Optimization of Process Parameters by Reliability-Based Uncertainty Modeling of Cold Rolling Process

Abstract

Metal working processes can often be expressed in a reliability format. Information about present and anticipated reliabilities in metallurgical processes, in conjunction with decision models, provides a rational and powerful decision-making tool. In practice uncertainties arise in predicting service or lifetime loads in considering the variability in material properties, workmanship, process dimensions, environmental conditions, inspection test data, maintenance and so on. A wide range of materials with different elastic moduli, yield stresses, strain hardening and friction co-efficient constitute specific characteristics in a metal working process. Thus a metal working process may be defined as a collection of one or more related objects. Consequently, decisions related to rolling processes are based on uncertain or incomplete information. Finite element based process simulation can offer valuable guidelines on how the current process parameters should be modified to meet the requirements on the process and the product. This work represents a continued effort towards developing a sound methodology for modelling uncertainties in rolling process with reference to the reliability assessment. Based on the information obtained from the finite element simulation, investigations are conducted to assess the structural integrity of final product. The objective of this work is to use probabilistic methods to represent sources of uncertainty and to attain optimum set of points of rolling by iteration to achieve controlled microstructure of the finished product.