scholarly journals The Analysis of Cost Estimation using Cost Significant Model on Bridge Construction in South Sulawesi

2021 ◽  
Vol 921 (1) ◽  
pp. 012073
Author(s):  
E Aprianti ◽  
S Hamzah ◽  
M A Abdurrahman
Keyword(s):  
Regression Analysis ◽  
Cost Estimation ◽  
Construction Projects ◽  
Steel Frame ◽  
Bridge Construction ◽  
South Sulawesi ◽  
The Cost ◽  
Total Project Cost ◽  
Total Project ◽  
Significant Model

Abstract One of the fundamental problems faced by the province of South Sulawesi is the factor of accessibility, so the role of bridges is quite important. For this reason, the budget planning for standard bridge construction projects also needs to be efficient in terms of preparation and accurate in terms of budget. The Cost Significant Model is one of the total construction cost estimation models that relies more on the prices that have the most influence on the total project cost as the basis for estimation. In general, this study uses data from steel frame bridge construction projects in South Sulawesi Province to formulate a mathematical model with linear regression analysis so that it can be used in the process of estimating similar projects going forward. The Estimation Model which is formed from the regression analysis and the Cost Significant Model in this study, namely; Y = 3.884 (X7) + 0.989 (X8) - 65515.372. With; Y = Estimated Total Cost (Rp/m); X7 = Reinforcement Work Cost (Rp/m); X8 = Steel Frame Structure Work Cost (Rp/m). Where this model can explain 99.7% of the total project cost with a cost model factor of 1.038. The level of accuracy (percentage error estimate) of the estimation results of the Cost Significant Model in this study ranges from - 1.46% to +2.45%.

scholarly journals Analysis of modern construction projects using montecarlo simulation technique

2018 ◽  
Vol 7 (2.19) ◽  
pp. 41
Author(s):  
A. M. Arunmohan ◽  
M. Lakshmi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Quantitative Analysis ◽  
Construction Projects ◽  
Project Success ◽  
Risk Identification ◽  
Project Schedule ◽  
Montecarlo Simulation ◽  
Total Project Cost ◽  
Total Project

Today, Construction based Industry is the prospering industry which has a high economical influence on any nation. Delay in the huge construction project increases the total project cost. Henceforth, uncertainties as well as risks must be significantly regarded during the project. For organizing and completing the projects in a financially, timely and qualitatively accountable manner, careful scheduling of projects is compulsory. Effectual scheduling of project assures project success. This study concentrates on qualitative analysis, risk identification, together with quantitative analysis. The targets are i) to ascertain the key risk aspects that disturb the project schedule, and ii) to find the probability of finishing the project within specified time. Questionnaires are distributed amongst 20 industry practitioners with disparate experience from [1] to [25] years.  Quantitative analysis is made by the methods like Monte Carlo simulation (MCS) and PERT. @RISK by Palisade corp. is utilized for MCS.

scholarly journals Cost prediction model based on system dynamics in water resource project

2019 ◽  
Vol 258 ◽  
pp. 02027
Author(s):  
Hirijanto ◽  
I Wayan Mundra ◽  
Addy Utomo
Keyword(s):  
Prediction Model ◽  
Cost Estimation ◽  
Construction Projects ◽  
Model Simulation ◽  
Secondary Data ◽  
System Dynamic ◽  
Cost Prediction ◽  
Cost Component ◽  
The Government ◽  
The Cost

Project’s cost is one of important components in project achievement. Because of the uniqueness of construction projects, cost estimation always differs from project to project. The rate of cost components always change over time make difficult to forecast the cost for the upcoming project. The cost component consists of many influencing variables where there is interrelationship each other affecting to the total project cost. This paper objective is to develop a cost prediction model to assist the project planners in cost estimation for future projects. System dynamic is one of the appropriate methods to analyse system behaviour with interrelationship referring to the historic data, so it is able to predict the future project. Developing the model, primary and secondary data are collected from previous studies, interview with the government planner and survey in Malang Regency. The model simulation is Brick work unit with its components. Data from last thirteen years are used to verify and validate the developed model by causal loop diagram as a basic method in system dynamic. The finding showed that the model is closed to real condition through the validation mechanism. The developed system is useful in decision making of budget planning based on work quantity.

scholarly journals Cost Optimal Project Scheduling

Organizacija ◽  
2008 ◽  
Vol 41 (4) ◽  
pp. 153-158
Author(s):  
Uroš Klanšek ◽  
Mirko Pšunder
Keyword(s):  
Nonlinear Programming ◽  
Objective Function ◽  
Project Scheduling ◽  
Programming Approach ◽  
Project Duration ◽  
Numerical Example ◽  
Activity Duration ◽  
The Cost ◽  
Total Project Cost ◽  
Total Project

Cost Optimal Project SchedulingThis paper presents the cost optimal project scheduling. The optimization was performed by the nonlinear programming approach, NLP. The nonlinear total project cost objective function is subjected to the rigorous system of the activity precedence relationship constraints, the activity duration constraints and the project duration constraints. The set of activity precedence relationship constraints was defined to comprise Finish-to-Start, Start-to-Start, Start-to-Finish and Finish-to-Finish precedence relationships between activities. The activity duration constraints determine relationships between minimum, maximum and possible duration of the project activities. The project duration constraints define the maximum feasible project duration. A numerical example is presented at the end of the paper in order to present the applicability of the proposed approach.

