Profit-Driven Methodology for Servo Press Motion Selection under Material Variability

Abstract

Servo presses enable new types of forming motion profiles that can be used to stamp difficult materials, such as high strength steels. This paper presents an application of Bayesian statistics to intelligently select which motion profile maximizes the expected utility given the properties of the incoming material. Bayesian logistic regression was used in conjunction with expected utility to estimate manufacturing returns, which can be used to make informed process decisions. A use case is presented, which demonstrates that the Smart Forming Algorithm can increase expected returns by more than 20%.

Monitoring of fluctuating material properties for optimizing sheet-metal forming processes: a systematic literature review

“…For a stamping process, variations of material were measured with non-destructive testing and different motions for a servo-press were evaluated [29]. The data of this experiments were then evaluated using Bayesian logistic regression resulting in a model that determines motion profiles for a servo-press based on material characteristics [31]. Maretta and Di Lorenzo proposed a method were meta-models and Monte Carlo simulation were combined to analyze the influence of coil-to-…”

“…Hot rolling [8,[21][22][23] Cold rolling [24] Roller levelling [25][26][27] Stamping [28] RQ3 Stamping [29][30][31] Deep drawing [32][33][34][35][36][37][38][39][40] Bending [41][42][43] Table 2. Summary of the publication conducted in the SLR.…”