scholarly journals Determination of Optimal MR&R Strategy and Inspection Intervals to Support Infrastructure Maintenance Decision Making

2021 ◽  
Vol 13 (5) ◽  
pp. 2664
Author(s):  
Yingnan Yang ◽  
Hongming Xie
Keyword(s):  
Decision Making ◽  
Transition Probabilities ◽  
Model Development ◽  
Cost Savings ◽  
Time Period ◽  
Predetermined Level ◽  
Optimal Maintenance ◽  
Maintenance Decisions ◽  
Infrastructure Maintenance

In the commonly used approach to maintenance scheduling for infrastructure facilities, maintenance decisions are made under the assumptions that inspection frequency is periodical and fixed, and that the true state of a facility is revealed through inspections. This research addresses these limitations by proposing a decision-making approach for determining optimal maintenance, repair, and rehabilitation (MR&R) strategy and inspection intervals for infrastructure facilities that can explicitly take into account non-periodical inspections as well as previously considered periodical inspections. Four transition probabilities are proposed to represent four different MR&R strategies. Then, an optimization program is suggested to minimize MR&R and inspection costs of a bridge element network over a given time period, while keeping the condition states of the element network above a predetermined level. A case study was applied to illustrate the proposed approach. The results show that the proposal approach can support decision making in situations where non-periodical inspections and MR&R actions are incorporated into the model development. If employed properly, this may allow agencies to maintain their infrastructure more effectively, resulting in cost savings and reducing unnecessary waste of resources.

Survival analysis at multiple scales for the modeling of track geometry deterioration

2017 ◽  
Vol 232 (3) ◽  
pp. 842-850 ◽  
Author(s):  
Negin Alemazkoor ◽  
Conrad J Ruppert ◽  
Hadi Meidani
Keyword(s):  
Survival Analysis ◽  
Multiple Scales ◽  
Fine Scale ◽  
Coarse Scale ◽  
Track Geometry ◽  
Time Period ◽  
Scale Models ◽  
Optimal Maintenance ◽  
Maintenance Decisions

Defects in track geometry have a notable impact on the safety of rail transportation. In order to make the optimal maintenance decisions to ensure the safety and efficiency of railroads, it is necessary to analyze the track geometry defects and develop reliable defect deterioration models. In general, standard deterioration models are typically developed for a segment of track. As a result, these coarse-scale deterioration models may fail to predict whether the isolated defects in a segment will exceed the safety limits after a given time period or not. In this paper, survival analysis is used to model the probability of exceeding the safety limits of the isolated defects. These fine-scale models are then used to calculate the probability of whether each segment of the track will require maintenance after a given time period. The model validation results show that the prediction quality of the coarse-scale segment-based models can be improved by exploiting information from the fine-scale defect-based deterioration models.

scholarly journals Development of Fuzzy Multi Criteria Decision Making Method for Selection of Optimum Maintenance Alternative

2012 ◽  
pp. 206-211
Author(s):  
Arun Nagar
Keyword(s):  
Decision Making ◽  
Manufacturing Industry ◽  
Model Development ◽  
Cost Effective ◽  
Multi Criteria Decision Making ◽  
Maintenance Strategy ◽  
Fuzzy Decision ◽  
Optimal Maintenance ◽  
Frame Work ◽  
Selection Of

An optimal maintenance strategy is a key support to production in the manufacturing industry. This paper present a fuzzy approach based on Multi-Criteria Decision-Making (MCDM) methodology for selecting the optimal maintenance alternative. In the present work the criticality of each equipment is achieved by ranking (based on production loss).It is very difficult to quantify the qualitative factors in exact numerical value. These factors can be expressed in the linguistics terms which can be translated into mathematical measures by using fuzzy sets & system theory. The study problem to develop a fuzzy decision approach to rank the suitable maintenance alternative. The objective of this paper is to propose fuzzy frame work based on fuzzy number theory to solve optimal maintenance alternative which includes decision criteria analysis, weight assessment & decision model development. The approach can aid formulating a cost-effective maintenance strategy for a manufacturing plant.

