Purpose: The present paper describes a knowledge-based system (KBS) developed for selection of progressive die components to automate the design process of progressive dies in stamping industries。72602

Design/methodology/approach: The production rule based KBS approach of Artificial Intelligence (AI) has been utilized for constructing the proposed system。 The system has been structured into seven KBS modules。 Modules are user interactive and designed to be loaded in to the prompt area of AutoCAD。

Findings: The output of system modules includes the type and proper dimensions of progressive die components namely die block, die gages (front spacer and back gage), stripper, punches, punch plate, back plate, die-set and fasteners。 The system has been designed in such a way that the expert advices imparted by its modules are automatically stored in different output data files。 These data files can be further utilized for automatic modeling of die components and die assembly。

Research limitations/implications: Although the system is limited to the design of progressive dies only, yet it can be extended further for the design of other types of dies  also。

Practical implications: The proposed system is ready for use in sheet metal industries for quick selection of progressive die components。 The system can be implemented on a PC having AutoCAD software and therefore its low cost of implementation makes it affordable by small and medium sized stamping industries。

Originality/value: The proposed system is capable of accomplishing the time-consuming task of selection of progressive die components in a very short time period。

Keywords: Automation engineering processes; Knowledge-based system; Progressive die components

The design of progressive dies is a complex and highly specialized procedure [1]。 The perse nature of products produced by progressive dies demands a high level of knowledge on the part of the die designer that can only be achieved through years of practical experience [2]。 Selection of type and proper dimensions of die components is a major activity for designing a progressive die。 The traditional methods of carrying out this task require expertise and are largely manual and therefore tedious, time consuming and error-prone。 Commercially available CAD/CAM  systems  are  providing  assistance  in  drafting    and

analysis in die design process, but human expertise is still needed to arrive at the final design。 Also, the high cost associated with setting up such systems is quite often beyond the reach of small and medium sized sheet metal industries, especially in developing countries。 To overcome these problems, there is an urgent need to develop an intelligent system for progressive die design to assist die designers and process planners working in sheet metal industries, especially small and medium  sized  stamping industries。 The system should be capable of providing an intelligent aid to the die designers for automating the major activities of progressive die design process including selection of die components。

© Copyright by International OCSCO World Press。 All rights reserved。 2007

Knowledge-based systems (KBS) or expert systems [3] are the most significant practical products to emerge from 30 years of Artificial Intelligence (AI) research。 While there have been numerous applications of KBS in manufacturing, few of them concern press tools, and even fewer are for progressive dies。 Progressive die design is a very knowledge demanding process。 Designers often base their decisions on past  experience rather than theoretical knowledge and to some extent; it remains a process of trial and error。 In today’s highly competitive industrial scenario where there is a shortage of experienced die designers, the requirement of high quality products with short lead times and low cost have emphasized the importance and urgency of developing computer aided progressive die design systems with embedded and easily modifiable knowledge。 This is a task, which needs both existing conventional CAD technology and KBS approach [4, 5] and that is the aim of this research。 Various researchers [6-8] have used AI techniques to deal with the problems, which require domain expertise for their solution。 The main reason of there being only a few KBS developed for die design and even fewer for progressive dies, is the inherent difficulties to elicit the design know-how from experienced die designers and then to code the same into the knowledge base of an expert system [9]。 Also the use of these systems is very limited。 They can either handle only blanking and piercing operations or parts with relatively simple geometry。 Thus, there is a stern need to develop a low cost intelligent progressive die design system using both CAD and KBS approach collectively, which can be easily affordable by small and medium scale sheet metal industries。 The aim of present work is to develop a KBS named as PROCOMP for selection of progressive die components to automate the design process of progressive dies in stamping industries。