A Rough-Cut Cost Estimation in a Finite-Capacity Stochastic Environment Based on Forced Idle Time Prediction

2008 ◽  
Author(s):  
Mark Eklin ◽  
Yohanan Arzi ◽  
Avraham Shtub
Keyword(s):  
Cost Estimation ◽  
Estimation Method ◽  
Idle Time ◽  
Estimation Methods ◽  
Shop Floor ◽  
Limited Capacity ◽  
Time Prediction ◽  
The Cost ◽  
Rough Cut ◽  
Cost Estimation Models

In recent years several researchers suggested cost estimation models that consider the limited capacity of the shop. In these studies, the stochastic nature of the shop floor is modeled by a time-consuming simulation. This paper proposes five alternative rough-cut cost estimation methods that can replace the simulation. Three of five methods based on forced idle time prediction. The study compares the cost estimations derived from these methods. A cost estimation method, based on the forced idle time of the bottleneck workstation, was found to be outperform the others. As the best method, the bottleneck-based method was compared to the actual order’s cost and was found as a replacement to simulation.

Research on Improved Staged Software Cost Estimation Method Based on COCOMO Model

2014 ◽  
Vol 989-994 ◽  
pp. 1501-1504
Author(s):  
Hai Yang
Keyword(s):  
Software Development ◽  
Cost Estimation ◽  
Software Maintenance ◽  
Estimation Method ◽  
Estimation Methods ◽  
Software Project ◽  
Software Cost Estimation ◽  
Software Cost ◽  
Cocomo Model ◽  
The Cost

The accuracy of software cost estimation is essential for software development management. By introducing and analyzing the estimation methods of software cost systematically, the paper discussed the necessary of considering the software maintenance stage and estimating the software cost by separating the procedure of software development into several small stages. Then a staged software cost estimation method based on COCOMO model was proposed. The use of the new software cost estimation method proposed by this paper not only contributes to the cost control of software project, but also effectively avoids the bias problem due to using by single cost estimation method so that the accuracy of cost estimation could be improved.

Keynote

2021 ◽  
Vol 48 (4) ◽  
pp. 3-3
Author(s):  
Ingo Weber
Keyword(s):  
Cost Estimation ◽  
Estimation Method ◽  
Main Topic ◽  
System Throughput ◽  
Distributed Ledger ◽  
Smart Contract ◽  
Distributed Ledger Technology ◽  
Wide Range ◽  
The Cost ◽  
Application Developers

Blockchain is a novel distributed ledger technology. Through its features and smart contract capabilities, a wide range of application areas opened up for blockchain-based innovation [5]. In order to analyse how concrete blockchain systems as well as blockchain applications are used, data must be extracted from these systems. Due to various complexities inherent in blockchain, the question how to interpret such data is non-trivial. Such interpretation should often be shared among parties, e.g., if they collaborate via a blockchain. To this end, we devised an approach codify the interpretation of blockchain data, to extract data from blockchains accordingly, and to output it in suitable formats [1, 2]. This work will be the main topic of the keynote. In addition, application developers and users of blockchain applications may want to estimate the cost of using or operating a blockchain application. In the keynote, I will also discuss our cost estimation method [3, 4]. This method was designed for the Ethereum blockchain platform, where cost also relates to transaction complexity, and therefore also to system throughput.

Insights on Cost Estimation Methods and its Uses in Software Project Design

2020 ◽  
pp. 166-169
Author(s):  
Aravindhan K
Keyword(s):  
Project Management ◽  
Cost Estimation ◽  
Estimation Methods ◽  
Software Project ◽  
Estimation Model ◽  
Software Projects ◽  
Software Applications ◽  
Software Companies ◽  
Cost Estimation Model ◽  
The Cost

Cost estimation of software projects is risky task in project management field. It is a process of predicting the cost and effort required to develop a software applications. Several cost estimation models have been proposed over the last thirty to forty years. Many software companies track and analyse the current project by measuring the planed cost and estimate the accuracy. If the estimation is not proper then it leads to the failure of the project. One of the challenging tasks in project management is how to evaluate the different cost estimation and selecting the proper model for the current project. This paper summarizes the different cost estimation model and its techniques. It also provides the proper model selection for the different types of the projects.

A grey rough set model for evaluation and selection of software cost estimation methods

2014 ◽  
Vol 4 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jun Liu ◽  
Jian-Zhong Qiao
Keyword(s):  
System Theory ◽  
Rough Set ◽  
Cost Estimation ◽  
Estimation Method ◽  
Grey System Theory ◽  
Estimation Methods ◽  
Software Cost Estimation ◽  
Grey System ◽  
Software Cost ◽  
Content Type

Purpose – Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs. Design/methodology/approach – Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness. Findings – The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided. Practical implications – Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method. Originality/value – This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.

