Cost estimation of automotive sheet metal components using knowledge-based engineering and case-based reasoning

Responding quickly to a customer's request with a sufficiently precise offer is one of the challenges faced by almost every manufacturing enterprise. Currently, necessary information is passed from department to department and in many cases this information is waiting to be processed. Further, number of offers that are converted into orders is small making the process of preparing an offer relatively costly. Research has been carried out to automatically determine process plans and estimate cost of simple sheet metal components. Unfortunately, this research has not been extended to simultaneously determine process plan and cost of complex deep drawn components. To overcome these drawbacks and to substantially improve the efficiency and precision of the time consuming process of offer preparation, a new methodology is presented which utilizes knowledge-based engineering and case-based reasoning. Inputs obtained to create an offer can be used to generate basic tool structure for the downstream processes.