scholarly journals Developing An Optimization Model For Pavement Maintenance Planning And Resource Allocation In Hossana Town, Ethiopia

2021 ◽  
Vol 23 (08) ◽  
pp. 824-836
Author(s):  
Tarekegn Shirko Lachore ◽  
◽  
Dagimwork Asele Manuka ◽  
Keyword(s):  
Mathematical Optimization ◽  
Cost Effective ◽  
Optimization Method ◽  
Pavement Management ◽  
Maintenance Strategy ◽  
Pavement Maintenance ◽  
The Road ◽  
Network Maintenance ◽  
Collection Data ◽  
Optimal Maintenance

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.

scholarly journals Analysis of Pavement Condition Survey Data for Effective Implementation of a Network Level Pavement Management Program for Kazakhstan

2019 ◽  
Vol 11 (3) ◽  
pp. 901 ◽  
Author(s):  
Antonio Pantuso ◽  
Giuseppe Loprencipe ◽  
Guido Bonin ◽  
Bagdat Burkhanbaiuly Teltayev
Keyword(s):  
Developing Countries ◽  
Survey Data ◽  
Cost Effective ◽  
Political Stability ◽  
Transportation Systems ◽  
Management Program ◽  
Pavement Management ◽  
Sustainable Growth ◽  
Pavement Maintenance ◽  
Capital Costs

Pavement roads and transportation systems are crucial assets for promoting political stability, as well as economic and sustainable growth in developing countries. However, pavement maintenance backlogs and the high capital costs of road rehabilitation require the use of pavement evaluation tools to assure the best value of the investment. This research presents a methodology for analyzing the collected pavement data for the implementation of a network level pavement management program in Kazakhstan. This methodology, which could also be suitable in other developing countries’ road networks, focuses on the survey data processing to determine cost-effective maintenance treatments for each road section. The proposed methodology aims to support a decision-making process for the application of a strategic level business planning analysis, by extracting information from the survey data.

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.

MAINTENANCE OPTIMIZATION OF EQUIPMENT BY LINEAR PROGRAMMING

2005 ◽  
Vol 20 (1) ◽  
pp. 183-193 ◽  
Author(s):  
Archana Jayakumar ◽  
Sohrab Asgarpoor
Keyword(s):  
Linear Programming ◽  
Preventive Maintenance ◽  
Mathematical Optimization ◽  
Optimal Solution ◽  
Cost Effective ◽  
Maintenance Policy ◽  
Markov Decision ◽  
Random Failure ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Optimal levels of preventive maintenance performed on any system ensures cost-effective and reliable operation of the system. In this paper a component with deterioration and random failure is modeled using Markov processes while incorporating the concept of minor and major preventive maintenance. The optimal mean times to preventive maintenance (both minor and major) of the component is determined by maximizing its availability with respect to mean time to preventive maintenance. Mathematical optimization programs Maple 7 and Lingo 7 are used to find the optimal solution, which is illustrated using a numerical example. Further, an optimal maintenance policy is obtained using Markov Decision Processes (MDPs). Linear Programming (LP) is utilized to implement the MDP problem.

scholarly journals Estimating Pavement Roughness by Fusing Color and Depth Data Obtained from an Inexpensive RGB-D Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1655 ◽  
Author(s):  
Ahmadreza Mahmoudzadeh ◽  
Amir Golroo ◽  
Mohammad Jahanshahi ◽  
Sayna Firoozi Yeganeh
Keyword(s):  
Surface Defects ◽  
Cost Effective ◽  
Pavement Management ◽  
Outdoor Environment ◽  
Primary Data ◽  
International Roughness Index ◽  
The Road ◽  
Pavement Roughness ◽  
Power Spectral ◽  
Road Roughness

Measuring pavement roughness and detecting pavement surface defects are two of the most important tasks in pavement management. While existing pavement roughness measurement approaches are expensive, the primary aim of this paper is to use a cost-effective and sufficiently accurate RGB-D sensor to estimate the pavement roughness in the outdoor environment. An algorithm is proposed to process the RGB-D data and autonomously quantify the road roughness. To this end, the RGB-D sensor is calibrated and primary data for estimating the pavement roughness are collected. The collected depth frames and RGB images are registered to create the 3D road surfaces. We found that there is a significant correlation between the estimated International Roughness Index (IRI) using the RGB-D sensor and the manual measured IRI using rod and level. By considering the Power Spectral Density (PSD) analysis and the repeatability of measurement, the results show that the proposed solution can accurately estimate the different pavement roughness.

scholarly journals An overview of the airport pavement management systems (APMS)