scholarly journals Efficient Procedure to Scheduling Construction Projects at the Planning Phase

2019 ◽  
Vol 7 (1) ◽  
pp. 60-80 ◽  
Author(s):  
Matiwos Tsegaye
Keyword(s):  
Cost Estimation ◽  
Construction Projects ◽  
Cost Optimization ◽  
Efficient Procedure ◽  
Start Date ◽  
Time Optimization ◽  
Planning Phase ◽  
Short Period ◽  
The Cost ◽  
Construction Schedule

Abstract The construction industry is one of the most important activities that contributes towards the economic growth of any nation. However, the sector has been experiencing problems of cost and time overruns, particularly the problems are significant for the lowest-bid awarded construction projects in the developing countries where inappropriate planning is reported to be one of the major causes. Thus, the paper aims at developing an integrated scheduling approach for construction projects during the planning phase from a project owner’s perspective. The proposed approach integrates cost estimation and schedule in light of practical activity precedence and mathematical cost optimization using different project commencement dates. The study has shown that cost and time optimization model could yield impractical results unless double precedence relations (start-to-start plus finish-to-finish) are imposed between some activities such as trench excavation and pipe laying. It has also demonstrated that the cost and time budgeted during the planning phase would substantially deviate from actual if the planned construction start date slips from the plan, particularly for short period projects. The proposed approach demonstrated in the paper can sufficiently allow planning engineers to develop a comprehensive construction schedule so that the cost and time overruns in the lowest-bid awarded construction projects can be reduced. The paper provides empirical insights into how a robust construction schedule is developed from an owner’s perspective. Cost-time optimization and risk analysis results obtained from manual computation might reduce the reasonable accuracy of the desired cost and schedule integration unless each activity is assigned its own calendar.

scholarly journals Elemental geochemistry of the Upper Cretaceous reservoir and surrounding formations applied in geosteering of horizontal wells, Lebăda Field – Western Black Sea

2020 ◽  
Vol 76 ◽  
pp. 1
Author(s):  
Ionuţ Mihai Prundeanu ◽  
Ciprian Chelariu ◽  
David Rafael Contreras Perez
Keyword(s):  
Horizontal Wells ◽  
Cost Effective ◽  
Geochemical Data ◽  
Elemental Geochemistry ◽  
Solid Foundation ◽  
A New Technique ◽  
The Cost ◽  
Mineral Concentrations ◽  
Total Project Cost ◽  
Total Project

The precise landing and steering of horizontal wells using conventional mudlogging and Logging While Drilling (LWD) data is a particular challenge for the Lebăda Field, offshore Romania. The use of a new technique of elemental geochemistry analysis (or chemosteering) became an option for the identification of Cenomanian, Turonian–Coniacian–Santonian, Campanian and Eocene strata. This has enabled more accurate placement of the horizontal development wells within the desired reservoir target interval. Geochemical data enabled the identification of chemostratigraphic zones C1, C2, C3 and zone R that correspond to the reservoir section. The application is a result of the geochemical zonation performed using elements and ratios that are sensitive to depositional environment, sea level change, heavy mineral concentrations and siliciclastic input namely: Sr/Ca, Zr/Th, Si/Zr and Si/K. In ascending stratigraphic order, the ratio thresholds of zone C3 are Zr/Th > 11, Sr/Ca > 1.1, Si/Zr < 22 and Si/K < 19, while zone R corresponds to 5.5 < Zr/Th < 11, Sr/Ca < 1.1, Si/Zr > 22 and Si/K > 19. C2 zone is defined by Zr/Th < 5.5, Sr/Ca > 1.1, Si/Zr < 22 and Si/K < 19 and C1 zone is characterized by Si/Zr > 22 and Si/K > 19. The selected geochemical ratios indicate a strong geochemical zonation. In the case of offset wells, 85.9% of the data confirmed the proposed classification and 89.4% for the real-time application case. The zone R shows a strong contrast with the surrounding formations facilitating critical decisions during well placement and geosteering, increasing the reservoir exposure by 28%. The quantitative approach delivered very valuable results, providing a solid foundation to define correlation and well landing intervals. Simultaneously, the cost of the method represents a fraction of the LWD cost and 0.15% of the total project cost, making it very cost effective and a standard approach for future projects.

scholarly journals Optimasi Biaya dan Waktu Proyek Konstruksi dengan Lembur dan Penambahan Tenaga Kerja

2021 ◽  
Vol 17 (1) ◽  
pp. 35-46
Author(s):  
Dinda Fardila ◽  
Nuur Robbyatul Adawyah
Keyword(s):  
Data Analysis ◽  
Cost Efficiency ◽  
Time Cost ◽  
Optimum Time ◽  
Time Efficiency ◽  
Project Cost ◽  
Trade Off ◽  
The Cost ◽  
Total Project Cost ◽  
Total Project

