scholarly journals A Cost Model for 3D Woven Preforms

2022 ◽  
Vol 6 (1) ◽  
pp. 18
Author(s):  
James Clarke ◽  
Alistair McIlhagger ◽  
Dorian Dixon ◽  
Edward Archer ◽  
Glenda Stewart ◽  
...  
Keyword(s):  
Cost Reduction ◽  
Control Algorithm ◽  
Cost Model ◽  
Woven Fabrics ◽  
Learning Curves ◽  
Cost Information ◽  
Model Framework ◽  
Variate Analysis ◽  
Technical Cost ◽  
Manufacturing Time

Lack of cost information is a barrier to acceptance of 3D woven preforms as reinforcements for composite materials, compared with 2D preforms. A parametric, resource-based technical cost model (TCM) was developed for 3D woven preforms based on a novel relationship equating manufacturing time and 3D preform complexity. Manufacturing time, and therefore cost, was found to scale with complexity for seventeen bespoke manufactured 3D preforms. Two sub-models were derived for a Weavebird loom and a Jacquard loom. For each loom, there was a strong correlation between preform complexity and manufacturing time. For a large, highly complex preform, the Jacquard loom is more efficient, so preform cost will be much lower than for the Weavebird. Provided production is continuous, learning, either by human agency or an autonomous loom control algorithm, can reduce preform cost for one or both looms to a commercially acceptable level. The TCM cost model framework could incorporate appropriate learning curves with digital twin/multi-variate analysis so that cost per preform of bespoke 3D woven fabrics for customised products with low production rates may be predicted with greater accuracy. A more accurate model could highlight resources such as tooling, labour and material for targeted cost reduction.

Application of Math-Based Marketing and Financial Tools in an Automated Parametric Design Framework

2004 ◽  
Author(s):  
Joseph A. Donndelinger ◽  
Peter A. Fenyes
Keyword(s):  
Market Share ◽  
Parametric Design ◽  
Cost Model ◽  
Design Parameters ◽  
Parameter Study ◽  
Design Framework ◽  
Net Income ◽  
Cost Estimates ◽  
Technical Cost ◽  
S Model

A suite of math-based marketing and financial tools has been deployed and exercised within an automated, multidisciplinary parametric design framework. This suite of tools includes a market share estimator based on Cook’s S-Model, a Technical Cost Model for estimating the variable and fixed costs of the vehicle’s body system, a database of cost estimates for other vehicle systems, and a profit estimator developed from a standard accounting template. Development of the S-Model market share estimator included completion of a Demand-Price analysis for the midsize sedan segment and collection of publicly available value curves predominantly covering the powertrain performance and interior roominess disciplines. A flexible input-output interface was developed for the Technical Cost Model to provide a means of propagating changes in body design parameters throughout the framework. A series of exercises including analysis of a baseline vehicle, optimization of a hypothetical vehicle concept for net income, and a hypothetical architectural parameter study were conducted to demonstrate the capabilities of a multidisciplinary parametric design framework enabled with marketing and financial tools. These exercises demonstrate that existing engineering and business discipline tools can effectively interoperate to design for profitability in a multidisciplinary parametric design environment. They also illustrate several key challenges in automated design for profitability, such as those encountered in defining the role of price as a design variable in a tightly coupled design-for-profit system and in generating cost estimates using a continuously variable design representation.

Weather Radar Network Benefit Model for Nontornadic Thunderstorm Wind Casualty Cost Reduction

2020 ◽  
Vol 12 (4) ◽  
pp. 789-804 ◽  
Author(s):  
John Y. N. Cho ◽  
James M. Kurdzo
Keyword(s):  
Cost Reduction ◽  
Flash Flood ◽  
Cost Model ◽  
Weather Radar ◽  
Storm Event ◽  
Radar Network ◽  
Density Maps ◽  
Update Rate ◽  
Statistical Relationships ◽  
First Time

AbstractAn econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic thunderstorm wind casualty rates are observed to be negatively correlated with better warning performance. In combination, these statistical relationships form the basis of a cost model that can be differenced between radar network configurations to generate geospatial benefit density maps. This model, applied to the current contiguous U.S. weather radar network, yields a benefit estimate of $207 million (M) yr−1 relative to no radar coverage at all. The remaining benefit pool with respect to enhanced radar coverage and scan update rate is about $36M yr−1. Aggregating these nontornadic thunderstorm wind results with estimates from earlier tornado and flash flood cost reduction models yields a total benefit of $1.12 billion yr−1 for the present-day radars and a remaining radar-based benefit pool of $778M yr−1.

