisely planned inspection schedule and the appropriate utilization of delay-time concept, which is indeed a powerful framework for inspection optimization problems.

Optical Fiber Sensors for Aircraft Structural Health Monitoring.

Aircraft structures require periodic and scheduled inspection and maintenance operations due to their special operating conditions and the principles of design employed to develop them. Therefore, structural health monitoring has a great potential to reduce the costs related to these operations. Optical fiber sensors applied to the monitoring of aircraft structures provide some advantages over traditional sensors. Several practical applications for structures and engines we have been working on are reported in this article. Fiber Bragg gratings have been analyzed in detail, because they have proved to constitute the most promising technology in this field, and two different alternatives for strain measurements are also described. With regard to engine condition evaluation, we present some results obtained with a reflected intensity-modulated optical fiber sensor for tip clearance and tip timing measurements in a turbine assembled in a wind tunnel.

Cause and effect oriented sewer degradation evaluation to support scheduled inspection planning.

Managing the subsurface urban infrastructure, while facing limited budgets, is one of the main challenges wastewater utilities currently face. In this context targeted planning of inspection and maintenance measures plays a crucial role. This paper introduces a cause and effect oriented sewer degradation evaluation approach to support decisions on inspection frequencies and priorities. Therefore, the application of logistic regression models, to predict the probability of failure categories as an alternative to the prediction of sewer condition classes, was introduced. We assume that analysing the negative effects resulting from different failure categories in extension to a condition class-based planning approach offers new possibilities for targeted inspection planning. In addition, a cross validation process was described to allow for a more accurate prediction of sewer degradation. The described approach was applied to an Austrian sewer system. The results show that the failure category-based regression models perform better than the conventional condition class-oriented models. The results of the failure category predictions are presented with respect to negative effects the failure may have on the hydraulic performance of the system. Finally, suggestions are given for how this performance-oriented sewer section evaluation can support scheduled inspection planning.

A myopic policy for optimal inspection scheduling for condition based maintenance

In this paper, we propose a decision policy for condition-based maintenance that schedules inspections according to the current health of the system, optimized myopically over the next inspection interval. In traditional condition-based maintenance practices, regular inspections are considered a given requirement. Most measurements, however, confirm that the machine in question is in good working order and that no maintenance is necessary. We consider the possibility that there are savings to be had in the number of inspections that are undertaken. As such, we use a proportional hazards model for risk of failure and a Markovian process to model the system covariates. The cost and time of inspections are incorporated into our model, and an optimal decision for one interval is made. This process can be repeated for each decision point, resulting in a decision policy that produces an inspect-or-replace result and an optimal time for the next inspection. Applied over the life of an asset, this policy can be used as a complete condition monitoring program supporting evidence based asset management.

Gamma process with recursive MLE for wear PDF prediction in precognitive maintenance under aperiodic monitoring

Effective degradation prediction under aperiodic monitoring can assist to save inspection costs and schedule maintenance for the realistic manufacturing systems. In this paper, an extended time-/condition-based framework will be proposed to predict the Probability Density Function (PDF) of unobservable degradation under aperiodic condition monitoring. Furthering our earlier work of indirect degradation estimation via a mixed time-/condition-based approach, a stage-based Gamma process is designed and implemented for the prediction of degradation PDF where a recursive Maximum Likelihood Estimation (MLE) algorithm deduced from the conventional MLE algorithm is able to update the modeling parameters based on each aperiodic monitoring interval. The effectiveness of our extended framework is tested on the tool wear experiments in an industrial high speed computer numerical control milling machine, which can achieve an acceptable prediction performance with the average error of predicted bounds less than 15.0% as well as the average accuracy more than 94.3%.

Single-stage Kanban system with deterioration failures and condition-based preventive maintenance

Despite the fact that the fields of pull type production control policies and condition-based preventive maintenance have much in common contextually, they have evolved independently up to now. In this investigation, an attempt is made to bridge the gap between these two branches of knowledge by introducing the single-stage Kanban system with deterioration failures and condition-based preventive maintenance. The formalism of continuous time Markov chains is used to model the system and expressions for eight performance metrics are derived. Two important, from a managerial perspective, constrained optimization problems for the proposed model are defined where the objective is the simultaneous optimization of the Kanban policy, the preventive maintenance policy and the inspection schedule under conflicting performance criteria. Multiple instances of each optimization problem are solved by means of the augmented Lagrangian genetic algorithm. The results from the optimization trials coupled by the results from extensive numerical examples facilitate the thorough investigation of the system’s behaviour.

