Repair Cost Estimation Research Articles

Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters

Artificial neural network-based repair and maintenance cost estimation model for rice combine harvesters

ANALYSIS OF DAMAGE LEVEL AND COST ESTIMATION OF THE SAMUDRAJAYA 04 BEKASI STATE ELEMENTARY SCHOOL BUILDING

This study aims to determine the level of damage to the school building using a benchmark assessment of the level of damage by DG Pauddikdasmen Kemendikbud in 2021 and investigate the building component repair-cost estimates using Works Unit Price Analysis (AHSP). The research population is a public elementary school in Samudrajaya Village with a sample building SDN Samudrajaya 04 Bekasi as the object of research. The method used in this research is a descriptive research method with a quantitative approach. The data collection technique was carried out through observation, documentation, and unstructured interviews. The results showed that the level of damage to the SDN Samudrajaya 04 Bekasi building in building one was slightly damaged, with the highest component of damage found in the wall component with brick wall sub-components or partition 8.2% glass, doors, and frames were not damaged. While the level of damage to building two was heavily damaged, with the highest component damage found in the wall components of the sub-components of brick or partition walls by 15%, glass 90.3%, doors 88.6%, and frames 96%. The results of the analysis of the estimated repair costs on the components that experienced the most serious damage based on the volume of damage were in building one of Rp. 30,522,168,48 and in building 2 Rp. 204,070,178.35, the total repair cost is Rp. 234,592,346.83 or can be rounded up to Rp. 234,593,000.

A deep learning algorithm-driven approach to predicting repair costs associated with natural disaster indicators: The case of accommodation facilities

It is well known that accurate and reliable maintenance and repair cost estimates are important to maintain a building in its optimal condition, especially during the operation and maintenance phase within the whole life cycle. However, due to emerging trends in buildings that are high-performance, large-scale, complex, and high-rise, it is difficult to achieve those cost estimates. In addition, the impact of climate changes that tend to occur more frequent and severe natural disasters has caused increasing damages to buildings , yet little is still specifically known about predicting the impact of natural disasters on repair costs of accommodation facilities accurately and reliably. This study fills this gap by developing and validating a deep neural network (DNN) model that can generalize repair cost trends associated with natural disaster factors, including peak ground acceleration , precipitation, wind speed, geographic profiles of adjacent water systems, drawing on 1125 insurance claim payout records on accommodation facilities. The robustness of the developed DNN model was scientifically tested and validated using the root mean squared error and the mean absolute error methods. Practical applicability of the proposed modeling framework was then demonstrated by creating predicted repair cost trends. This study contributes to the existing knowledge by proposing a deep learning method that predicts repair costs of accommodation facilities associated with natural disasters, while providing both facility managers and insurance companies with evidence-based reference to develop better-informed cost management strategies against potential natural disasters. • Prediction of repair costs of accommodation facilities against natural hazards. • Development of a deep neural network (DNN)-driven learning model. • Improved predictability of the DNN model compared to the multiple regression model. • Model validation using mean absolute error and root mean squared error methods. • Repair cost trends by weather and seismic conditions and water system profiles.

Loss Estimation for Typical Adobe Façades of Cuenca (Ecuador) Due to Earthquake Scenarios

ABSTRACT A relevant percentage of the world population lives in constructions made of sun-dried earth, which are built according to several techniques such as rammed earth, bahareque or adobe. This work specifically focuses on the adobe buildings located in the Historic Centre of Cuenca (Ecuador), recognized as a World Heritage Site since 1999. Although these buildings are characterized by different geometrical and material configurations, all of them have load-bearing façade walls made of adobe. This paper illustrates an analysis of the seismic vulnerability of these adobe façade walls according to different geometrical configurations and considering an out-of-plane loading. This study is based on original in-situ collected data about 45 one and multi-storey buildings. The seismic behaviour of the case studies is investigated through a demand versus capacity analysis based on 5 different failure mechanisms and considering a variable intensity of the seismic action. This procedure has allowed to classify the case studies according to their seismic vulnerability and to identify the most relevant failure mechanisms in such adobe façades. As a main result, some continued fragility curves have been produced to allow replicating this procedure to buildings with similar features. Finally, a repair cost estimation after seismic scenarios is estimated.

Earthquake Damage Repair Loss Estimation in New Zealand: What Other Variables Are Essential Based on Experts’ Opinions?

