Productivity Improvement is one of the most important strategies for every enterprise. Head cold forging is a widely common production process which can achieve economical processes and less energy consumption. Die is the major key of the forging process but how to perform an effective design, needs several years of experiences or using engineering tools for assistance. This paper proposes the collaborative die design and analysis by combining engineering methods and industrial experts to correct problems and to validate a new and complex design. DEFORM is used to investigate suitable parameters by guidance from the expert. One of the classical problem in the head cold forging is to make a small long complex stud. It is found from simulation that a five step of punch with suitable taper angle is the most effectiveness.
Quality is the most important aspect of fastener production for maintaining competitiveness and customer satisfaction. Nowadays, the quality control process is uncertain and complicated. Cold forging is used to produce preform fasteners via various processes. As a traditional measure of cold forging, quality prediction can be done using the normal probability method, but this approach is not effective or accurate enough. This paper proposes a novel quality prediction for preform fasteners using a fuzzy inference system and DEFORM simulation using an engineering software called DEFORM® system that can analyze metal forming. Multi-factors and criteria are considered, consisting of deformability, defects, stress, and time. The developed modeling can predict the cold forging quality at the stage of product design, which can associate decision making with production control. It can eliminate defects and reduce cost and time to rework. The case study is illustrated on the cold heading of stainless 341 using DEFORM, whereas the modeling is simulated by MATLAB.
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