ABSTRACT                                                                         In the construction of a construction project, there are three main elements: time efficiency, minimal costs, and appropriate quality. This study aims to calculate changes in the cost and time of project implementation with variations in overtime and additional workforce. Data analysis using Microsoft Project 2010 program and Time-Cost Trade-Off method. The results of this study indicate that (1) the optimum time and costs due to overtime are obtained at the project age of 235 working days with a total project cost of IDR 8,438,038,832 with a project time efficiency of 5 days (2.13%) and a project cost efficiency of IDR 3.559,695 (0.042%). (2) The optimum time and cost due to the addition of labor is the best choice with the results obtained at the project age of 226 working days with a total project cost of IDR 8,429,832,759 with a project time efficiency of 14 days (6.19%) and cost-efficiency. project amounting to Rp. 11,779,674 (0.14%). ABSTRAKDalam pelaksanaan pembangunan suatu proyek konstruksi, terdapat tiga unsur utama yaitu waktu yang efisien, biaya minimal dan mutu yang sesuai. Tujuan dari penelitian ini adalah menghitung perubahan biaya dan waktu pelaksanaan proyek dengan variasi lembur dan penambahan tenaga kerja. Analisis data menggunakan program Microsoft Project 2010 dan metode Time Cost Trade Off. Hasil penelitian ini menunjukkan bahwa (1) Waktu dan biaya optimum akibat lembur didapat pada umur proyek 235 hari kerja dengan total biaya proyek sebesar Rp8.438.038.832 dengan efisiensi waktu proyek sebanyak 5 hari (2,13%) dan efisiensi biaya proyek sebesar Rp3.559.695 (0,042%). (2) Waktu dan biaya optimum akibat penambahan tenaga kerja menjadi pilihan terbaik dengan hasil yang didapat pada umur proyek 226 hari kerja dengan total biaya proyek sebesar Rp8.429.832.759 dengan efisiensi waktu proyek sebanyak 14 hari (6,19%) dan efisiensi biaya proyek sebesar Rp11.779.674 (0,14%).

scholarly journals Cost Estimation Process of Remote Sensing Satellites

2021 ◽  
Vol 11 (2) ◽  
pp. 78-85
Author(s):  
Dechamma K K ◽  
◽  
Mohith C G ◽  
Suma Mirji ◽  
Rahul Kumar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Regression Analysis ◽  
Cost Estimation ◽  
Deterministic Model ◽  
Knowledge Building ◽  
Cost Model ◽  
Technical Knowledge ◽  
Building Relationships ◽  
Technical Parameters ◽  
The Cost

Forecasting cost of satellites is not a recent development in space agencies, they were in practice from the beginning using traditional methods. The attempt to make it simpler, quicker and accurate; established the path to build a model by incorporating statistics, technology and technical knowledge. Building relationships between satellite cost and the technical parameters affecting them directly or indirectly became the basis of the model. The building of the cost model is more vexing than it looks. It requires data to perform regression analysis, which can be linear or nonlinear along with transformations. This paper also specifies the significance of the uncertainty impacting the cost associated with the technical parameters and the method of estimation. The overall model is mapped into three parts; the manpower and facility cost model being the deterministic bottom-up model and the combination of probabilistic and deterministic model for satellite cost.

scholarly journals Comparison of the Performance of “Unit Area Cost Method” (UACM) and “Unit Price Method” (UPM) Used in Estimating the Costs of the Reinforced Concrete Multi-Storey Housing Buildings

2021 ◽  
Author(s):  
Latif Onur Uğur ◽  
◽  
Kadir Penbe
Keyword(s):  
Regression Analysis ◽  
Reinforced Concrete ◽  
Error Rate ◽  
Cost Estimation ◽  
Unit Area ◽  
Linear Regression Analysis ◽  
Estimation Method ◽  
Error Rates ◽  
Unit Price ◽  
The Cost

Unit Price Method (UPM) and Unit Area Cost Method (UACM) are widely used in the cost of reinforced concrete multi-storey housing buildings. In this study, it is aimed to determine the cost estimation method with high performance (its use will provide an advantage to the estimator over the other) by comparing the cost estimates in the modeling by making “Regression Analysis” (RA), with the data of such struction. In the literature review, studies of equivalent and different structures were evaluated. In modeling; Number of rooms, floor area, total area, number of floors, floor height, facade area, facade void area, Bathroom/wc areas, balcony areas, building height are parameters. UPM and UACM based costs which were created with the data of 2020 of 41 similar structures (38 for modelling, 3 for tests) were used as independent variables, and cost models were created with linear regression analysis. The results were randomly selected and compared with test groups that were not used in these models, and the error rates and performances of the methods were tested. According to the comparison, in the UACM analysis, there was a high R2 value in 6 data and a low error rate in 8 predictions; In the UPM analysis, it was determined that an equally high R2 value and a low error rate occured in 7 predictions. As a result, UACM reached a better performance in finding the estimated cost; It has been observed that using it in cost estimation gives better results. However, even if UACM performed better, the difference in error rates is very low, at 2.7%.

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