Major earthquakes can cause extensive damage to buildings and alter both the natural and built environments. Accurately estimating the financial impact from these events is complex, and the damage is not always visible to the naked eye. PACT, SLAT, and HAZUS are some of the computer-based tools designed to predict probable damage before an earthquake. However, there are no identifiable models built for post-earthquake use. This paper focuses on verifying the significance and usage of variables that specifically need to be considered for the post-earthquake cost estimation of earthquake damage repair work (CEEDRW). The research was conducted using a questionnaire survey involving 92 participants who have experience in cost estimating earthquake damage repair work in New Zealand. The Weighted Average, Relative Importance Index (RII), and Exploratory Factor Analysis were used to analyse the data. The research verified that eleven major variables that are significant to the CEEDRW and should be incorporated to cost estimation models. Verified variables can be used to develop a post-earthquake repair cost estimation tool and can be used to improve the pre-earthquake loss prediction tools.

Repair and Maintenance Cost Estimation for Two Power Sizes of Agricultural Tractors as Affected by Hours of Use and Age in Years: A Case Study, Dongola Area, Sudan

Repair and maintenance cost is considered as one of important items for machinery management and selection especially agricultural tractors. The present study was carried out in Dongola area for tractor repair and maintenance costs estimation. The data was collected from records of Elshimalya Company for Agricultural services. Forty-four tractors representing two powers sizes, 75hp and 150hp used in the area were selected for this study. Based on the data collected, regression correlation analysis was carried out and mathematical models were derived to predict the accumulated repair and maintenance (R and M) costs as percent of purchase price in relation to accumulated hours of use and age (years) for each tractor size, and for the two sizes collectively. Five model forms (linear, logarithmic, polynomial, power and exponential) were derived and the power function was found the best fit to explain the relation. The accumulated Rand M costs as percent of purchase price (Y) was increased as the accumulated hours of use (x) and age (g) of the tractor in years were increased. A high correlation was found between the accumulated R and M cost and both accumulated hours of use and tractor age in years (Average R2 = 0.93).
 It was concluded that the power function was the best fit for repair and maintenance cost estimations and this relation may be used as an average of the two tractor powers, for estimation of the accumulated R and M costs as percent of purchase price (Y) with accumulated hours of use (x) and age (g): Y=0.028x0.662 (mean) Y=12.294g1.276 (mean).

Planning for Maintenance and Repair of Continuous Ship Unloader Using the IRRO Method

The problem faced is damage, especially to the screw conveyor from the Continuous Ship Unloader (CSU) as a dry bulk material transfer equipment (phosphate rock) which is taken from the ship's hold which is flowed by a screw conveyor followed by the belt conveyor to the material warehouse to be processed into a type of fertilizer. The purpose of planning is to obtain a schedule and estimated cost of maintenance and repair of CSU for the period 2022 to 2025, and to obtain the ratio of maintenance-repair costs to the profit of the machine. Planning methods uses the IRRO (Inspection, Replace, Repair, and Overhoul) method include data collection of machine maintenance history and component breakdowns, checking CSU specifications, making a list of component life predictions and component prices, predicting costs and duration of component dissasembly, screw conveyor repair, maintenance and repair scheduling, and maintenance and repair cost estimates. The real results of planning in the form of a maintenance and repair schedule for the period of 2022 to 2025; maintenance and repair costs respectively for the years 2022 to 2025 are IDR 136,873,000; IDR 335,986,000; IDR 160,687,000; and IDR 464,733,000; and the ratio between maintenance costs to profit for the years 2022 to 2025 is 0.51, 1.22, 0.57, and 1.63 which means the machine is still fit for use without the need for refurbishment because it is still prospective.

Road Load Based Model for Vehicle Repair and Maintenance Cost Estimation

A techno-economic model is developed based on road-load simulation results expressed in relation to slip energy (SE) at the tire–pavement interface and the repair and maintenance (R&M) cost obtained from published sources and data from state agencies. Tire SE allows for the consideration of aggressive acceleration and deceleration, high torque conditions (for instance, driving an upslope grade), and roadway curvature. Tire SE data used in this effort were generated using physics-based simulation models of different vehicle types for arrays of road conditions (e.g., grades, curvatures) and driving cycles (i.e., vehicle speed profiles). R&M costs were estimated for various vehicle categories and accumulated vehicle mileage. The approach is based on relating the probability density functions (PDFs) of SE and R&M costs. Asymptotic series expansion for an incomplete gamma function was used to approximate the gamma functions and to determine the gamma ratio function that is used as the coefficient to SE to estimate R&M costs. The average R&M cost per mile results from the model compared with the arithmetic mean R&M cost data from fleet operators and published data. The model can serve as a method for predicting R&M cost as a function of road load to vehicle fleet.