Generalized capital investment planning of oil-refineries using MILP and sequence-dependent setups

Due to quantity times quality nonlinear terms inherent in the oil-refining industry, performing industrial-sized capital investment planning (CIP) in this field is traditionally done using linear (LP) or nonlinear (NLP) models whereby a gamut of scenarios are generated and manually searched to make expand and/or install decisions. Though mixed-integer nonlinear (MINLP) solvers have made significant advancements, they are often slow for large industrial applications in optimization; hence, we propose a more tractable approach to solve the CIP problem using a mixed-integer linear programming (MILP) model and input–output (Leontief) models, where the nonlinearities are approximated to linearized operations, activities, or modes in large-scaled flowsheet problems. To model the different types of CIP's known as revamping, retrofitting, and repairing, we unify the modeling by combining planning balances with scheduling concepts of sequence-dependent changeovers to represent the construction, commission, and correction stages explicitly in similar applications such as process design synthesis, asset allocation and utilization, and turnaround and inspection scheduling. Two motivating examples illustrate the modeling, and a retrofit example and an oil-refinery investment planning problem are also highlighted.

Degradation modeling–based remaining useful life estimation: A review on approaches for systems with heterogeneity

Prognostics and health management has drawn increasing attention and gained deepening recognition and widening applications during the past decades. Due to offering guidance for sequential managements involving inspection schedule, maintenance, replacement, and spare parts ordering, remaining useful life estimation has been termed as the kernel technology of prognostics and health management and is the focus of this research in the field of reliability. Heterogeneity is widespread in the inner states of a system and its related working environments. This article provides a review on approaches for degradation modeling and remaining useful life estimation, with an emphasis on the heterogeneity in the systems. Approaches for three kinds of heterogeneity, including the unit-to-unit variability, the variability in time-varying operating conditions, and the diversity of tasks and workloads of a system during its lifetime, are summarized consecutively, and the corresponding methods are provided. Merits and drawbacks are summed up, respectively, following each approach. In addition, several possible future research directions are provided at the end of this article.

Transit stop inspection and maintenance scheduling: A GPU accelerated metaheuristics approach

Bus stops are integral elements of a transit system and as such, their efficient inspection and maintenance is required, for proper and attractive transit operations. Nevertheless, spatial dispersion and the extensive number of bus stops, even for mid-size transit systems, complicates scheduling of inspection and maintenance tasks. In this context, the problem of scheduling transit stop inspection and maintenance activities (TSIMP) by a two-stage optimization approach, is formulated and discussed. In particular, the first stage involves districting of the bus stop locations into areas of responsibility for different inspection and maintenance crews (IMCs), while in the second stage, determination of the sequence of bus stops to be visited by an IMC is modelled as a vehicle routing problem. Given the complexity of proposed optimization models, advanced versions of different metaheuristic algorithms (Harmony Search and Ant Colony Optimization) are exploited and assessed as possible options for solving these models. Furthermore, two variants of ACO are implemented herein; one implemented into a CPU parallel computing environment along with an accelerated one by means of general-purpose graphics processing unit (GPGPU) computing. The model and algorithms are applied to the Athens (Greece) bus system, whose extensive number of transit stops (over 7500) offers a real-world test bed for assessing the potential of the proposed modelling approach and solution algorithms. As it was shown for the test example examined, both algorithms managed to achieve optimized solutions for the problem at hand while there were fund robust with respect to their algorithmic parameters. Furthermore, the use of graphics processing units (GPU) managed to reduce of computational time required.

Effect of grading category on the roundness of degraded and abraded railway quartzites

Sustained train traffic loading result in rounding of sub angular ballasts and consequently reduce the interparticle friction. Reduced particle interlocking can result in instability, non-alignment of rail line and derailment and thus screening of insitu rail foundation ballasts is required during the service life to track changes in textural and mechanical properties. Two different particle grading categories (A and F) of quartzite ballasts from a Johannesburg quarry were degraded by sulphate solution and cycles of temperature. The ballasts were progressively abraded to failure in a Los Angeles abrasion device and the textural properties; average particle size (d50), flakiness index (FA), roundness (RND) and Los Angeles abrasion index (LAAI) were analyzed after each cycle of abrasion. The fouling potential of the particles generated by abrasion was classified according to the Fouling Index (FI) and Relative ballast fouling ratio (RBFR). Decrease in d50 and increase in FA with increase in number of abrasion cycles (N) were observed in the two grades of ballasts. Particle gradation and shape affected the degree of abrasion differently and with decreasing abrasion ratio, mean roundness becomes increasingly dependent on both the effect of degradation and grading. RBFR estimated the void volume occupied by fouling material and was found to be a better indicator of ballast fouling than FI. Regression equation of the ballast abrasion process based on abrasion ratio, relative ballast fouling ratio was formulated but required more data for potential application in track inspection and maintenance schedule.

