Cost-Estimation Methods for Drying

2006 ◽  
Author(s):  
Tadeusz Kudra ◽  
Zbigniew Sztabert
Keyword(s):  
Cost Estimation ◽  
Estimation Methods

Biorefinery implementation for recovery debottlenecking at existing pulp mills- Part II: Techno-economic evaluation

TAPPI Journal ◽  
2012 ◽  
Vol 11 (8) ◽  
pp. 17-24 ◽  
Author(s):  
HAKIM GHEZZAZ ◽  
LUC PELLETIER ◽  
PAUL R. STUART
Keyword(s):  
Cost Estimation ◽  
Process Model ◽  
Black Liquor ◽  
Pulp Mill ◽  
Value Added ◽  
Economic Assessment ◽  
Extraction Process ◽  
Estimation Methods ◽  
Precipitation Process

The evaluation and process risk assessment of (a) lignin precipitation from black liquor, and (b) the near-neutral hemicellulose pre-extraction for recovery boiler debottlenecking in an existing pulp mill is presented in Part I of this paper, which was published in the July 2012 issue of TAPPI Journal. In Part II, the economic assessment of the two biorefinery process options is presented and interpreted. A mill process model was developed using WinGEMS software and used for calculating the mass and energy balances. Investment costs, operating costs, and profitability of the two biorefinery options have been calculated using standard cost estimation methods. The results show that the two biorefinery options are profitable for the case study mill and effective at process debottlenecking. The after-tax internal rate of return (IRR) of the lignin precipitation process option was estimated to be 95%, while that of the hemicellulose pre-extraction process option was 28%. Sensitivity analysis showed that the after tax-IRR of the lignin precipitation process remains higher than that of the hemicellulose pre-extraction process option, for all changes in the selected sensitivity parameters. If we consider the after-tax IRR, as well as capital cost, as selection criteria, the results show that for the case study mill, the lignin precipitation process is more promising than the near-neutral hemicellulose pre-extraction process. However, the comparison between the two biorefinery options should include long-term evaluation criteria. The potential of high value-added products that could be produced from lignin in the case of the lignin precipitation process, or from ethanol and acetic acid in the case of the hemicellulose pre-extraction process, should also be considered in the selection of the most promising process option.

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 Multilayer Taxonomy of Cost Estimation Techniques, Looking at the Whole Product Lifecycle

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Stefania Altavilla ◽  
Francesca Montagna ◽  
Marco Cantamessa
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Life Cycle ◽  
Cost Estimation ◽  
Product Life Cycle ◽  
Recent Literature ◽  
Estimation Methods ◽  
Product Lifecycle ◽  
Conscious Decision ◽  
Decision Making Tool

Product cost estimation (PCE) still draws the attention of researchers and practitioners, even though it has been extensively discussed in the literature for more than 20 years. This is due to its central impact on the company's performance. Nowadays, the adoption of cost estimation methods seems to be limited, despite the multitude of examples and applications available. A possible reason is the multitude of approaches and techniques proposed in the literature, which, instead of representing a guide for enabling possible implementations, actually create confusion and ambiguity on their appropriateness for a particular application. Hence, this paper aims to provide a systematic review of the recent literature in the field of PCE, and intensively investigates the aspects that can enable a more conscious decision on the type of technique to be adopted. This results in the identification of five different perspectives, which can be taken simultaneously into account. By combining the different viewpoints, a new multilayer framework is derived, with a specific focus on the whole product life cycle. The proposed framework can be used as a decision-making tool by both researchers and practitioners. In fact, the former group can benefit from the new structure, as a way to identify new areas of possible research opportunities. The latter group is provided an operative guide for the application in industrial contexts.

Integrating fuzzy case-based reasoning, parametric and feature-based cost estimation methods for machining process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fentahun Moges Kasie ◽  
Glen Bright
Keyword(s):  
Cost Estimation ◽  
Intelligent System ◽  
Machining Process ◽  
Estimation Methods ◽  
Case Based Reasoning ◽  
Cost Estimates ◽  
Content Type ◽  
Estimation Techniques ◽  
Feature Based ◽  
Case Based

Purpose This paper aims to propose an intelligent system that serves as a cost estimator when new part orders are received from customers. Design/methodology/approach The methodologies applied in this study were case-based reasoning (CBR), analytic hierarchy process, rule-based reasoning and fuzzy set theory for case retrieval. The retrieved cases were revised using parametric and feature-based cost estimation techniques. Cases were represented using an object-oriented (OO) approach to characterize them in n-dimensional Euclidean vector space. Findings The proposed cost estimator retrieves historical cases that have the most similar cost estimates to the current new orders. Further, it revises the retrieved cost estimates based on attribute differences between new and retrieved cases using parametric and feature-based cost estimation techniques. Research limitations/implications The proposed system was illustrated using a numerical example by considering different lathe machine operations in a computer-based laboratory environment; however, its applicability was not validated in industrial situations. Originality/value Different intelligent methods were proposed in the past; however, the combination of fuzzy CBR, parametric and feature-oriented methods was not addressed in product cost estimation problems.

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.

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.

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