IMPLEMENTASI MANAJEMEN PEMBELAJARAN TAHFIDZUL QUR’AN DI MI ISTIQOMAH SAMBAS PURBALINGGA

2018 ◽  
Vol 19 (2) ◽  
pp. 104-120
Author(s):  
Maulana Khusen
Keyword(s):  
Decision Making ◽  
Teacher Performance ◽  
Learning Program ◽  
Target Class ◽  
Class 1 ◽  
Second Year ◽  
Learning Management ◽  
Coordination Meeting

Abstract: The results of the study show that: (1) Tahfidzul Qur'an learning planning is done through the preparation of memorization targets and the determination of effective weeks and days in each semester; (2) Organizing is carried out through the division of tasks and responsibilities as well as the construction of the structure of the tutoring teacher; (3) The mobilization is carried out through the coordination meeting of the Tahfidz coordinator as a shering forum for decision making and direction of the Tahfidzul Qur'an learning program and the implementation of learning is carried out every Monday-Friday; and (4) Supervision is carried out through assessing teacher performance at the end of December and June. The highest achievement target for the second year of the implementation of the Tahfidzul Qur'an's 2017/2018 year program is juz 29 and 30, the lowest target for class 1 is juz 30 to Surat al Ghosyiyyah. For class 1, 85% of the target is achieved and 11% of students exceed the target. Class 2 targets reached 19%. Class 3, 10.86% reached the target and 0.35% of students exceeded the target. Class 4 tarjet reached 12.44%. Class 5 targets reached 4.24%, and the last grade 6 target reached 13.79% and 1.5% of students exceeded the target. Keywords: Learning Management, Tahfidzul Qur'an.

Treatment of venous leg ulcers using bilayered living cellular construct

2020 ◽  
Vol 9 (13) ◽  
pp. 907-918
Author(s):  
Aseel Bin Sawad ◽  
Fatema Turkistani
Keyword(s):  
Healthcare System ◽  
Cost Savings ◽  
Standard Of Care ◽  
Healthcare Resource Utilization ◽  
Psychological Status ◽  
Leg Ulcers ◽  
Venous Leg Ulcers ◽  
Time Period ◽  
The Us ◽  
Economic Analyses

Background: Venous leg ulcers (VLUs) present a significant economic burden on the US healthcare system and payers (US$14.9 billion). Aim: To evaluate the quality of life (QoL) of patients with VLUs; to analyze the limitations of standard of care (SOC) for VLUs; and to explain how using bilayered living cellular construct (BLCC) with SOC for treatment of VLUs can help heal more VLUs faster (than using SOC alone) as well as help improve QoL and help reduce the burden on the US healthcare system and payers. Materials & methods: This is a review study. The search was conducted in February 2020 by way of electronic databases to find relevant articles that provided information related to QoL of patients with VLUs, limitations of SOC for VLUs and economic analyses of using BLCC for treatment of VLUs. Results: VLUs impact patients’ physical, functional and psychological status and reduce QoL. A total 75% of VLU patients who used SOC alone failed to achieve healing in a timely fashion, which led to increased healthcare costs and healthcare resource utilization. Although the upfront cost is high, the greater effectiveness of BLCC offsets the added cost of the product during the time period of the studies. Therefore, BLCC helps to improve the QoL of VLU patients. As an example, for every 100 VLU patients in a healthcare plan, the use of BLCC can create cost savings of US$1,349,829.51. Conclusion: Payers’ coverage of BLCC results in reduction of the overall medical cost for treating VLU patients.

scholarly journals Bayesian maintenance decision optimisation based on computing the information value from condition inspections

2021 ◽  
pp. 1748006X2097812
Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González
Keyword(s):  
Decision Making ◽  
Structural Integrity ◽  
Fatigue Cracking ◽  
Cost Effective ◽  
Offshore Structures ◽  
Information Value ◽  
Bayesian Decision ◽  
Maintenance Strategies ◽  
Optimal Maintenance ◽  
Maintenance Decision

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.

scholarly journals A New Grey Approach for Using SWARA and PIPRECIA Methods in a Group Decision-Making Environment

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1554
Author(s):  
Dragiša Stanujkić ◽  
Darjan Karabašević ◽  
Gabrijela Popović ◽  
Predrag S. Stanimirović ◽  
Muzafer Saračević ◽  
...  
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Multiple Criteria Decision Making ◽  
Grey System Theory ◽  
Multiple Criteria ◽  
Decision Making Process ◽  
Grey System ◽  
Criteria Weights

