Prediction of total manufacturing costs for stamping tool on the basis of CAD-model of finished product

Ficko, Mirko; Drstvenšek, Igor; Brezočnik, Miran; Balič, Jože; Vaupotic, B.

doi:10.1016/j.jmatprotec.2005.02.013

Cited by 37 publications

(28 citation statements)

References 7 publications

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“…Consequently, estimation uncertainty and risks decrease, so more accurate and reliable results can be expected. Estimation methods differ in accordance with the project stage in which they are used [3], [5] and [6] and are divided into:…”

Section: The Project Estimation Processmentioning

confidence: 99%

“…The estimation process in the mold making business most commonly relies on human intuitive methods [5], or a combination of intuitive and analogical estimation methods. Mold makers put major emphasis on retrieving accurate project estimation with minimal time consumption, because a large number of quotations have to be processed in order to achieve sufficient order load.…”

Section: Fig 2 Expert Estimation Solution Spacementioning

confidence: 99%

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Neural Network-Based Model for Supporting the Expert Driven Project Estimation Process in Mold Manufacturing

Florjanič¹,

Govekar²,

Kuzman³

2013

SV-JME

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The mold making industry is project driven, and as such it has to cope with the characteristics of an individual production process. One of the major sources of risk in project management is the inaccurate forecast of project costs, demand, and other impacts [1]. In the mold production process it is crucial to minimize uncertainty in the early project estimation phase. The estimation phase is commonly a human expert driven activity which is sensitive to the expert's bias. This bias can lead to an underestimation of project resources when the estimator is overconfident, or to over-estimation of project resources when the estimator does not have sufficient confidence that all aspects of the project can be properly covered. Both scenarios have a negative impact on future business. In the case of underestimation, the project will bring economic loss, and in the case of overestimation, it will most likely be assigned to a competitive supplier. The estimator's key competence is to properly collect and evaluate all significant information for making the project estimation successful. The contradiction lies in the fact that the estimator should spend minimal time necessary on estimation activity since usually less than 10% of all offers turn into orders in the mold making industry, as stated in [2] to [4].Estimations in the mold manufacturing business still rely heavily on intuitive methods, which are subjective and prone to reliability and repeatability problems. A solution for these problems is addressed in this article, with the development of a supported expert driven project estimation process.In the project estimation process the volume of manufacturing hours represents one of the most important pieces of information. It reflects the majority of costs in the final project price, and it most significantly shapes the project schedule. The research objective is to develop an ANN-supported, expert driven project estimation process to improve the estimation of the volume of manufacturing hours in the mold production. In addition to the development of a reliable estimation model, it is also very important to properly position the supporting model in the expert driven estimation process. Therefore, in addition to model building, the problem of proper position of the supporting model will be addressed in the paper.Following these aims, first an overview of estimation process is given. Then, the solution for the problem of proper placement of an estimation support model is addressed. Furthermore, the proposed ANN-based model for estimation of the volume of manufacturing hours is presented. Finally, the results of ANN modelling are presented and discussed. THE PROJECT ESTIMATION PROCESSA major challenge of the project estimation process in general is to achieve sufficient project estimation reliability within minimal time consumption for this operation. Estimation reliability is directly related to the amount and quality of the data available at the moment the estimation process takes place. As shown in Fig. 1, the availabi...

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Section: The Project Estimation Processmentioning

confidence: 99%

Section: Fig 2 Expert Estimation Solution Spacementioning

confidence: 99%

Neural Network-Based Model for Supporting the Expert Driven Project Estimation Process in Mold Manufacturing

Florjanič¹,

Govekar²,

Kuzman³

2013

SV-JME

View full text Add to dashboard Cite

show abstract

“…Several authors, such as Tang et al [17], construct relationships between final part geometrical features and tooling costs. In a similar vein, Ficko et al [18] identify the cost-defining geometric features of previously produced stampings and then estimate the cost of new stampings based on their empirical findings. For the production of small batch sizes, Poli [19] states that, due to short forming times, and therefore low energy and labor costs, the die and sheet metal account for the majority of costs.…”

Section: Introductionmentioning

confidence: 99%

An Environmental and Cost Analysis of Stamping Sheet Metal Parts

Cooper

Rossie

Gutowski

2016

Journal of Manufacturing Science and Engineering

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Little work has been done on quantifying the environmental impacts and costs of sheet metal stamping. In this work we present models that can be used to predict the energy requirements, global warming potential, human health impacts, and costs of making drawn parts using zinc (kirksite) die-sets and hydraulic or mechanical presses. The methodology presented can also be used to produce models of stamping using other die materials, such as iron, for which casting data already exists.An unprecedented study on the environmental impacts and costs of zinc die-set production was conducted at a leading Michigan die-maker. This analysis was used in conjunction with electrical energy measurements on forming presses to complete cradle-to-gate impact and cost analyses on producing small batch size hood and tailgate parts. These case studies were used to inform a generalized model that allows engineers to predict the impacts and costs of forming based on as little information as the final part material, surface area, thickness and batch size (number of units produced).The case studies show that press electricity is an insignificant contributor to the overall impacts and costs. The generalized models highlight that while costs for small batch production are dominated by the die-set, the environmental impacts are often dominated by the sheet metal. These findings explain the motivation behind research into die-less forming processes such as incremental sheet forming, and emphasize the need to minimize sheet metal scrap generation in order to reduce environmental impacts.

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“…Epistemic uncertainty is a subjective and reducible kind of uncertainty that stems from lack of knowledge or data about the process or the materials [5]. At the early stages manufacturing costs but it must be taken under a significant level of epistemic uncertainty and the effect of random uncertainty is negligible [6]. In this paper, a new approach, called Reliability Based Economical Optimization (RBEO) is proposed for early design optimization of sheet metal forming processes under epistemic uncertainty, based on the minimisation of direct variable industrial costs, rather than quality or reliability.…”

Section: Introductionmentioning

confidence: 99%

Reliability Based Economical Optimization of Sheet Metal Forming Processes

Strano

2010

Int J Mater Form

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In metal forming, optimization under uncertainty, e.g. by Reliability Based Design Optimization (RBDO), in combination with the results of FEM simulations has been recently opened. In RBDO, optimal process solutions should be robust with respect to uncontrollable or unpredictable variations of working conditions. Many try to solve the problem of optimizing some sort of objective function, under a reliability constraint. However, to the author's knowledge, all the objective functions previously presented are expressed in terms of part quality (e.g. thickness uniformity) or process robustness with respect to failures (wrinkles, tears, etc.). In this paper a new approach is proposed for design optimization, under uncertainty, based on the minimisations of direct variable industrial costs (namely the material costs and the failure costs) rather than quality or reliability. It is called Reliability Based Economical Design Optimization (RBEO), and is demonstrated using the #1 benchmark case of Numisheet 1993. A simple cost model is used in order to build an economical objective function, which directly correlates the traditional technological design variables of the stamping process (e.g. the blank holder force) to the manufacturing costs.

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Prediction of total manufacturing costs for stamping tool on the basis of CAD-model of finished product

Cited by 37 publications

References 7 publications

Neural Network-Based Model for Supporting the Expert Driven Project Estimation Process in Mold Manufacturing

Neural Network-Based Model for Supporting the Expert Driven Project Estimation Process in Mold Manufacturing

An Environmental and Cost Analysis of Stamping Sheet Metal Parts

Reliability Based Economical Optimization of Sheet Metal Forming Processes

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