Alternative Maintenance Strategies Research Articles

Identifying environmentally sustainable pavement management strategies via deep reinforcement learning

Pavement life cycle assessments (LCAs) enable decision-makers to evaluate the environmental impact of alternative maintenance, rehabilitation, and reconstruction strategies. This paper explores the viability of deep reinforcement learning (DRL), a framework that enables agents to learn optimal actions within a given situation, to identify environmentally benign pavement management strategies. More specifically, this study utilizes proximal-policy optimization (PPO), a subtype of DRL algorithms, to identify a management strategy that minimizes the expected global warming impact of a pavement facility over its lifecycle. Through an urban Interstate case study, this paper shows that the proposed PPO algorithm identifies management strategies that are anticipated to reduce the expected global warming impact of a pavement facility over its planning horizon by 16 percent relative to traditional practice. Furthermore, the PPO algorithm is able to identify this management strategy in only 25 learning iterations, which is in stark comparison to Q-learning, a common reinforcement learning algorithm, that requires 70,000 learning iterations. The results of this work highlight the viability of DRL to integrate within complex LCA models to determine environmentally sustainable pavement management strategies.

Value of Information Analysis for the Post-Earthquake Assessment of Existing Masonry Structures—Case Studies

In the last decades, the post-earthquake assessment and strengthening of existing structures are becoming one of the most critical fields of civil engineering. Most parts of Europe, as well as many existing buildings in Croatia, are built in masonry. For that reason, the main objective of this paper is to show the role of updating knowledge in the decision analysis process of existing masonry assessment. Collecting information through condition assessment can be performed on multiple levels with different precision and quality of the obtained data. Several alternative maintenance strategies and corresponding outcomes usually represent decision problems regarding the assessment of existing structures. Regarding existing buildings, decision analysis proved the benefits of updating knowledge in the building post-earthquake assessment process. As case studies, two existing masonry buildings were selected and different assessment procedures and decision scenarios were presented. The Value of Information (VoI) analysis showed that the applied method is feasible from the perspective of owners and users, as its implementation resulted in a reduction in the overall strengthening and maintenance costs.

Pavement management system: implementing project evaluation for local road administrations

Pavement Management System (PMS) is widely used by highway and airport administrations for the rational managing of pavement networks and for identifying cost-effective maintenance strategies. Local Road Administrations (LRA) need the implementation of PMS due to the limited financial, technology and specialised human resources. To lead the LRA to a more conscious and effective use of PMS, tailored procedures and tools have to be defined considering their own potentiality and requirements. For this purpose, the Geographic Information System (GIS) can be implemented, which facilitates the collection, management and analysis of road inventory and monitoring data. GIS allows to easily display on a thematic map a wide set of geographically referenced information and to relate them with spatial and data management tools. Furthermore, customised GIS-based tools can be created to enhance pavement management and to assist the decision-making phase.This paper shows how the implementation of the project evaluation phase in a tailored PMS for several local road administrations in the center of Italy, in order to support maintenance planning and to identify the effective maintenance strategies in a long-term perspective. The process is based upon a systematically and progressive application of interconnected activities, which are supported by reference documentations and specific GIS tools. Specific GIS-based tools were developed for the set-up of road database, prioritisation, selection of properly repairs and maintenance planning. To achieve a more rational and objective maintenance planning assessments, alternative maintenance scenarios were defined using predictive models to estimate the evolution of pavement conditions over time. Long-term effectiveness of alternative maintenance strategies was established using a customised strategic index (SI).

Integrated remanufacturing, maintenance and spares policies towards life extension of a multi-component system

The decision for remanufacturing as a life extension solution for ageing equipment approaching their end of life (EOL), has marginalized the active role of the end-users and maintenance functions, by predominantly considering the remanufacturers (OEM/R) context. However, the decisions influencing the immediate core (used item/part of its component) condition like corrective maintenance actions used, and when to return a core for remanufacturing or exchange with a remanufactured part, are often the end-users responsibility. Factors like remanufacturing cost, alternative maintenance and spare strategies, introduce conflicting preferences, hence an asymmetric relationship between the end-user and the remanufacturer. This paper develops an integrated methodology to optimize maintenance, remanufacturing, and multiple spare strategies (new and remanufactured exchange) jointly, for life extension of an ageing multi-component system with dependencies. The model inculcates the asymmetric relationship to assist the end-user to derive decision support on optimal maintenance and remanufacturing strategies while minimizing the costs. A case study of an ageing turbine rotor assembly of a turbocharger with spare obsolescence demonstrates the utility of the proposed model. The study shows that the approach offers robust decision support, and further demonstrates the significance of the maintenance function and end-user influence in the remanufacturing decision making.

