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 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 Estimasi Biaya Konseptual Pada Jembatan Beton Bertulang Dengan Metode Indek Biaya

2017 ◽  
Vol 13 (2) ◽  
pp. 105
Author(s):  
Bagyo Mulyono ◽  
Paulus Setyo Nugroho
Keyword(s):  
Cost Estimation ◽  
Early Stage ◽  
Cost Model ◽  
Construction Project ◽  
Public Works ◽  
Cost Index ◽  
Reinforced Concrete Bridge ◽  
Construction Project Cost ◽  
The Cost ◽  
Available Information

<p class="DRAbstrak">Cost estimation is the art of estimating the amount of cost required for an activity based on available information. The conceptual cost estimate is an early stage in planning a construction project. This estimate provides the cost that must be budgeted for a construction project. Cost conceptual estimates have low accuracy because the time of calculation and available information is limited. This study aims to obtain a conceptual model of the conceptual cost of short-spaced bridges. The method used is the cost index. The cost index is a figure indicating the cost per m2 of bridges at a given time. The required data are contract documents and drawings design that are built in 2012 - 2015 in Banyumas residency area. Span of bridge 4 - 38.8 meters and width of bridge 2 - 7 meters with caisson  foundation. The data were obtained from Dinas Bina Marga and Public Works Agency. The results showed that the conceptual cost model of reinforced concrete bridge with caisson foundation was BJiL = (100.540.56t2-404.528.636,58t + 406.914.286.088,58) x P x W, with t = year, P = span bridge, and W = bridge width. The error value of validation of this model is 2.31%.</p>

A Cost Model for the Metal Inert Gas (MIG) Welding Process

2007 ◽  
Author(s):  
Pradeep Kumar Tipaji ◽  
Venkat Allada ◽  
Rajiv Mishra
Keyword(s):  
Cost Estimation ◽  
Material Selection ◽  
Cost Model ◽  
Welding Process ◽  
Inert Gas ◽  
Mig Welding ◽  
Estimation Model ◽  
Cost Component ◽  
Cost Estimation Model ◽  
The Cost

A cost model is an important tool for product design and material selection. An efficient and effective cost estimation tool is necessary for early design evaluations. In this paper, a cost estimation model is presented that estimates the production cost for metal inert gas (MIG) welded joints. This model determines the cost incurred in fabricating each joint with a detailed explanation of each cost component / driver. Each cost component has been closely analyzed and the major cost components have been included in the cost model. We used this cost model to predict the cost of the forty two different joints joined using MIG welding technique. The results predicted by the MIG welding cost model have been compared to that quoted by an expert welder. Initial results show that the cost model and the expert cost estimates follow a similar general trend. Further study is needed to refine the MIG cost model.

A STUDY ON THE DEVELOPMENT OF A COST MODEL BASED ON THE OWNER'S DECISION MAKING AT THE EARLY STAGES OF A CONSTRUCTION PROJECT

2010 ◽  
Vol 14 (2) ◽  
pp. 121-137 ◽  
Author(s):  
Choong-Wan Koo ◽  
TaeHoon Hong ◽  
Chang-Taek Hyun ◽  
Sang H. Park ◽  
Joon-oh Seo
Keyword(s):  
Decision Making ◽  
Cost Estimation ◽  
Cost Model ◽  
Construction Project ◽  
Case Based Reasoning ◽  
Planning Stage ◽  
Attribute Weights ◽  
Early Stages ◽  
Minimum Criteria ◽  
The Cost