Multi-stage optimization for periodic inspection planning of geo-distributed infrastructure systems

This paper develops a multi-stage optimization framework for determining periodic inspection intervals for geo-distributed infrastructure systems subject to hidden failures. We assume that the unit’s failure can only be rectified at periodic inspection when a perfect repair is carried out to restore the unit to as-good-as-new condition. For large-scale systems such as fire hydrants in a city, water supply and power transformer distribution networks in urban areas, firstly, we partition the units of a system into groups based on their pre-specified features by a clustering algorithm; then compute an optimal periodic inspection interval for each group based on the expected cost per cycle; and finally, we find the inspection schedule for the whole system that not only minimizes the total inspection and maintenance cost but also satisfies the workforce and budget resource constraints. An integer nonlinear programming formulation and a heuristics are introduced to determine the inspection schedule. The proposed approach is applied to scheduling periodic inspection of large amounts of fire hydrants in a major U.S. city.

Determining a relationship between licensing status and semi-quantitative risk score for BC dairy processing plants


 Background: Following the 2014 Gort’s Gouda Cheese Escherichia coli O157:H7 outbreak which resulted in one death and 28 illnesses, an examination of dairy processing plants (DPP) within British Columbia (BC) was undertaken. The intent of this examination was to efficiently allocate resources to ensure a lower likelihood of future outbreaks occurring in a BC DPP and to improve current knowledge regarding DPP practices. A risk-based approach to assessing inspection activities for DPPs was undertaken. As such, the purpose of the project was to create a semi-quantitative tool to assess inherent risk factors of DPPs, after which it would be used to determine appropriate inspection frequencies for these plants based on their risk scores. Finally, a comparison between provincially licensed and federally registered dairies was conducted in order to examine if there was a difference in risk between the two licensing statuses. Methods: A semi-quantitative approach was used to characterize responses to a survey (Shi, 2014) conducted by the BCCDC between August and December 2014. This survey was sent to all DPPs (n=54) operating in BC. Each survey question related to increasing information on conditions found in DPPs, after which a semi-quantitative assessment approach was used to assign a total risk inherent to each DPP due to the conditions found in the facility. The DPPs were then ranked against each other with respect to their risk scores in order to assess which facility was considered of higher risk. Facilities were grouped by their licensing status, provincially licensed or federally registered, and then compared against one another using a two variable t-test in NCSS 10. Semi-quantitative risk assessment was done using an Excel tool designed specifically for the present study. Results: Complete data was obtained for 85%(n=46) of DPPs, with an equal number of provincial and federal DPPs used in the evaluation. Dairies were ranked against one another with respect to their total risk score. A statistically significant difference (p=0.036) was found when comparing the inherent risk of provincial and federal DPPs, with federally registered dairies showing a lower total inherent risk score. Conclusion: The information obtained from this study provided the BCCDC with a standardized risk-based inspection approach. Ranking of DPPs with respect to their inherent risk also allows inspectors to gain better understanding of present day dairies and their high risk issues. This reassessment allows for the development of more efficient inspection schedules in order to effectively allocate inspection resources and to increase the ability for inspectors to capture and prevent risks which would lead to foodborne illnesses.

Computerized Preventive Maintenance Management System (CPMMS) for Haematology Department Equipments

devices and equipment have become very complex and are expected to operate under stringent environments. Equipment's should be properly maintained in order to fulfil their objectives. The signs of equipment's failure may not be apparent to clinical staff. Therefore they should be inspected periodically. Scheduled inspections help ensure the safety and efficacy of the medical equipment. A software tool is developed to implement a risk oriented prioritization of devices for equipment maintenance. First establishing an effective, efficient Computerized Preventive Maintenance Management System, collecting the data of equipments in laboratories and implement them to the system. The reports based on the inspection results, help determining a better maintenance's schedule.