Pavement Deterioration Analysis for Rural Roads using HDM-4

Highway Development and Management (HDM-4) is comprised of decision-making tools used to assess the economic, social, and environmental viability of project development proposals to arrive at the best investment decisions. The entire system is built on various functions of pavement performing under numerous structural and environmental influences. The present work aims to study pavement distress and deteriorations prevailing on rural roads. At each stage, the road deterioration models predict impacts of distress at different rates and scenarios over each of the study sections. The analysis presents alternative maintenance and improvement strategies that could be implemented judiciously under scheduled or responsive routine assessments of road performance. Moreover, the analysis and output data for distress projection as obtained from HDM-4 is also validated from the existing pavement deterioration condition of the selected sections. The comparison of deterioration before and after works and the economic indicators delineated that Overlay for rural road sections is considered to be the most suitable alternative possible among others. Furthermore, the validation of the deterioration levels as predicted through HDM-4 indicates very low variation in the range of 2%-10% from the existing pavement deterioration levels. The results of this study are useful for developing pavement maintenance management strategies for rural roads network with similar characteristics.

A fuzzy DEMATEL-ANP-VIKOR analytical model for maintenance strategy selection of safety critical assets

In most industries, such as aerospace, manufacturing, transport and energy sectors, maintenance plays a vital role in improving the performance of safety critical equipment and facilities. It also helps industries achieve the largest possible efficiency, ensure workplace and environmental safety, and reduce unnecessary breakdowns and costs. Therefore, it is crucial for industries to adopt an optimal maintenance strategy for their critical systems and infrastructure. In this study, we aim to propose a novel analytical multi-criteria decision-making (MCDM) methodology for selecting the most suitable maintenance strategy in distillation units of oil refinery plants. The alternative maintenance strategies include run-to-failure (RTF), preventive maintenance (PM), condition-based maintenance (CBM), and reliability centered maintenance (RCM), which are evaluated with respect to 12 sub-criteria in three categories of economical, safety, and sustainability issues. The MCDM methodology consists of a DEMATEL-based analytic network process (ANP) method to determine the importance weights of decision criteria and a VIKOR method to rank the maintenance strategies. Also, interval type-2 fuzzy sets are used to capture uncertainty in experts’ individual judgments. Finally, a real case study is provided to show the applicability of the proposed methodology to an oil refinery plant. The results show that, thanks to advances in degradation modeling, sensor technology, and data analytics platforms, the RCM and CBM are the superior maintenance strategy for crude oil distillation systems.

Risk-informed sustainable asset management of railway tracks

Railway track infrastructure asset management is a challenging problem with added values on safety, society and environment. With railways serving as a key sustainable mode of transportation for passengers and freight, the industry is facing an increasing demand to expand its capacity, availability and speed, resulting in faster deterioration of the ageing railway track infrastructure. Given the constrained maintenance budgets and the environmental challenges posed by climate change, railway asset managers have to identify economically and environmentally justifiable track maintenance strategies without compromising on safety. To this end, this paper proposes a risk-informed approach to arrive at sustainable railway track maintenance strategies while considering the associated track maintenance costs and impacts on train operation (environmental emissions and risk of derailments). Monte Carlo simulation is employed to address data uncertainties associated with track quality data, the costs and benefits of track maintenance and train operation. The proposed approach is successfully applied to the heavy-haul railway lines in Sweden and Australia to compare some alternative maintenance strategies and identify the sustainable one.

Hybrid modelling for linear actuator diagnosis in absence of faulty data records

The advantages of condition based maintenance over alternative maintenance strategies have been widely proven. Detection, diagnosis and prognostic algorithms enable the optimization of repair schedules while avoiding breakdowns and downtimes. However, some industrial limitations complicate the development of diagnostic monitoring algorithms, particularly in scenarios with unique or non-mass-produced machines, as obtaining faulty data records is difficult.This work proposes an approach that combines the data from physical models with data-based models (or hybrid modelling) to sort out the lack of faulty data records in the condition monitoring of a linear actuator. A test rig was built and used to collect data from healthy and faulty cases (the later only used for validation purposes), in addition to a physical model that simulated nominal (healthy) and faulty conditions to generate synthetic data. Synthetic and real measured data were combined with an improved fusion by means of a feature selection method. A diagnostic model was developed and the algorithm was validated in the detection of real faulty cases. Additionally, this approach is also valuable to detect unseen operating conditions.The results obtained in this work prove the validity of hybrid models for those cases in the industry where there are physical or economical limitations to obtain data records that difficult the implementation of diagnostic algorithms.