Quantifying the Importance of Solar Soft Costs: A New Method to Apply Sensitivity Analysis to a Value Function

2020 ◽  
Vol 142 (12) ◽  
Author(s):  
Sita M. Syal ◽  
Erin F. MacDonald
Keyword(s):  
Sensitivity Analysis ◽  
Cost Reduction ◽  
Research Funding ◽  
Value Function ◽  
Cost Model ◽  
Department Of Energy ◽  
Potential Cost ◽  
Industry Growth ◽  
Cost Of Energy ◽  
Solar Research

Abstract This paper presents a new approach to build a decision model for government funding agencies, such as the US Department of Energy (DOE) solar office, to evaluate solar research funding strategies. High solar project costs—including technology costs, such as modules, and soft costs, such as permitting—currently hinder many installations; project cost reduction could lead to a lower project levelized cost of energy (LCOE) and, in turn, higher installation rates. Government research funding is a crucial driver to solar industry growth and potential cost reduction; however, DOE solar funding has not historically aligned with the industry priorities for LCOE reduction. Solar technology has received significantly higher research funding from the DOE compared to soft costs. Increased research funding to soft cost programs could spur needed innovation and accelerate cost reduction for the industry. To this end, we build a cost model to calculate the LCOE of a utility-scale solar development using technology and soft costs and conduct a sensitivity analysis to quantify how the inputs influence the LCOE. Using these results, we develop a multi-attribute value function and evaluate six funding strategies as possible alternatives. We find the strategy based on current DOE allocations results in the lowest calculated value and the strategy that prioritizes soft cost results in the highest calculated value, suggesting alternative ways for the DOE solar office to prioritize research funding and potentially spur future cost reduction.

RBF Neural Network Based Adaptive Tracking Control for a Class of Nonlinear Plant Using Stochastic U-Model

2011 ◽  
Vol 474-476 ◽  
pp. 1209-1214 ◽  
Author(s):  
Bin Wang ◽  
Cai Liu ◽  
Xue Li Wu ◽  
Lei Liu
Keyword(s):  
Neural Network ◽  
Tracking Control ◽  
Control Algorithm ◽  
Design Procedure ◽  
Least Mean Square ◽  
Unknown Parameters ◽  
Model Framework ◽  
Adaptive Tracking Control ◽  
Adaptive Tracking ◽  
Wide Range

In this paper an adaptive tracking control algorithm and its step by step implementation procedure are developed for a class of nonlinear plants within a U-model framework with unknown parameters. With the author’s previous justification, not only the control oriented model represents a wide range of smooth (polynomial) nonlinear dynamic plants (without using linearisation approximation at all), but also make almost all linear control system design techniques directly applicable (with a root solver bridging the linear design and calculation of controller output). A new technique is proposed to design an online control algorithm using the Radial Basis Functions Neural Network (RBFNN). The plant parameters are estimated online and are used to update the weights of the RBFNN. The weights update equations are derived based on the well known LMS (least mean square). A number of simulated case studies are conducted to illustrate the efficiency of the claimed insight and design procedure.

scholarly journals An Accuracy Investigation of Product Cost Estimation in Automotive Die Manufacturing

2017 ◽  
Vol 8 (7) ◽  
pp. 1 ◽  
Author(s):  
Julia Bendul ◽  
Vasile Apostu
Keyword(s):  
Cost Estimation ◽  
Cost Reduction ◽  
Real Data ◽  
Estimation Methods ◽  
Design Phase ◽  
Cost Information ◽  
Capacity Decisions ◽  
Accuracy Level ◽  
Application Fields ◽  
The Cost

Automotive die manufacturers face the constant challenge of producing qualitative products while having to reduce costs. However, cost reduction measures are rather insignificant during the actual manufacturing process as the most important cost-impacting decisions are taken during the design phase. Cost estimation methods attempt to determine the production cost already in the design phase; the cost can be broken down and therefore the plan times of manufacturing processes can be pre-calculated, thus enabling early capacity decisions. Many researchers have been focusing for decades on developing efficient cost estimation methods. Yet their scarce access to cost information meant that most of the developed methods could not be evaluated with real data and thus their implementation in practice being challenged. This paper reviews and classifies cost estimation methods and investigates the accuracy of the estimate based onpractical application in 190 cases. The overall aim is to determine the accuracy level of the studied methods in practice and therefore identify their application fields.

Analytic, Numerical, and Stochastic Comparison of Forming Force Modeling at Deep Drawing and Backward Extrusion on the Same Al 99.5 F7 Parts

2007 ◽  
Vol 344 ◽  
pp. 419-426 ◽  
Author(s):  
Branimir Barisic ◽  
Miljenko Dino Math ◽  
Branko Grizelj
Keyword(s):  
Deep Drawing ◽  
Cost Reduction ◽  
Direct Application ◽  
Stochastic Comparison ◽  
Forming Force ◽  
Modeling And Analysis ◽  
Backward Extrusion ◽  
Force Modeling ◽  
Design And Manufacturing ◽  
Manufacturing Time

In order to determine the forming force in deep drawing and backward extrusion processes (on Al 99.5F7 specimens) the analytical, numerical and stochastic modeling and analysis of forming force on the basis of the Box-Wilson’s multi factorial experimental designs by use of rotatable experimental design were carried out. The goal of the paper is to predict the force in these different forming processes giving identical parts by means of different modeling approaches. This study will seek to compare the results of these modeling solutions with experimental results serving to check the correction and the verification of analytic, stochastic and numerically obtained results. Also, the scope of the present paper is to evaluate different parameters affecting these processes and to examine some experimental procedures in laboratory scale for the listed material in order to give more useful information in numerical and stochastic computations and also, to define the correlation among the parameters of these processes in order to improve the existing one and to raise it to a higher techno economic level. The increasing tendency for industrial parts cost reduction, quality improvement, materials savings, and the shortening of design and manufacturing time is more focused on this way of analysis of processes. These investigations are a basis for general conclusions about the forming force and they have a direct application in the projecting of these processes, tools and forming systems.