Decision making at the early stages of a construction project has a significant impact on the project, and various scenarios created based on the owner's requirements should be considered for the decision making. At the early stages of a construction project, the information regarding the project is usually limited and uncertain. As such, it is difficult to plan and manage the project (especially cost planning). Thus, a cost model that could be varied according to the owner's requirements was developed. The cost model that was developed in this study is based on the case‐based reasoning (CBR) methodology. The model suggests cost estimation with the most similar historical case as a basis for the estimation. In this study, the optimization process was also conducted, using genetic algorithms that reflect the changes in the number of project characteristics and in the database of the model according to the owner's decision making. Two optimization parameters were established: (1) the minimum criteria for scoring attribute similarity (MCAS); and (2) the range of attribute weights (RAW). The cost model proposed in this study can help building owners and managers estimate the project budget at the business planning stage. Santruka Sprendimu priemimas ankstyvuoju statybos projekto etapu turi didele itaka projektui ir ivairiems scenarijams, remiantis savininko reikalavimais, kuriu turi būti laikomasi priimant sprendimus. Ankstyvaisiais statybos projekto etapais informacijos apie projekta paprastai yra nedaug ir ji nera patikima. Del to sudetinga planuoti ir taisyti projekta (ypač išlaidu planavima). Todel šio tyrimo metu buvo sukurtas kainos modelis, kuris galetu būti keičiamas atsižvelgiant i savininko poreikius. Kainos modelis, kuris buvo sukurtas šio tyrimo metu, remiasi atveju analize, pagrista argumentu metodika (angl. CBR). Modelis siūlo samatinius skaičiavimus su panašiausiais ankstesniais atvejais, kurie yra skaičiavimo pagrindas. Šio tyrimo metu procesas buvo optimizuotas naudojant genetinius algoritmus, rodančius projektu skaičiaus kitima tam tikro modelio duomenu bazeje pagal savininko priimamus sprendimus. Buvo nustatyti du optimizavimo parametrai: 1) minimalūs kriterijai veiksniu panašumui ivertinti (angl. MCAS); 2) veiksniu svoriu vertinimo intervalas (angl. RAW). Kainos modelis, pasiūlytas šiame tyrime, gali padeti pastatu savininkams ir valdytojams ivertinti projekto biudžeta verslo planavimo etape.

New Approach in Cost Structuring of High Speed Hard Turning

2011 ◽  
Vol 264-265 ◽  
pp. 1003-1008 ◽  
Author(s):  
Muataz H.F. Al Hazza ◽  
Erry Yulian Triblas Adesta
Keyword(s):  
Cost Estimation ◽  
High Speed ◽  
Hard Turning ◽  
Cost Model ◽  
New Technology ◽  
Cost Estimating ◽  
New Approach ◽  
Cost Drivers ◽  
Optimum Solution ◽  
The Cost

Cost structuring of new technology is a critical mission which needs to be developed systematically to get accurate cost estimation. In this research a new approach was proposed and developed for cost structuring a new process. Cost modeling roadmap was proposed to guide the development of genetic cost model by integrating different cost estimating methods and supporting the optimum solution by using statistical techniques in modeling the cost in high speed hard turning, then by building logical relationships between the different effective variables through three levels of cost drivers; main drivers, process and technical drivers and final drivers. Finally a matlab model was developed for simulating the final cost drivers to study the effect of different parameters on the cost drivers.

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%.

scholarly journals The Optimization of Cost-Model for Join Operator on Spark SQL Platform

2018 ◽  
Vol 173 ◽  
pp. 01015
Author(s):  
Xin Lian ◽  
Tianyu Zhang
Keyword(s):  
Cost Estimation ◽  
Cost Model ◽  
Estimation Model ◽  
Network Resources ◽  
Operation Performance ◽  
Query Optimizer ◽  
Network Transmission ◽  
Cost Estimation Model ◽  
The Cost ◽  
Memory Resources

Spark needs to use lots of memory resources, network resources and disk I/O resources when Spark SQL execute Join operation. The Join operation will greatly affect the performance of Spark SQL. How to improve the Join operation performance become an urgent problem. Spark SQL use Catalyst as query optimizer in the latest release. Catalyst query optimizer both implement the rule-based optimize strategy (RBO) and cost-based optimize strategy (CBO). There are some problems with the Catalyst CBO module. In the first place, the characteristic of In-memory computing in Spark was not fully considered. In the second place, the cost estimation of network transfer and disk I/O is insufficient. To solve these problems and improve the performance of Spark SQL. In this study, we proposed a cost estimation model for Join operator which take the cost from four aspects: time complexity, space complexity, network transfer and disk I/O. Then, the most cost-efficiency plan could be selected by using hierarchical analysis method from the equivalence physical plans which generated by Spark SQL. The experimental results show that the total amount of network transmission is reduced and the usage of processor is increased. Thus the performance of Spark SQL has improved.