Bright Ideas: HTM Team Realizes Major Time Savings by Devising the AEM 'Holy Grail'.

Bright Ideas: HTM Team Realizes Major Time Savings by Devising the AEM 'Holy Grail'.

Definition of a condition-based model for natural stone claddings

Nowadays, the degradation of the built environment is becoming a serious economic, cultural and environmental problem in several developed countries, after several decades of adopting an attitude of “built and let decay”. The lack of maintenance policies led to additional costs and risks for owners and increased the aesthetic degradation of our cities. In this study, a condition-based maintenance model, based on Petri nets, is used to analyse the influence of alternative maintenance strategies on the overall degradation of natural stone claddings. For this purpose, three maintenance strategies are considered: i) total replacement; ii) combination of minor intervention and total replacement; and iii) combination of cleaning operations, minor intervention and total replacement. The impact of the alternative maintenance strategies on the future performance and remaining service life of natural stone claddings is discussed. In this study, a sample of 203 natural stone claddings, located in Portugal, is analysed and the degradation of these claddings in-service condition is evaluated through in-situ inspections. Furthermore, a simplified multi-criteria analysis is carried out to evaluate the economic impact of each maintenance strategy in comparison with the increased durability achieved through its adoption. The results reveal that the adoption of other maintenance activities (minor interventions or cleaning operations) increases the operational costs, as expected, but promotes the durability of the claddings. The adoption of maintenance actions allows increasing the predicted service life of NSC (148 years for MS2 and 177 years for MS3), when compared with NSC that are not subjected to any kind of preventive maintenance (70 years).

Bortezomib Maintenance Therapy as a Standard of Care Provides Favorable Outcomes in Newly Diagnosed Myeloma Patients: A Multisite Real-Life Study

BackgroundLenalidomide and ixazomib maintenance improve long-term outcomes in newly diagnosed multiple myeloma (NDMM) patients. However, there is less evidence to support bortezomib (BTZ) maintenance therapy, and real-life data on maintenance are scarce. We investigated the efficacy and safety of BTZ maintenance therapy in NDMM. Patients and MethodsA retrospective multisite study was performed in 6 medical centers in Israel. All consecutive patients with NDMM diagnosed between January 1, 2010, and July 3, 2019, who received a BTZ-based induction, with or without an autologous transplantation, followed by BTZ maintenance therapy, were identified. Maintenance therapy was defined as BTZ (1.3 mg/m2) once every 2 weeks, administered subcutaneously alone or with dexamethasone, or weekly BTZ monotherapy. ResultsA total of 105 patients were identified, 58 of whom had received a transplant (transplant eligible) and 47 who had not (not transplant eligible). During BTZ maintenance therapy, 96% had one or more adverse event, 11.5% had grade 3 or higher adverse events, and 11.5% discontinued treatment due to toxicity. Median progression-free survival (PFS) and overall survival were 45 and 91.5 months, respectively; 4-year survival was 88%. Adverse cytogenetics was associated with worse PFS (24 vs. 46 months, P = .001). In subgroup analysis, adverse cytogenetics were associated with worse PFS (P < .001) and OS (P < .001) among transplant-ineligible but not transplant-eligible patients. ConclusionAnalysis of multisite real-life data showed that BTZ maintenance therapy is safe, well tolerated, and effective. Median PFS was similar to that reported with alternative maintenance strategies. Our findings further support its use among patients with adverse cytogenetics, it may also be relevant for patients with lenalidomide-intolerant disease.

A whole life cycle approach under uncertainty for economically justifiable ballasted railway track maintenance

Historically, railway track maintenance strategies have been based on engineering judgement taking into account available budgets and operational safety. This has led to insufficient concern of the socio-economic and environmental costs and benefits of track maintenance. Given the pressure to increase track utilisation, the ageing infrastructure of railway networks, constrained maintenance budgets, the vertical separation of the ownership and operation of railway track infrastructure and rolling stock in many countries, and concerns about the environmental impacts of transport, there is a need to implement economically justifiable maintenance strategies. To this end, this paper presents for the first time an approach to appraise the investment in railway track maintenance. The approach uses a whole life cycle cost analysis under uncertainty approach which considers the costs and benefits of track maintenance to train operators, users and the environment. Monte Carlo simulation technique is used to address data uncertainties associated with the costs and benefits of track and train operation and maintenance. The proposed approach is applied to three different route types on the UK main-line railway network to compare a number of alternative maintenance strategies. In all the three cases more economically beneficial strategies were identified in comparison to those currently adopted.

