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

doi:10.1016/j.jmatprotec.2005.02.013

Journal of Materials Processing Technology

Volumes 164–165, 15 May 2005, Pages 1327-1335

https://doi.org/10.1016/j.jmatprotec.2005.02.013 Get rights and content

Abstract

One of the orientations of the tool-making industry is towards shortening the time from enquiry to the supply of tools. The tool-making shops must prepare within the shortest possible time an offer for the manufacturer of the tool based on the enquiry in the form of the CAD-model of the final product. For preparation of a proper offer, the values of certain technological features occurring in the manufacture of the tool are needed. Most frequently the tool manufacturer is interested in total cost for manufacture of the tool. Because of lack of time for making a detailed analysis the total costs of tool manufacture are predicted by the expert on the basis of the experience gathered during several years of work in this area. In our work, we conceived an intelligent system for predicting of total cost of the tool manufacture. We limited ourselves to tools for manufacture of sheet metal products by stamping; the system is based on the concept of case-based reasoning. On the basis of target and source cases, the system prepares the prediction of costs. The target case is the CAD-model in whose costs we are interested, whereas the source cases are the CAD-model of products, for which the tools had already been made, and the relevant total costs are known. The system first abstracts from CAD-models the geometrical features, and then it calculates the similarities between the source cases and target case. Then the most similar cases are used for preparation of prediction by genetic programming method. The genetic programming method provides the model connecting the individual geometrical features with total costs searched for. In the experimental work, we made a system adapted for predicting of tool costs used for tool manufacture on the basis of a theoretic model. The results show that the quality of predictions made by the intelligent system is comparable to the quality assured by the experienced expert.

Introduction

In today's industry, where the costs play a very important role, the sheet metal products have replaced many products made by casting or forging. They have replaced also many complex composed products. The sheet metal products have become popular also due to low price, accuracy of dimensions, durability and favourable physical properties. Today, when new products appear on market within shorter time intervals and the development times are shorter, the branch of industry busy with tool manufacture assumes a vital role. The buyers of tools have a worked out idea about finished product, whereas the toolmakers are responsible for the tool design, preparation of the manufacturing technology and final manufacture of the tool.

The capacity of the tool-making shop to respond quickly to the enquiry is an important factor of competitivity. On the basis of the enquiry, it must obtain the answer to the following questions within the shortest possible time:

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Are we in a position to make the tool for the product concerned?
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Do we have the means for the manufacture of that tool?
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How much time do we need to be able to make the tool?
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How much the tool will cost?

The answers to the first two questions are rather trivial; if the company does not know the answers to these two questions it is probably better for it not to undertake the order at all. As the matter of fact the answers to these two questions are the result of cooperation between designers and technologist and depend on the state of skills and resources in the company [5]. The answer to the third question is very important particularly in the tool-making activities since adhering to the delivery times is one of the most important factors of success. However, it is often difficult to answer that question, since the answer depends on a variety of interconnected factors [12]. In the process of agreeing the toolmakers usually do not have the chance to determine the tool manufacturing times since they are specified by the clients. The tool-making shop must answer like this: “The delivery times can/cannot be met.” The answer to the fourth question, too, is very important, since only if it is precise, on the one hand the preparation of a competitive offer is possible and, on the other hand, undertaking jobs, bringing loss, is avoided. The tool price is limited upwards and downwards since the toolmakers cannot afford additional reserves in price because if the price is too high it is not competitive on the market and the order is not awarded. Contrarily, if the price is too low it brings loss to the company, which is not to the interest of the toolmaker.

In the stage prior to undertaking an order the tool-making shop is busy with the problem of specifying the technological features of tool. It has available scarce, usually only geometrical and physical information about the final product on the basis of which it must prepare its offer. The tool manufacture is a complex process including a variety of personnel, machines and technologies. Therefore, specifying the technological features, including the manufacturing costs, poses a serious problem. In addition, this activity is very time-limited. The output of this activity is of key importance for securing an order and for the business success of the order secured. The total costs increased for the expected profit are an important piece of information the company needs for negotiations with the tool buyer. The tool manufacturing costs can be rather precisely analytically determined, but analyses require additional time and cause additional costs. The toolmakers can afford none of these. In answer to the enquiry the offer must be prepared fastest possible, possibly within a few hours, but not later than in a few days – those times are specified by the client. However, the toolmakers try to avoid the additional costs of preparation of the offer which may not bring a new order at all.

It can be claimed that the problem of prediction of the total manufacturing costs has not been satisfactorily solved. Prediction relies too much on subjective influences of the expert. It is evident that the described problem needs a better solution. A system is needed in the offering stage to be able to determine the tool manufacture costs directly from the CAD-model of the finished product fastly and without the necessary expert knowledge.

This paper comprises five sections. Section 1 presents the problems of the tool-making industry occurring in preparation of the order. Section 2 describes how today the cost prediction is effected in tool-making companies. Here, the cost determination methods known are discussed. Section 3 presents the model of the intelligent system for cost prediction. Sections 3.1 Case-based reasoning, 3.2 Description of model, 3.3 Abstraction of CAD-model, 3.4 Similarities of cases, 3.5 Selection of the most similar source cases, 3.6 Genetic programming, 3.7 Preparation and use of formula explain the individual components and working principles of that system. Section 4 deals with the use of the presented system on a concrete problem and with the test results of the system. In Section 5, the results are discussed and the guidelines for future researches indicated.

Section snippets

Present situation

Although many methods of prediction of the tool manufacturing costs have been developed, the intuitive cost prediction is most frequently used for the reasons stated in the introduction. It means that for prediction of the manufacturing costs toolmakers use particularly their experience acquired in manufacture of similar tools. That experience is gathered in the form of expert knowledge of the employees. Thus the offers are prepared by experts, well familiarized with the tool manufacture, in

Model of intelligent system for prediction of tool manufacturing costs

It has been established that the toolmakers most frequently use the intuitive prediction of total manufacturing costs. Such cost prediction is used since it is not demanding with respect to time and cost. However, this approach is today obsolete and the problem requires a better solution. It is interesting that the cost prediction for the needs of preparation of offers in the customer multi-project environment has not yet been better solved, particularly if the importance of this activity from

Example and results

The input information into our model is the CAD-model of the final product, which is also the target case. The other input information into the model are the cases of tools already made. These CAD-models with costs are the source cases.

From CAD-model it is necessary first to abstract the data on the basis of which the case vectors will be determined and similarity between the source cases and the target case calculated. From CAD-models the following geometrical features have been identified:

Conclusion

We have conceived a general concept of the intelligent system for predicting total manufacturing costs of tools on the basis of the CAD-model of the finished product. We have decided on building intelligent system due to awareness that the problems treated cannot be solved by deterministic approaches. The system built on the basis of our model is viewed as useful particularly in preparation of offers for the manufacture of tools on the basis of CAD-model of the finished product.

Testing of the

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

Abstract

Introduction

Section snippets

Present situation

Model of intelligent system for prediction of tool manufacturing costs

Example and results

Conclusion

Robot. Comput. Integrated Manuf.

Decision Support for Case-based Applications

Wirtschaftsinformatik

Cost estimation during design step: parametric method versus case based reasoning method

Int. J. Adv. Manuf. Technol.

Use of parametric models in an economic evaluation step during the design phase

Int. J. Adv. Manuf. Technol.

Evaluation economique des activites de conception et de developpmet des produits noveaux

Adaptation in Natural and Artificial Systems