2020 ◽  
Vol 13 (6) ◽  
pp. 581-590
Author(s):  
Md. Tofail Miah ◽  
Erwin Oh ◽  
Gary Chai ◽  
Phil Bell
Keyword(s):  
Implementation Process ◽  
Cost Effective ◽  
Pavement Management ◽  
Management Systems ◽  
Extensive Literature ◽  
Pavement Maintenance ◽  
Study Approach ◽  
Airport Pavement ◽  
Pavement Management Systems ◽  
Optimum Cost

AbstractAirport Pavement Management System (APMS) is a useful tool, including a set of procedures for collecting, analyzing, maintaining, and reporting pavement data, thus assisting airports in finding optimum cost-effective treatments to preserve their pavement assets. The paper provides an in-depth overview of the APMS from an extensive literature review with the aim to identify numerous issues within APMS, such as the components, Pavement Condition Indices, software utilization, and the comprehensive implementation process. The methodology adopted for this research is a descriptive-based study approach on the various airport pavement manuals, guidelines and advisory circulars, journal articles, and book publications for the APMS applications. The airport pavement management systems and the case studies in various airports internationally will be included in the review. The study includes various subjects such as major components, benefit and cost approach, management in different levels, software utilization, maintenance, and rehabilitation (M&R) policies in the implementation of the APMS. Additionally, the research examines the pavement performance indicators that are the key elements for evaluating pavement conditions. Besides, the APMS software programs can store historical information, analyze data, develop models, and generate reports for M&R in association with the budget, including estimating future pavement life. The study summarizes the condition data required for the implementation and operation of an APMS, as well as the information generated by the APMS. The review highlights the benefits of an APMS in providing the airport operators and engineers far more informed position for decision-making to forecast future pavement maintenance requirements for an adequate and timely M&R.

CALIBRATION OF RUTTING AND ROUGHNESS DISTRESS MODELS OF HDM-4 FOR DEVELOPING PAVEMENT MAINTENANCE MANAGEMENT

2018 ◽  
Vol 5 (2) ◽  
Author(s):  
Aditya Singh ◽  
Tanuj Chopra
Keyword(s):  
Road Network ◽  
Local Conditions ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
The Road ◽  
The World Bank ◽  
Pavement Deterioration ◽  
Network Maintenance ◽  
Investment Programme ◽  
Development And Management

The Highway Development and Management model (HDM-4) is a tool developed by the World Bank to aid highway administrators and engineers in the process of decision making for preparing of road investment programme and determining the road network maintenance strategies. HDM-4 essentially models the interaction between the traffic volume, environment and pavement composition to predict the different kinds of distress that develop in pavements over time. Since distress is caused due to different conditions and progresses at different rates, therefore it is necessary to calibrate the HDM-4 model as per the local conditions. The aim of the study is to calibrate the HDM-4 pavement deterioration model in terms of rutting and roughness for the urban road network of Patiala (Punjab, India). In our study, we select 15 road sections and group them based on varying traffic and pavement age. The pavement condition data, which was measured starting from 2012 to the end of 2014, is fed as the input to the HDM-4 distress models. The calibration process is performed using statistical analysis between the observed and predicted value of the distress by keeping minimum Root Mean Square Error (RMSE) and maximum R-square (R2). The determined calibration factors are validated and further used for developing pavement deterioration models which prove to be helpful in building a Pavement Maintenance and Management system for Patiala.

scholarly journals Analysis Of Quality Control Plans For Bridge Over The River Maza Jugla Accoring To COST TU 1406 Methodology

2021 ◽  
Vol 1202 (1) ◽  
pp. 012028
Author(s):  
Roberts Auzins ◽  
Ainars Paeglitis
Keyword(s):  
Quality Control ◽  
Road Network ◽  
Cost Effective ◽  
Management Process ◽  
Bridge Management ◽  
European Level ◽  
The Road ◽  
European Cooperation ◽  
Collection Data ◽  
Quality Specifications

Abstract Bridges are one of the most expensive elements of the road network, and therefore in the bridge management process, it is very important to make the most technically efficient and cost-effective decisions about planned actions such as maintenance, rehabilitation and reconstruction works. Decisions have to be based both on the current situation and possible future options and alternatives. The European Cooperation in Science and Technology (COST) during the action TU 1406 “Quality specifications for roadway bridges, standardization at a European level (BridgeSpecs)” in the period from 2014 to 2019 has developed the framework for the development of bridge Quality Control Plans (QCP) including the system of data collection, data processing and outcomes. This article analyses and compares different Quality Control Plans developed according to COST TU 1406 methodology for the existing bridge over the river Maza Jugla, located on regional road P10 at km 34.80 in Latvia.

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

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.

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