scholarly journals Preventive Maintenance Model for National School Buildings in Indonesia Using a Constraint Programming Approach

2021 ◽  
Vol 13 (4) ◽  
pp. 1874
Author(s):  
Shu-Shun Liu ◽  
Muhammad Faizal Ardhiansyah Arifin
Keyword(s):  
Constraint Programming ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Programming Approach ◽  
School Buildings ◽  
Maintenance Planning ◽  
Building Conditions ◽  
Building Maintenance ◽  
Deterioration Rate ◽  
Maintenance Model

The Indonesian government needs to maintain around 231,000 school buildings in active use. Such a portfolio of buildings given the diversity of locations, limited maintenance budget, and deterioration rates varied by different building conditions presents many challenges to effective maintenance planning. Many of those schools had been reported to be aging and in a degenerated condition. However, contemporary practice for the planning method of Indonesia’s building maintenance program applies reactive maintenance strategies with a single linear deterioration rate. Such methodology cannot properly guarantee the sustainability of those school buildings. Therefore, this study attempts to examine a different approach to Indonesia’s building maintenance planning by adopting a preventive maintenance strategy using the deterioration rate model proved by historical data from a previous study. This study develops an optimization model with varied deterioration rates and considers the budget limitation, by utilizing a Constraint Programming (CP) approach. The proposed model achieves the minimum maintenance cost for a real case of 41 school buildings under different deterioration rates to ensure adequate building conditions and maintain expected levels of service. Finally, research analysis also proves that this new preventive maintenance model has potential to deliver superior capability for assisting building maintenance decisions in Indonesia’s government.

scholarly journals Constraint Programming Approach for Optimizing Business Asset Maintenance Strategy

2019 ◽  
Vol 1 (01) ◽  
Author(s):  
Gilang Ramadhan ◽  
Shu Shun Liu
Keyword(s):  
Decision Making ◽  
Constraint Programming ◽  
Optimization Model ◽  
Maintenance Treatment ◽  
Treatment Options ◽  
Programming Approach ◽  
Building Maintenance ◽  
Maintenance Program ◽  
Building Condition ◽  
Decision Making Tool

There are many buildings with various conditions in Indonesia and some of them are not in finest conditions that need maintenance treatment urgently. The absence of building maintenance decision-making tool and limited budget are among main factors that cause unmanageable maintenance program. Therefore, this study has been conducted to propose an optimization model that is capable to determine the most appropriate building maintenance treatment. This study applied Constraint Programming (CP) approach to select the most economical maintenance treatment for a certain building and to allocate annual maintenance budget. CP-based model in this study subjects to constraint of budget and targeted level of building condition. In this study, maintenance treatment options, budget, time period, building deterioration rates, and the minimum standard of building condition were set. The model was run in IBM ILOG CPLEX Optimization Studio since the software is very efficient and effective in processing the optimization model. Furthermore, a case study was carried out to run the model involving 41 buildings in a 10-year period, and two different scenarios were conducted to examine the optimization model. The results successfully validated that the model can be a decision-making tool in selecting and prioritizing effective maintenance treatment.

An integrated space-based building maintenance management model using multi-objective optimization

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Huthaifa AL-Smadi ◽  
Abobakr Al-Sakkaf ◽  
Tarek Zayed ◽  
Fuzhan Nasiri
Keyword(s):  
Residential Buildings ◽  
Maintenance Cost ◽  
Content Type ◽  
Fund Allocation ◽  
Building Maintenance ◽  
Window System ◽  
Optimal Maintenance ◽  
Building Condition ◽  
Maintenance Model

PurposeThe purpose of this study is to minimize cost and minimize building condition. Weibull distribution approach was employed to generate deterioration curves over time. The third floor of Concordia University’s Engineering And Visual Arts (EV) Complex in Montreal, Canada, served as a case study to test the maintenance model and determine the optimal maintenance activities to be performed.Design/methodology/approachThis research has demonstrated that there is insufficient fund allocation for the maintenance of non-residential buildings. Therefore, this research focused on designing and developing a maintenance optimization model that provides the type of spaces (architectural system) in a building. Sensitivity analysis was used to calculate weights to validate the model. Particle swarm optimization, based explicitly on multiple objectives, was applied for the optimization problem using MATLAB.FindingsFollowing 100 iterations, 13 non-dominant solutions were generated. Not only was the overall maintenance cost minimized, but the condition of the building was also maximized. Moreover, the condition prediction model demonstrated that the window system type has the most rapid deterioration in educational buildings.Originality/valueThe model is flexible and can be modified by facility managers to align with the required codes or standards.

scholarly journals Development of a Preventive Maintenance Strategy for an Automatic Production Line Based on Group Maintenance Method

2018 ◽  
Vol 8 (10) ◽  
pp. 1781 ◽  
Author(s):  
Guofa Li ◽  
Yi Li ◽  
Xinge Zhang ◽  
Chao Hou ◽  
Jialong He ◽  
...  
Keyword(s):  
Preventive Maintenance ◽  
Production Line ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Automatic Production ◽  
Critical Machine ◽  
Automotive Part ◽  
Automatic Production Line ◽  
Critical Machines ◽  
Maintenance Model

The high maintenance costs and low reliability of automatic production line are attributed to the complexity of maintenance management. In the present study, a preventive maintenance strategy for the automatic production line was developed based on the group maintenance method. The criticality of machines in the production line was evaluated, and then the machines were classified into three groups: the most critical machines, the secondary critical machines and the general machines. The general machines were performed on the breakdown maintenance. The preventive maintenance model of the most critical machines was established with the shortest shutdown time as decision objective on basis of the Delay-time theory. The maintenance model of the secondary critical machine was established based on the considering of reliability-maintenance cost. A case study on an automotive part automatic production line was carried out to verify the proposed preventive maintenance strategy based on the production line data, and the maintenance periods of the most and secondary critical machines were gained; meanwhile, the machines all satisfied the reliability requirements during the maintenance periods.

scholarly journals Multiobjective Multistate System Preventive Maintenance Model with Human Reliability

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Chao-Hui Huang ◽  
Chun-Ho Wang ◽  
Guan-Liang Chen
Keyword(s):  
Preventive Maintenance ◽  
Power Transmission ◽  
Pareto Frontier ◽  
Sensitivity Analyses ◽  
Maintenance Cost ◽  
Human Reliability ◽  
Reliability Factor ◽  
Multistate System ◽  
Performance Conditions ◽  
Maintenance Model

Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters.