Factors impacting post-earthquake damage repair cost estimations

Purpose Reconstruction processes after an earthquake require estimating repair costs to decide on whether to repair or rebuild. This requires an accurate post-earthquake cost estimation tool. Currently, there are no post-earthquake loss estimation models to estimate repair costs accurately. There are loss assessment tools available, namely, HAZUS, performance assessment calculation tool (PACT), seismic performance and loss assessment tool (SLAT) and seismic performance prediction tool, which have not been specifically used for post-earthquake repair cost estimation. This paper aims to focus on identifying factors that need to be considered when upgrading these tools for post-earthquake repair cost estimation. Design/methodology/approach The research was conducted as an exploratory study using a literature review, document analysis of the PACT, SLAT and HAZUS software and 18 semi-structured interviews. Findings The research identified information sources available for estimation and factors to be considered when developing estimations based on the information sources. Research limitations/implications The data was collected from professionals who were involved mostly in housing repair work in New Zealand. Therefore, impact of these repair work factors might vary in other forms of structures such as civil structures include bridges and the country as a result of varying construction details and standards. Practical implications The identified factors will be used to improve the loss estimation tools are such as PACT and HAZUS, as well as to develop a post-earthquake repair cost estimation tool. Originality/value Currently, the identified factors impacting post-earthquake damage repair cost estimations are not considered in loss estimation tools. Factors identified in this research will help to develop a more accurate cost estimation tool for post-earthquake repair work.

Repair cost estimation techniques for reinforced concrete structures located at the seashore: Considering various probabilistic service life functions and actual mix proportions

RC (reinforced concrete) structures are durable and have a long service life. However, corrosion in embedded steel due to chloride ingress causes durability problems, and this poses a threat to structural performance degradation. The repair cost is very important for the maintenance of RC structures, through which the service life can be extended with reasonable performances. Unlike the conventional deterministic evaluation used to determine repair cost, the probabilistic method can provide a more reasonable result that considers various engineering uncertainties and continuous repair cost. In this paper, the repair cost for an apartment near the seashore was evaluated based on the actual concrete mix proportions and repair unit cost. Two patterns of PSLF (probabilistic service life function) using normal distribution and log distribution were considered for the repair cost evaluation. This was done after the derivation of service life was calculated based on two mix proportions. Within a given service life, various repair costs were evaluated and discussed that considered concrete mix proportions, the pattern of PSLF, and conventional techniques.

Postdisaster image‐based damage detection and repair cost estimation of reinforced concrete buildings using dual convolutional neural networks

AbstractReinforced concrete (RC) buildings are commonly used around the world. With recent earthquakes worldwide, rapid structural damage inspection and repair cost evaluation are crucial for building owners and policy makers to make informed risk management decisions. To improve the efficiency of such inspection, advanced computer vision techniques based on convolutional neural networks have been adopted in recent research to rapidly quantify the damage state (DS) of structures. In this article, an advanced object detection neural network, named YOLOv2, is implemented, which achieves 98.2% and 84.5% average precision in training and testing, respectively. The proposed YOLOv2 is used in combination with the classification neural network, which improves the identification accuracy for critical DS of RC structures by 7.5%. The improved classification procedures allow engineers to rapidly and more accurately quantify the DSs of the structure, and also localize the critical damage features. The identified DS can then be integrated with the state‐of‐the‐art performance evaluation framework to quantify the financial losses of critical RC buildings. The results can be used by the building owners and decision makers to make informed risk management decisions immediately after the strong earthquake shaking. Hence, resources can be allocated rapidly to improve the resiliency of the community.