Protecting the Auckland Harbour Bridge, New Zealand – developing a 40-year coatings maintenance plan

The Auckland Harbour Bridge (Auckland, New Zealand), built in 1959 and widened in 1969, has approximately 125 000 m2 of external steel surfaces that have previously been maintained using a ‘spot repair and overcoat’ approach. This has been carried out since 1998 under a performance-specified maintenance contract using moisture-cured urethane coatings. In 2017, the Auckland Harbour Bridge Alliance embarked on a study to review the existing coatings maintenance regime and investigate alternative maintenance strategies. This paper summarises the findings of this investigation, from which a 40-year coatings maintenance plan was developed using net present value life-cycle cost analysis of zone painting. The maintenance plan was developed to achieve the lowest whole-of-life cost while meeting environmental protection requirements.

Stochastic maintenance models for ceramic claddings

Maintenance decision-making involves a series of multiple objectives, some of them contradictory. Usually, stakeholders intend to find the optimal maintenance strategy, to minimize the economic burden, while simultaneously maximizing the buildings’ performance. In this study, a condition-based maintenance model, based on Petri nets, is proposed to evaluate the consequences of alternative maintenance strategies to maintain and improve the performance of ceramic claddings. This maintenance model is a full life-cycle model that integrates the stochastic assessment of the degradation condition of the claddings, and also inspections, maintenance and renewal processes. Three maintenance strategies are considered: (i) major intervention only; (ii) combination of minor and major interventions; and (iii) combination of cleaning operations, minor and major interventions. The uncertainties associated with the degradation process, as well as with the definition of the effects of maintenance actions are considered by modelling the transitions times in Petri nets as random variables. Considering the complexity of Petri nets, the statistical descriptors of the performance of the assets (e.g., mean condition, probability of applying maintenance) were computed using Monte Carlo simulation. The impact of the different maintenance strategies in the claddings’ service life is discussed, comparing the different alternatives also from an economic point of view.

Integration of optimization methodology to evaluate pavement maintenance strategies for deteriorated low-volume roads

Low-volume roads (LVRs) are restricted with limited maintenance funding due to the recent national economic downturn. Only few selected LVRs with deteriorated pavements are typically rehabilitated in which poor LVRs are expected to continue deteriorating to extreme levels of distress. Colorado Department of Transportation (CDOT) is evaluating pavement treatments on LVRs to find the most cost-effective maintenance strategies. As part of these efforts, a comprehensive optimization analysis is adopted in this paper to investigate alternative maintenance strategies and define the capital improvement plans for deteriorated LVRs with marginal pavement conditions. A proposed strategy was found to enhance the effectiveness of current policies followed by CDOT. However, the results emphasize the need for additional resources at network level for dealing with deteriorated LVRs. The optimization procedure described in this paper can be followed by other agencies nationwide to identify strategies and establish funding needs that secure higher funding from decision makers.

Selective maintenance of value information helps resolve the exploration/exploitation dilemma

In natural environments with many options of uncertain value, one faces a difficult tradeoff between exploiting familiar, valuable options or searching for better alternatives. Reinforcement learning models of this exploration/exploitation dilemma typically modulate the rate of exploratory choices or preferentially sample uncertain options. The extent to which such models capture human behavior remains unclear, in part because they do not consider the constraints on remembering what is learned.Using reinforcement-based timing as a motivating example, we show that selectively maintaining high-value actions compresses the amount of information to be tracked in learning, as quantified by Shannon's entropy. In turn, the information content of the value representation controls the balance between exploration (high entropy) and exploitation (low entropy). Selectively maintaining preferred action values while allowing others to decay renders the choices increasingly exploitative across learning episodes.To adjudicate among alternative maintenance and sampling strategies, we developed a new reinforcement learning model, StrategiC ExPloration/ExPloitation of Temporal Instrumental Contingencies (SCEPTIC). In computational studies, a resource-rational selective maintenance approach was as successful as more resource-intensive strategies. Furthermore, human behavior was consistent with selective maintenance; information compression was most pronounced in subjects with superior performance and non-verbal intelligence, and in learnable vs. unlearnable contingencies. Cognitively demanding uncertainty-directed exploration recovered a more accurate representation in simulations with no foraging advantage and was strongly unsupported in our human study.

