Maintenance Planning
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2021 ◽  
Vol 13 (18) ◽  
pp. 3687
Author(s):  
Ye Xia ◽  
Xiaoming Lei ◽  
Peng Wang ◽  
Limin Sun

The functional and structural characteristics of civil engineering works, in particular bridges, influence the performance of transport infrastructure. Remote sensing technology and other advanced technologies could help bridge managers review structural conditions and deteriorations through bridge inspection. This paper proposes an artificial intelligence-based methodology to solve the condition assessment of regional bridges and optimize their maintenance schemes. It includes data integration, condition assessment, and maintenance optimization. Data from bridge inspection reports is the main source of this data-driven approach, which could provide a substantial amount og condition-related information to reveal the time-variant bridge condition deterioration and effect of maintenance behaviors. The regional bridge condition deterioration model is established by neural networks, and the impact of the maintenance scheme on the future condition of bridges is quantified. Given the need to manage limited resources and ensure safety and functionality, adequate maintenance schemes for regional bridges are optimized with genetic algorithms. The proposed data-driven methodology is applied to real regional highway bridges. The regional inspection information is obtained with the help of emerging technologies. The established structural deterioration models achieve up to 85% prediction accuracy. The obtained optimal maintenance schemes could be chosen according to actual structural conditions, maintenance requirements, and total budget. Data-driven decision support can substantially aid in smart and efficient maintenance planning of road bridges.


Author(s):  
Lean Heong Foo

AbstractGuided tissue regeneration (GTR) has been proven to promote attachment and regeneration of periodontal tissue. However, there is a 20 to 40% incidence of attachment loss on regenerated attachments reported in the literature. To my knowledge, this is the first case report on a second attempt in GTR on a previous successful grafted site with clinical attachment loss. A healthy 17-year-old Chinese male patient had GTR performed with xenograft particles and bovine resorbable membrane on his root-canal treated, fused upper right lateral incisor and upper right canine (#12-#13) in 2007. Probing depth on the mid-palatal region of #12-#13 was reduced to 4 mm and maintained for the next 4 years. But in the fifth year, probing depth increased to 11 mm with no endodontic symptoms, and a second attempt of GTR using the same materials was carried out. The probing depth at the surgical site was reduced to 4 mm and successfully maintained for another 5 years. Irregular maintenance and the presence of plaque retentive factor could have caused the clinical attachment loss on #12-#13. This case shows it is possible to attempt GTR on a previous successfully grafted site. GTR did not increase tissue resistance against periodontal breakdown. Hence, proper maintenance planning for GTR sites is important to prevent periodontal breakdown.


2021 ◽  
Vol 238 ◽  
pp. 109695
Author(s):  
Joseph Davies ◽  
Huy Truong-Ba ◽  
Michael E. Cholette ◽  
Geoffrey Will

Author(s):  
Pavel Yu. Gubin ◽  
Vladislav P. Oboskalov

Currently, heuristic methods based on iterative changing of feasible solutions set provide a perspective tool for generation equipment maintenance scheduling in power systems. Wherein effectiveness of a heuristic method depends significantly on the initial set of possible schedules or in other words quality of the method initialization. In this case, a widely used methodology of building the initial array of solutions on the basis of pseudorandom uniform generation of control variables seems to be only palliative way to access the problem. This paper proposes alternative initialization procedure drawing on the example of generating units maintenance planning with heuristic differential evolution method. The principle of this method is to get initial set of solutions utilizing normal probability distribution to generate pseudorandom deviations from the suboptimal maintenance schedule which is to be preliminarily formed using directed search method. Following this approach allows to improve probabilistic characteristics of resultant maintenance schedule in particular to decrease median value of an objective function and its coefficient of variation, and to maximize probability to get the combination of units outage moments completely suiting operational constraints.


2021 ◽  
Vol 23 (08) ◽  
pp. 824-836
Author(s):  
Tarekegn Shirko Lachore ◽  
◽  
Dagimwork Asele Manuka ◽  

Pavement Management System is designed to provide objective information and useful data for analysis so that road managers can make more consistent, cost-effective, and defensible decisions related to the preservation of a pavement network. During the process of road network maintenance and rehabilitation, road authorities strive to select an optimum maintenance strategy from a number of alternatives. Mathematical optimization models, supported by suitable data, can assist decision making about allocating funds between alternative maintenance tasks and about the size of the maintenance budget. It can be done through the analysis of costs and benefits by comparing the various maintenance alternatives with the help of an optimization method known as solver. The road segment mainly included in study was road from Hosanna Menhariya to Wachemo University and other important access roads. These roads are divided into different sections in not more than 100m length. The Study involves data collection, data analysis and the selection of optimal maintenance strategy by using a method known as Solver (Add-ins in Microsoft excel). In this study, patching was selected as possible maintenance among the other alternatives. The result of solver analysis for patching indicates that as 74,574 birr allocated for the maintenance of pavement per kilometer in different three segments under the municipality having the constraint budget of 152,018.45 birr/km. The optimized solution shows that about 20962.5 birr would be saved in one year per km with in municipality.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Samane Babaeimorad ◽  
Parviz Fattahi ◽  
Hamed Fazlollahtabar

PurposeThe purpose of this paper is to present an integrated strategy for inventory control and preventive maintenance planning for a single-machine production system with increasing failure rates.Design/methodology/approachThere are three scenarios for solving presented model. The strategy is such that the production component is placed under maintenance as soon as it reaches the m level or in the event of a malfunction earlier than m. Maintenance completion time is not predictable. As a result of periodic maintenance, a buffer stock h is held and the production component starts to produce from period A with the maximum throughput to satisfy demand and handle the shortage. A numerical algorithm to find the optimal policy is developed. The algorithm is implemented using MATLAB software.FindingsThe authors discovered that joint optimization mainly reduces production system costs. Cs is holding cost of a product unit during a unit of time. The authors consider two values for Cs, consist of, Cs = 1 and Cs = 2. By comparing the two cases, it is concluded that by reducing the cost from Cs = 2 to Cs = 1, the optimal scenario does not differ. The amount of decision variables decreases.Originality/valueThis paper is the provision of a model in which the shortage of back order type is considered, which greatly increases the complexity of the problem compared to similar issues. The methods for solving such problems are provided by the numerical algorithm, and the use of buffers as a way to compensate for the shortage in the event of a complete shutdown of the production line which is a very effective and efficient way to deal with customer loss.


