Abstract: Metal stamping die design is a complex, experiencebased
and time-consuming task. Various artificial intelligence (AI)
techniques are being used by worldwide researchers for stamping die
design to reduce complexity, dependence on human expertise and
time taken in design process as well as to improve design efficiency.
In this paper a comprehensive review of applications of AI
techniques in manufacturability evaluation of sheet metal parts, die
design and process planning of metal stamping die is presented.
Further the salient features of major research work published in the
area of metal stamping are presented in tabular form and scope of
future research work is identified.
Abstract: In this paper a low cost knowledge base system (KBS)
framework is proposed for design of deep drawing die and procedure
for developing system modules. The task of building the system is
structured into different modules for major activities of design of
deep drawing die. A manufacturability assessment module of the
proposed framework is developed to check the manufacturability of
deep drawn parts. The technological knowledge is represented by
using IF- THEN rules and it is coded in AutoLISP language. The
module is designed to be loaded into the prompt area of AutoCAD.
The cost of implementation of proposed system makes it affordable
for small and medium scale sheet metal industries.