Evaluation of seismic dynamic behaviour of drywall partitions, façades and ceilings through shake table testing

Significant damage to architectural non-structural components caused by recent seismic events highlighted their importance in the building design and showed that their damage or collapse might have severe consequences. Therefore, the study of the seismic behaviour of non-structural components is very important to minimize the risk. In this context, a specific research project aimed to improve and expand the knowledge of seismic response of architectural non-structural lightweight steel drywall components started at the University of Naples “Federico II”. This paper presents the results of dynamic shake table tests performed on prototypes made of indoor partition walls, outdoor façade walls and suspended continuous ceilings. The influence on seismic response of prototypes from basic and enhanced anti-seismic solutions, corresponding to the use of fixed or sliding connections at the walls and ceilings perimeter, was investigated. The seismic performance in terms of damage occurrence was also evaluated by fragility curves, which showed a better seismic response of enhanced solutions than basic solutions and a seismic “fragility” of indoor partition walls higher than that of outdoor façade walls. Finally, a repair cost estimation was performed by highlighting that the repair cost of partitions is higher than that of façades.

Development of a Maintenance and Repair Cost Estimation Model for Educational Buildings Using Regression Analysis

The aim of this study is to identify key performance indicators as well as the correlations among these indicators to develop a maintenance and repair cost estimation model for educational buildings based on actual payment records. The importance of financial estimation for facility management systems has increased. Especially, the estimation of maintenance and repair costs is essential to facility management for educational buildings considering the long-life cycle of a building. However, data regarding facility management is still limited. This study adopts payment records related to maintenance and repair work from educational institutions to develop a quantitative approach. Statistical analyses and a multiple regression analysis are conducted to examine the record and generate a cost estimation model. The findings and results of this study provide a guide for maintenance and repair cost estimation of integrated facility management and could be used as a guideline for budgeting for school maintenance.

Characterising the in-plane seismic performance of infill masonry

Masonry infills, commonly found in frame buildings throughout Europe and other parts of the world, have performed poorly in past earthquakes, with infill damage endangering lives, causing disruption and significant monetary losses. To characterize the performance of masonry infills, commonly classified as non-structural elements, an extensive set of experimental test data is collected and examined in this work in order to develop fragility functions for the in plane performance of masonry infills. The collected data stems from testing conducted in Europe, the Middle East and the United States and includes solid and hollow clay brick or concrete block infills, constructed to be in contact within either reinforced concrete or steel framing. The results indicate that infill masonry can exhibit first signs of damage at drifts as low as 0.2% but may not suffer complete failure until drifts as high as 2.0%. Furthermore, it is shown that masonry fragility changes significantly according to the type of infill masonry. Subsequently, a short discussion is provided to highlight the potential use of the infill fragility information within non-linear analysis models of masonry infill. Finally, repair cost estimates for infills in Italy are computed using costing-manuals and are compared with cost estimates obtained through consultation with a number of Italian building contractors, with examination of both the median and dispersion in repair costs. It is anticipated that the results of this work will be particularly useful for advanced performance-based earthquake engineering assessments of buildings with masonry infill, providing new information on the in-plane fragility, repair costs and nonlinear modelling of masonry infills.

Bridge management in Turkey: a BMS design with customised functionalities

The overall design and customised functionalities of a bridge management system (BMS), developed in Turkey in 2009–2013 period (the so-called KYS), are presented. The novel design features are explained. Development of the web-based BMS involved the establishment of a bridge inventory database, a detailed multi-layer cost database with an itemised unit cost breakdown capability, inventory management, cost and planning modules, optimal allocation of maintenance-repair–replacement (MR&R) budgets while producing repair cost estimates at damage level, a network-level multi-criteria prioritisation implementation, establishment of a damage-level condition evaluation and rating model, 13 separate customised functionalities, and visual inspections and data entry for a pilot group of 200 bridges. Matrices containing bridge types versus element types and element types versus damage types are constructed. For each element, a dynamic list is developed that can expand or contract depending on an element's damage types. A check mark-based interactive decision-making capability is built, by which the user can overwrite the recommended decisions. BMS is being used by the bridge administration. Out of a total of 7514 bridges in Turkey, in 2014, the damage-level inspection data of over 3000 bridges is entered into the inventory. Entry of bridge and inspection data for the remaining bridge stock will be completed in 2015.