Application of the life cycle cost estimation method in transport infrastructure managing

2019 ◽  
Vol 126 ◽  
pp. 5-14
Author(s):  
Anna Gobis ◽  
Kazimierz Jamroz ◽  
Łukasz Jeliński
Keyword(s):  
Life Cycle ◽  
Cost Estimation ◽  
Life Cycle Cost ◽  
Estimation Method ◽  
Research Problem ◽  
Transport Infrastructure ◽  
Life Cycle Thinking ◽  
Infrastructure Management ◽  
Practical Tool ◽  
The Cost

The transport infrastructure management should be in line with sustainable development. Actions and activities that combine the environmental, social, and infrastructure expenditures optimally should be undertaken. The article presents a concept of life-cycle thinking that resolves these problems. The life cycle cost estimation method is a practical tool for managing transport infrastructure. The LCC analysis mustn’t generate more work than the benefits of it. Therefore appropriate assumptions should be made in constructing the method. The method assumes basic assumptions, taking into account the extensive scope of the research problem: transport infrastructure. The result of this article is a proposed mathematical model for estimating life-cycle costs. In the end, the practical use of the proposed methodology for determining the cost of the horizontal marking is provided.

Manufacturing Feature Based Dynamic Cost Estimation for Design

2004 ◽  
Author(s):  
Harshal Patwardhan ◽  
Karthik Ramani
Keyword(s):  
Cost Estimation ◽  
Estimation Methods ◽  
Design Stage ◽  
Design Parameters ◽  
User Requirements ◽  
Geometric Information ◽  
Early Stages ◽  
Feature Based ◽  
The Cost ◽  
Manufacturing Feature

Due to the ever-increasing competition in today’s global markets, the cost of the product is rapidly emerging as one of the most crucial factors in deciding the success of the product. Decisions made during the design stage affect as much as 70–80% of the final product cost. Hence, a manufacturing cost estimation tool that can be used by the designer concurrently during the design phase will be of maximum benefit. A literature study of the available cost estimation tools suggests that a majority of these tools are meant for use in the later stages of the product development lifecycle. In the early stages of a product lifecycle, the only information that is available to the designer is related to geometry and material. Hence, the cost estimation methods that have been developed with the intent of being used in the early stages of design make use of the geometric information available at that stage of the design. Most of the earlier models that use parametric cost estimation and features technology consider the design features in their implementation. However, such models fail to consider “manufacturing based features” such as cores and undercuts. These manufacturing based features are very important in deciding the manufacturability and the cost of the part. The Engineering Cost Advisory System (ECAS) is a knowledge-based system that presents cost advice to the designer at the design stage after considering various design parameters and user requirements. Some of these design parameters can be extracted via standard Application Programming Interfaces (APIs). Moreover, ECAS uses innovative techniques of geometric reasoning and the hybrid B-rep-voxel model approach to extract manufacturing feature-based geometric information directly from the CAD input. By considering the manufacturing based features along with the design parameters, the ECAS architecture is applicable to a much wider variety of manufacturing processes. The complexity of the part, which is derived from the geometric parameters (manufacturing based and design based) and other non-geometric user requirements (e.g. quantity, material), is used to estimate the manufacturing effort involved in process specific activities. The final cost is then estimated based on this manufacturing effort and considering the hourly rates of labor and other contextual resources as well as material rates.

scholarly journals IPTEKS PERENCANAAN LABA KONTRIBUSI PADA USAHA MANUFAKTUR

2020 ◽  
Vol 4 (2) ◽  
pp. 30
Author(s):  
Novi Swandari Budiarso ◽  
Winston Pontoh
Keyword(s):  
Cost Estimation ◽  
Accounting Information ◽  
Estimation Methods ◽  
Fixed Costs ◽  
Planning And Control ◽  
Cost Behavior ◽  
The One ◽  
Implicit And Explicit ◽  
The Cost ◽  
And Control

The manufacturing firms have implicit and explicit goals and objectives. In order to achieve these goal and objective then manager needs accounting information. The accounting information created and used by management is intended primarily for planning and control decisions. One of the accounting information is cost accounting that can be used as a tool for planning the profit as the objective of the companies. Manufacturing costs are identified as variable costs or fixed costs under cost behavior analysis. Regression analysis is the one of the cost estimation methods in term to estimate the fixed costs and variable costs where the results of estimation are used to calculate the contribution margin.

Hybrid Spectral Clustering Algorithm and its Application in Cost Index Estimation

2012 ◽  
Vol 461 ◽  
pp. 695-701
Author(s):  
Bing Chen ◽  
Xue Qin Hu ◽  
Bei Zhan Wang ◽  
Yin Huan Zheng
Keyword(s):  
Cost Estimation ◽  
Spectral Clustering ◽  
Clustering Algorithm ◽  
Estimation Method ◽  
Cost Index ◽  
Actual Case ◽  
Project Cost ◽  
Index Estimation ◽  
The Cost ◽  
Spectral Clustering Algorithm

This paper proposed a new hybrid spectral clustering algorithm in which Mean Impact Value (MIV) was used in the cost dimension reduction. The processing of system implementation is as follows: first, we used BP neural network to determine the principal items materials, and then applied the spectral clustering algorithm to calculate the principal items price according to principal items materials; finally, principal items ratio estimation method has been used to do cost estimation. This paper took the Xiamen project cost station as the actual case and experimental results shown that this algorithm could meet the cost requirements of project cost station both in time efficiency and accuracy through parameters self-adjusting.

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