Optimizing Bi-Objective Imperfect Preventive Maintenance Model for Multi-Component System Using a Proposed Improved PSO Algorithm

2013 ◽  
Vol 284-287 ◽  
pp. 3707-3711
Author(s):  
Chung Ho Wang ◽  
Sheng Wang Tsai
Keyword(s):  
Preventive Maintenance ◽  
Pso Algorithm ◽  
Maintenance Cost ◽  
Adjustment Mechanism ◽  
Decision Variables ◽  
The Mean ◽  
Ipso Algorithm ◽  
Maintenance Model ◽  
Multi Component System ◽  
Search Capability

This study aims to establish a bi-objective imperfect preventive maintenance (BOIPM) model in which the total maintenance cost and the mean system reliability are optimized by determining the maintenance periods and maintenance activities simultaneously. To efficiently solve the established BOIPM model, this study proposes an improved particle swarm optimization (IPSO) algorithm. The IPSO extends the practicability of the conventional PSO originally designed to solve an optimization problem with continuous decision variables. Furthermore, time-varying mechanisms associated with search parameters of the PSO are utilized to enhance the particles search capability. An adjustment mechanism addressing the issue of particles falling into the infeasible area is constructed to enhance the exploring ability of the IPSO. A case verifies the effectiveness of the proposed approach.

scholarly journals Identification of Damage Level and Cost Estimate of Building Maintenance of Elementary School

2020 ◽  
Vol 331 ◽  
pp. 01005
Author(s):  
Fahirah Fahruddin ◽  
Donny M Mangitung ◽  
Andi Rizal
Keyword(s):  
Elementary School ◽  
Preventive Maintenance ◽  
Building Materials ◽  
Secondary Data ◽  
Cost Estimate ◽  
Primary Data ◽  
School Buildings ◽  
Planning Period ◽  
Damage Level ◽  
Building Maintenance

The damage of the buildings is a sure thing to happen, in the planning period, implementation until the time of its used. To maintain the reliability of the building and facilities of infrastructure so that the building is always functional, then the building maintenance is done. Cleaning, weeding, testing, repair and / or replacement of building materials or equipment are included in the scope of building maintenance (preventive maintenance). The purpose of this research is to determine the level of damage and cost estimate of building maintenance of elementary school in North Morowali District. The research method used consisted of several stages, namely primary and secondary data collection. Primary data through direct survey to the location and interview with related parties. There are 5 (five) school buildings in North Morowali District. Data processing is done by calculating the damage quantity, the level of damage in the school buildings and cost estimate maintenance. Data analysis was used Descriptive Statistics. The results of the study identified the level of damage from 5 school buildings with an average of minor damage was 21. 26%. Cost estimate of maintenance needed so that the parties associated with the school building can do preventive maintenance activities and run the maintenance of the building based on school management well was IDR 484. 805. 296.

scholarly journals RAILWAY CONDITION-BASED MAINTENANCE MODEL WITH STOCHASTIC DETERIORATION

2014 ◽  
Vol 20 (5) ◽  
pp. 686-692 ◽  
Author(s):  
Cecília Vale ◽  
Isabel M. Ribeiro
Keyword(s):  
Standard Deviation ◽  
Stochastic Simulation ◽  
Preventive Maintenance ◽  
Real Data ◽  
Condition Based Maintenance ◽  
Nonlinear Program ◽  
Monte Carlo Techniques ◽  
Deterioration Rate ◽  
Maintenance Model ◽  
Over Time

The application of mathematical programming for scheduling preventive maintenance in railways is relatively new. This paper presents a stochastic mathematical model designed to optimize and to predict tamping operations in ballasted tracks as preventive condition-based maintenance. The model is formulated as a mixed 0–1 nonlinear program that considers real technical aspects as constraints: the reduction of the geometrical track quality over time is characterized by the deterioration rate of the standard deviation of the longitudinal level; the track layout; the dependency of the track recovery on its quality at the moment of the maintenance operation; the limits for preventive maintenance that depend on the maximum permissible train speed. In the model application, a railway stretch with 51.2 km of length is analysed for a time period of five years. The deterioration model is stochastic and represents the reduction of the standard deviation of the longitudinal level over time. The deterioration rate of the standard deviation of the longitudinal level is simulated by Monte Carlo techniques, considering the three parameters Dagum probabilistic distribution fitted with real data (Vale, Simões 2012). Two simulations are performed and compared: stochastic simulation in space; stochastic simulation in space and time. The proposed condition-based maintenance model is able to produce optimal schedules within appropriate computational times.

scholarly journals Optimal Preventive Maintenance of Wind Turbine Components with Imperfect Continuous Condition Monitoring

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3801 ◽  
Author(s):  
Ahmed Raza ◽  
Vladimir Ulansky
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Preventive Maintenance ◽  
False Negative ◽  
Maintenance Cost ◽  
Arbitrary Distribution ◽  
Average Lifetime ◽  
True Negative ◽  
Degradation Failure ◽  
Lifetime Maintenance

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.

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