scholarly journals THE USE OF EXPLORATORY TUNNELS AS A TOOL FOR SCHEDULING AND COST ESTIMATION

2007 ◽  
Vol 13 (4) ◽  
pp. 280-287 ◽  
Author(s):  
Ahmed Abdallah
Keyword(s):  
Cost Estimation ◽  
High Speed ◽  
Deterministic Model ◽  
Management Tool ◽  
High Speed Railway ◽  
Project Data ◽  
The Cost ◽  
Double Track ◽  
Total Project ◽  
Structural Aspects

Exploratory tunnels are commonly used for examining the geotechnical and structural aspects of proposed tunnel alignments. This paper explores the utilisation of exploratory tunnels as a project management tool for estimating the cost and duration of construction for the entire project. Data were collected from the Kaponig 2,75 kilometers exploratory tunnel, a part of a double‐track high‐speed railway development in Austria. This knowledge and experience was used to evaluate the risks associated with design details for the final tunnel enlargement (alignment and grade, support requirements and excavation methods). A deterministic model based on Monte Carlo simulation was developed capable of predicting potential outcomes of the total project in terms of cost, duration and their associated probabilities.

scholarly journals A Micro-Level Compensation-Based Cost Model for Resource Allocation in a Fog Environment

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2954 ◽  
Author(s):  
Sudheer Kumar Battula ◽  
Saurabh Garg ◽  
Ranesh Kumar Naha ◽  
Parimala Thulasiraman ◽  
Ruppa Thulasiram
Keyword(s):  
Resource Allocation ◽  
Cost Estimation ◽  
Cost Model ◽  
Fog Computing ◽  
Cost Models ◽  
Efficient Resource ◽  
Micro Level ◽  
And Performance ◽  
The Cost ◽  
Allocation Algorithms

Fog computing aims to support applications requiring low latency and high scalability by using resources at the edge level. In general, fog computing comprises several autonomous mobile or static devices that share their idle resources to run different services. The providers of these devices also need to be compensated based on their device usage. In any fog-based resource-allocation problem, both cost and performance need to be considered for generating an efficient resource-allocation plan. Estimating the cost of using fog devices prior to the resource allocation helps to minimize the cost and maximize the performance of the system. In the fog computing domain, recent research works have proposed various resource-allocation algorithms without considering the compensation to resource providers and the cost estimation of the fog resources. Moreover, the existing cost models in similar paradigms such as in the cloud are not suitable for fog environments as the scaling of different autonomous resources with heterogeneity and variety of offerings is much more complicated. To fill this gap, this study first proposes a micro-level compensation cost model and then proposes a new resource-allocation method based on the cost model, which benefits both providers and users. Experimental results show that the proposed algorithm ensures better resource-allocation performance and lowers application processing costs when compared to the existing best-fit algorithm.

scholarly journals AN ANALYTICAL COST MODEL FOR INVESTMENT CASTING

2020 ◽  
Vol 1 ◽  
pp. 987-996
Author(s):  
M. Mandolini ◽  
F. Campi ◽  
C. Favi ◽  
P. Cicconi ◽  
M. Germani
Keyword(s):  
Investment Casting ◽  
Cost Estimation ◽  
Cost Model ◽  
Complex Task ◽  
Cluster Assembly ◽  
Design Phase ◽  
Production Lines ◽  
The Cost ◽  
Estimation Models ◽  
Cost Estimation Models

AbstractAnalytical cost estimation of investment casted products during design phase is a complex task since the quantity of parameters to be evaluated. So far, there is a short literature on such cost estimation models. This paper attempts to improve the cost model presented by Boothroyd and Dewhurst. Improvements (mainly focused on cluster assembly and investment, sintering and melting phases) were defined and verified in cooperation with two foundries. Tested on eight components, deviation between estimated and actual costs is around 14% for manual production lines and 6% for automatic ones.

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