Development Steps for Concentrating Solar Power Technologies With Maximum Impact on Cost Reduction: Results of the European ECOSTAR Study

Solar Energy ◽  
2005 ◽  
Author(s):  
Robert Pitz-Paal ◽  
Ju¨rgen Dersch ◽  
Barbara Milow ◽  
Fe´lix Te´llez ◽  
Alain Ferriere ◽  
...  
Keyword(s):  
Cost Reduction ◽  
Power Plants ◽  
Solar Power ◽  
Low Cost ◽  
Performance Model ◽  
Concentrating Solar Power ◽  
Cost Information ◽  
Power Cycles ◽  
Electricity Cost ◽  
The Cost

Beside continuous implementation of concentrating solar power plants (CSP) in Europe, which stipulate cost reduction by mass production effects, further R&D activities are necessary to achieve the cost competitiveness to fossil power generation. Therefore the cost range of 15–20 cents€/kWh for the currently planned CSP systems in Europe has to be decreased by a factor of 2–4. The European Concentrated Solar Thermal Roadmap (ECOSTAR) study that is conducted by leading CSP research institutes in Europe intends to stipulate the direction for R&D activities in the context of cost reduction. It uses a common methodology approach, based on an annual performance model to identify the most essential technical innovations that will reduce the cost of seven different CSP system concepts, which are currently under promotion world wide. The potential of innovative concepts for solar light weight concentrators, low-cost thermal energy storage concepts, solar receivers/absorbers and power cycles are in the main focus of interest. The results of the study include a description of the value of CSP power, the sensitivity of the electricity cost information, a list of innovations that have been investigated and recommendations for the focus of further R&D work.

scholarly journals A Model for Prioritization of Improvement Opportunities Based on Quality Costs in the Process Interdependency Context

2019 ◽  
Vol 30 (3) ◽  
pp. 278-293
Author(s):  
Maja Glogovac ◽  
Jovan Filipovic
Keyword(s):  
Cost Reduction ◽  
Cost Model ◽  
Model Assumption ◽  
Quality Cost ◽  
Quality Costs ◽  
Process Cost ◽  
The Difference ◽  
Process Level

In this paper, the PAF (preventive-appraisal-failure) quality costs model is used on the process level, in order to identify those processes which are critical as a top-priority for improvement. The elements of quality costs are considered in relation to the outputs of the processes, where the principle that one process affects the quality of another process by its outputs is taken into account. That is why the failure costs of the affected processes should also be assigned to the quality costs of the observed process. Using the factors proposed in the Process cost model, costs are identified and calculated for each process for two moments: the current (before improvements) and desired (after improvements). Improvements are implemented on the basis of the causes of nonconformity analysis and according to the PAF model assumption that preventive and appraisal activities reduce failure costs and the total costs of quality. The difference between the total costs of quality in two observed moments is seen as the greatest possible quality cost reduction for the observed process. This value is used as a criterion for ranking the processes according to their priority for improvements, taking into account the assumption of the PAF model that greater costs mean lower quality and hence a higher priority for improvement.

scholarly journals The Effect of Resource Consumption Accounting on Accounting Pricing Decisions- An Exploratory Study in the Men's Clothing Factory in Najaf: أثر محاسبة استهلاك الموارد على قرارات التسعير المحاسبية – دراسة استطلاعية في معمل الألبسة الرجالية في النجف الأشرف

2019 ◽  
Vol 3 (13) ◽  
Author(s):  
YASIR SAHIB MALIK, AHMED MAHER MOHAMMED ALI, HASSNAIN KADHIM
Keyword(s):  
Cost Reduction ◽  
Indirect Costs ◽  
Scientific Basis ◽  
Resource Consumption ◽  
Cost Information ◽  
Important Conclusion ◽  
Pricing Decisions ◽  
Statistical Program ◽  
Statistical Metrics

  The research aims to indicate role of Resource Consumption Accounting as a management and costing technique. That is compatible with the rapid developments and changes in the external environment, provided by the information and scientific basis in the allocation of indirect costs; Identifying and measuring idle power and costs contribute to scientific support accounting pricing decisions. This is in the light of the intense competition and the multiplicity of alternatives. To achieve this goal Authors selected a random sample represented in the men's clothing factory in Najaf. Sample include selected deliberate ones represented by administrative and accounting staff included (52) an individual. For test the hypothesis of the research, Authors used statistical program (SPSS), and a set of other statistical metrics. The most important conclusion is that the Resource Consumption Accounting contributes to support pricing decisions by contributing to the provision of accurate cost information, achieve cost reduction, contributes to the process of planning, improving productivity, and profitability. The most important recommendations were the need to apply the research sample to the technique of Resource Consumption Accounting, including the reduction in costs, identify and measure unused energy, and manage this energy. Which contributes to supporting accounting pricing decisions.  

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