Author(s):  
Simon Zhai ◽  
Meltem Göksu Kandemir ◽  
Gunther Reinhart

AbstractTo harness the full potential of predictive maintenance (PdM), PdM information has to be used to optimally plan production and maintenance actions. Hence, operation-specific modelling of degradation, i.e. predictions of the health condition under time-varying operational conditions, has to be realized. By utilizing operation-specific degradation information, maintenance and production can be planned with regard to each other and thus, predictive maintenance integrated production scheduling (PdM-IPS) is enabled. This publication proposes a novel PdM-IPS approach consisting of two interacting modules: an operation-specific Prognostics and Health Management (PHM) module and an integrated production scheduling and maintenance planning (IPSMP) module. Specifically, the mathematical problem of the IPSMP module based on an extended version of the maintenance integrated flexible job shop problem is formulated. A two-stage genetic algorithm to efficiently solve this problem is designed and subsequently applied to simulated condition monitoring, as well as real industrial data. Results indicate that the approach is able to find feasible high quality PdM integrated production schedules.


2021 ◽  
Vol 13 (15) ◽  
pp. 8208
Author(s):  
Waraporn Luejai ◽  
Thanapong Suwanasri ◽  
Cattareeya Suwanasri

In this paper, a D-distance risk factor was proposed to prioritize high-voltage transmission lines from high to low risk in transmission line maintenance and renovation management. Various conditions and importance assessment criteria together with the weighting and scoring method were proposed to calculate both the renovation and importance indices of transmission lines. The scores of different test methods and visual inspection were differentiated from zero to five as end-of-life to very good condition to evaluate the condition of the line and its components. Additionally, the scores of different importance criteria were modified to assess the line importance from low to high importance. Moreover, the analytic hierarchy process was applied to determine the important weight of all test methods and importance criteria, which were evaluated by utility experts. The renovation and importance indices were combined in a risk matrix to finally determine the risk of the line by using the D-distance technique. Later, the risk of every transmission line was plotted in a risk matrix to prioritize and manage maintenance tasks. Finally, a maintenance cost was analyzed by applying the D-distance risk factor and compared with the replacement cost of a new transmission line for maintenance planning and cost minimization. Twenty out of 115, 230 and 500 kV transmission lines fleet in Thailand were practically analyzed with actual data. The results were realistic to feasibly implement in a transmission system for sustainable management.


2021 ◽  
pp. 147592172110306
Author(s):  
Jannie S Nielsen

A Bayesian approach is often applied when updating a deterioration model using observations from inspections, structural health monitoring, or condition monitoring. The observations are stochastic variables with probability distributions that depend on the damage size. Consecutive observations are usually assumed to be independent of each other, but this assumption does not always hold, especially when using online monitoring systems. Frequent updating using dependent measurements can lead to an over-optimistic assessment of the value of information when the measurements are incorrectly modeled as being independent. This article presents a Bayesian network modeling approach for the inclusion of temporal dependency between measurements through a dependency parameter and presents a generic monitoring model based on the exceedance of thresholds for a damage index. Additionally, the model is implemented in a computational framework for risk-based maintenance planning, developed for maintenance planning for wind turbines. The framework is applied for a numerical experiment, where the expected lifetime costs are found for strategies with monitoring with and without dependency between observations, and also for the case where dependency is present but is neglected when making decisions. The numerical experiment and associated parameter study show that neglecting dependency in the decision model when the observations are in fact dependent can lead to much higher costs than expected and to the selection of non-optimal strategies. Much lower costs (down to one quarter) can be obtained when the dependency is properly modeled. In the case of temporally dependent observations, an advanced decision model using a Bayesian network as a simple digital twin is needed to make monitoring feasible compared to only using inspections.


2021 ◽  
Vol 6 (7) ◽  

Bone metabolism is gaining more prominence due to osseointegrated implants. Even after a minimally traumatic tooth extraction, there are natural reductions and losses in the proportions of the alveolar bone and other periodontal tissues. Maintaining these dimensions has become a challenge for researchers. Immediate implants are set in the same surgical act as tooth extraction. Implants are recommended aiming at reducing the waiting time for bone repair and thus offering the necessary stimuli to the bone for its dimensional, functional, and esthetic maintenance. Planning prior to immediate setting should take into account anatomical variations and even anomalies mainly related to the dimensions and number of tooth roots. Among the general factors of anatomical variation, those related to Gender, Age, Biotype, and Ethnicity stand out. These data were provided in studies carried out by several authors in several countries, correlating them with the dimensions and number of tooth roots. A selection of works using measurement methods as Cone Beam Computed Tomography or direct measurements in extracted teeth was carried out. Studies confirm that Panoramic Radiography presents greater distortions and does not provide sharpness for dimensional boundary markings. Significant data were obtained and confirm the correlation of these general factors of anatomical variation with the length and number of tooth roots. Further studies need to be carried out, in order to provide clinicians with details of these variants, important in the planning and prior choice of the best shape and size of the dental implant to be installed.


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