Methotrexate and Thioguanine Rescue Therapy for Conventional Thiopurine Failing Ulcerative Colitis Patients: A Multi-center Database Study on Tolerability and Effectiveness.

Patients with active ulcerative colitis (UC) failing conventional therapies are in need of rescue strategies. Due to the fact that accepted step-up therapy with biologicals is expensive and sometimes unavailable, alternative therapies are warranted. Methotrexate (MTX) and thioguanine (TG) have both been suggested as alternative maintenance strategies in conventional thiopurine failing UC patients. In this multicenter database study, we compared safety and effectiveness (drug-survival) of MTX and TG in UC patients. We collected data from the Parelsnoer database, a prospective Dutch national database consisting of inflammatory bowel disease patients from all university hospitals in The Netherlands. Additional data were collected from detailed chart review. In total, 99 UC patients were included, of which 48 used TG, 43 used MTX, and 8 patients had a history of both TG and MTX use. In 12% of the patients, biological therapy had failed. Roughly 70% of the patients in both groups were able to continue therapy for over 1 year. Adverse events were noted in 33% of all the patients and were mainly elevated liver enzymes or gastrointestinal complaints. Twenty-eight patients (28%) continued therapy (15 TG, 13 MTX) without the need of escalation therapy (eg, corticosteroids, biologicals, or surgery). Drug survival curves of both drugs were comparable, just as the number of patients with sustained clinical benefit of therapy (P > 0.05). Both MTX and TG may be used and maintained as rescue therapy with sustained clinical benefit in one-third of the UC patients failing conventional therapies.

Economic evaluation of maintenance strategies for ground-mounted solar photovoltaic plants

We propose a generic model which allows to evaluate the economic viability of alternative maintenance strategies for differently sized photovoltaic plants with variable components. We thoroughly review the existing literature on reliability, maintenance and maintenance strategies for PV plants. The model is applied to fixed-tilt ground-mounted solar PV plants in Germany of three different sizes: 1, 10, and 100MWp. The PV plants are set up in a central inverter configuration with the following components: AC/DC switch, circuit breaker, and inverter. The analysis compares immediate corrective maintenance with maintenance strategies of different periodicity (weekly, bi-weekly, and monthly). Simulations take the driving time of the service team and the operation of a spare parts inventory into account. We further analyze the impact of hourly spot prices in contrast to constant prices (feed-in tariffs). We find that corrective maintenance is the most cost-efficient strategy. If the service journey takes six hours instead of one hour, corrective maintenance becomes more expensive than weekly periodic maintenance. For a three-hour journey, the size of the PV plant matters. If corrective maintenance is adopted, the establishing of a spare parts inventory should be considered. When volatile hourly spot prices are considered, we find that opportunity costs are lowest (highest) when service teams operate at 8pm (8 am), irrespective of the day of the week, whereas maintenance events scheduled for Wednesdays at 8 am or 2pm are, given current EPEX spot prices, the most cost-efficient in terms of total costs.

A Petri net model for railway bridge maintenance

This article describes the application of the Petri net modelling approach to managing the maintenance process of railway bridges. The Petri net model accounts for the degradation, inspection and repair processes of individual bridge elements in investigating the effectiveness of alternative maintenance strategies. The times governing the degradation and repair processes considered are stochastic and defined by the appropriate Weibull distribution. The model offers a capability for modelling the bridge asset which overcomes the limitations in the currently used modelling techniques reported in the literature. The bridge model also provides a means of predicting the future asset condition as a result of adopting different maintenance strategies. The solution of the Petri net model is performed using a Monte Carlo simulation routine. The application of the model to a typical metal railway bridge is also presented in the article.

Sustainable Pavement Management System in Urban Areas Considering the Vehicle Operating Costs

Urban roads constitute most of the existing roads and they are directly managed by small administrations. Normally, these small administrations do not have sufficient funds or sufficient qualified personnel to carry out this task. This paper deals with an easy-implementation Pavement Management System (PMS) to develop strategies to maintain, preserve and rehabilitate urban roads. The proposed method includes the creation of the road network inventory, the visual surveys of the pavement and the evaluation of its condition by the Pavement Condition Index (PCI). The method intends to give a valid tool to road managers to compare alternative maintenance strategies and perform the priority analysis on the network. With this aim, the procedure assesses the Vehicle Operating Costs (VOC) by a written regression between PCI and International Roughness Index (IRI). The proposed method has several advantages because it can be easily adapted to various situations and it does not require a large amount of time and money for its implementation.