A probabilistic framework for correlated seismic downtime and repair cost estimation of geo‐structures

SUMMARYAn important component of probabilistic risk assessment methods is the development of models to quantify the direct consequences of damage to geo‐structural components for a given intensity of the hazard. This paper presents a general probabilistic framework for correlated repair cost and downtime estimation of geo‐structures exposed to seismic hazards. The framework uses as input the results of nonlinear time‐history analysis of geo‐structures for the set of earthquake records that are representative of the seismic hazard models for the region of interest. The repair cost and downtime are estimated for individual earthquakes probabilistically considering the uncertainties associated with damage states. In addition, the formulation of the repair cost and downtime accounts for the reduction in the repair requirements as the number of damaged components in the given damage state increases. An analytical linear and two bilinear regression models are proposed for conditional correlated seismic repair cost and downtime estimation of geo‐structures given the intensity measure. The proposed framework is demonstrated by developing seismic repair models of a typical pile‐supported wharf structure on the west coast of the United States. The presented framework is general and can be applied to other types of geo‐structures and hazards and can include other decision variables such as loss of life as well. Copyright © 2013 John Wiley & Sons, Ltd.

A Proposal of Repair Cost Estimating Criteria for Persistent Defects in Apartment Houses

It has been often noted as a problem that as there are no objective and clear criteria for the repair cost estimate of persistent defects, when a claim arises in relation to an apartment construction, significantly different amounts of compensation may be given for similar defects based on the experience and tendencies of the construction experts asked to make a judgment. For this reason, this research aims to present defect managers with a more reasonable and objective estimation criteria and a system to determine the repair cost of defects based on an analysis of relevant factors. The research findings show that the historical cost system is applied first, and then a standard of estimation is used to estimate the cost for the items that are not included in the historical cost system. The criteria for the repair cost for each defect is as follows: the repair cost for defects arising from a regulation violation is determined by calculating the reconstruction cost of the parts in question after demolishing them; the repair cost for progressive defects is determined based on a contribution ratio proportional to the age of the building; the repair cost for repetitive defects is calculated by considering an alternative to maximize the intended function of the defective parts; and the repair cost for value depreciation defects is determined based on the ratio of the warranty period to the lapsed years. However, repair cost estimation for dual value depreciation defects should be studied in future research.

Post‐earthquake bridge repair cost and repair time estimation methodology

AbstractWhile structural engineers have traditionally focused on individual components (bridges, for example) of transportation networks for design, retrofit, and analysis, it has become increasingly apparent that the economic costs to society after extreme earthquake events are caused at least as much from indirect costs as direct costs due to individual structures. This paper describes an improved methodology for developing probabilistic estimates of repair costs and repair times that can be used for evaluating the performance of new bridge design options and existing bridges in preparation for the next major earthquake. The proposed approach in this paper is an improvement on previous bridge loss modeling studies—it is based on the local linearization of the dependence between repair quantities and damage states so that the resulting model follows a linear relationship between damage states and repair points. The methodology uses the concept of performance groups (PGs) that account for damage and repair of individual bridge components and subassemblies. The method is validated using two simple examples that compare the proposed method to simulation and previous methods based on loss models using a power–law relationship between repair quantities and damage. In addition, an illustration of the method is provided for a complete study on the performance of a common five‐span overpass bridge structure in California. Intensity‐dependent repair cost ratios (RCRs) and repair times are calculated using the proposed approach, as well as plots that show the disaggregation of repair cost by repair quantity and by PG. This provides the decision maker with a higher fidelity of data when evaluating the contribution of different bridge components to the performance of the bridge system, where performance is evaluated in terms of repair costs and repair times rather than traditional engineering quantities such as displacements and stresses. Copyright © 2009 John Wiley & Sons, Ltd.

Integrated Multiple-Element Bridge Management System

This paper presents the development of a comprehensive bridge management system that optimizes repair decisions considering multiple bridge elements and large networks of bridges. The strength of the system stems from its integration of project-level decisions of the best repair strategies to use on the elements of each bridge, and network-level decisions of the most beneficial repair year for each bridge. These decisions, however, represent complex optimization problems that traditional optimization techniques are often unable to solve. To handle such a large problem, the proposed system uniquely segments the problem into smaller sequential optimizations that are solved using the genetic algorithms technique. The system uses a year-by-year optimization formulation to maximize the benefit/cost ratio of the repairs, and to maximize the overall network condition. The paper provides a description of the multiple-element system, its life-cycle formulation, and its related models for deterioration analysis and repair cost estimation. System implementation and an example application are then presented to demonstrate the practicality of the system and its performance on different sizes of bridge networks.

Essay competition: The variability of building surveyors in house condition surveys: its impact on repair cost estimation

(2000). Essay competition: The variability of building surveyors in house condition surveys: its impact on repair cost estimation. Building Research & Information: Vol. 28, No. 1, pp. 73-75.