The environment in which the decision-making process takes place is often characterized by uncertainty and vagueness and, because of that, sometimes it is very hard to express the criteria weights with crisp numbers. Therefore, the application of the Grey System Theory, i.e., grey numbers, in this case, is very convenient when it comes to determination of the criteria weights with partially known information. Besides, the criteria weights have a significant role in the multiple criteria decision-making process. Many ordinary multiple criteria decision-making methods are adapted for using grey numbers, and this is the case in this article as well. A new grey extension of the certain multiple criteria decision-making methods for the determination of the criteria weights is proposed. Therefore, the article aims to propose a new extension of the Step-wise Weight Assessment Ratio Analysis (SWARA) and PIvot Pairwise Relative Criteria Importance Assessment (PIPRECIA) methods adapted for group decision-making. In the proposed approach, attitudes of decision-makers are transformed into grey group attitudes, which allows taking advantage of the benefit that grey numbers provide over crisp numbers. The main advantage of the proposed approach in relation to the use of crisp numbers is the ability to conduct different analyses, i.e., considering different scenarios, such as pessimistic, optimistic, and so on. By varying the value of the whitening coefficient, different weights of the criteria can be obtained, and it should be emphasized that this approach gives the same weights as in the case of crisp numbers when the whitening coefficient has a value of 0.5. In addition, in this approach, the grey number was formed based on the median value of collected responses because it better maintains the deviation from the normal distribution of the collected responses. The application of the proposed approach was considered through two numerical illustrations, based on which appropriate conclusions were drawn.

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

Information technology support for integrated supply chain modeling

2008 ◽  
Vol 27 (1) ◽  
pp. 3-13
Author(s):  
Charu Chandra ◽  
Jānis Grabis
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Supply Chain ◽  
Process Modeling ◽  
Service Oriented Architecture ◽  
Model Development ◽  
Integrated Models ◽  
Supply Chain Modeling ◽  
Decision Making Models ◽  
Integrated Supply Chain

Multiple interrelated decision-making models are frequently used in supply chain modeling. Model integration is a precondition for efficient development and utilization of these models. This paper discusses use of modern information technology (IT) techniques and methods for integration of supply chain decision-making models. The overall approach to using IT at various stages of model development is presented. Data and process modeling techniques are used to developed semi-formalized representation of integrated models. These models support integration of decision-making components with other parts of supply chain information system. Process modeling is also used to describe interrelationships among multiple decision-making models. This representation is used as the basis for implementation of integrated models. The service-oriented architecture is proposed as an implementation platform. The presented discussion serves as the basis for further developments in developing integrated supply chain decision-making models.

scholarly journals Automated Residential Energy Audits Using a Smart WiFi Thermostat-Enabled Data Mining Approach

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2500
Author(s):  
Abdulrahman Alanezi ◽  
Kevin P. Hallinan ◽  
Kefan Huang
Keyword(s):  
Low Cost ◽  
Model Development ◽  
Cost Savings ◽  
Measured Temperature ◽  
Single Family ◽  
Furnace Efficiency ◽  
Heating And Cooling ◽  
Data Mining Approach ◽  
Energy Auditing ◽  
Energy Audits

Smart WiFi thermostats, when they first reached the market, were touted as a means for achieving substantial heating and cooling energy cost savings. These savings did not materialize until additional features, such as geofencing, were added. Today, average savings from these thermostats of 10–12% in heating and 15% in cooling for a single-family residence have been reported. This research aims to demonstrate additional potential benefit of these thermostats, namely as a potential instrument for conducting virtual energy audits on residences. In this study, archived smart WiFi thermostat measured temperature data in the form of a power spectrum, corresponding historical weather and energy consumption data, building geometry characteristics, and occupancy data were integrated in order to train a machine learning model to predict attic and wall R-Values, furnace efficiency, and air conditioning seasonal energy efficiency ratio (SEER), all of which were known for all residences in this study. The developed model was validated on residences not used for model development. Validation R-squared values of 0.9408, 0.9421, 0.9536, and 0.9053 for predicting attic and wall R-values, furnace efficiency, and AC SEER, respectively, were realized. This research demonstrates promise for low-cost data-based energy auditing of residences reliant upon smart WiFi thermostats.

Sign in / Sign up

Export Citation Format

Share Document