Integrated Computational Materials Engineering: Extending from Design to Supply Management

Abstract

Integrated Computational Materials Engineering (ICME) has significantly matured during the last one decade, in terms of formal definition, thriving technical community, framework for workflow, textbooks, academic curriculum as well as few examples of their maturity into products. However, hitherto the scope of ICME has been limited to simultaneous optimization of design, materials and manufacturing processes for developing a robust and optimal product. Unfortunately, in this VUCA world (volatile, uncertain, complex and ambiguous), there is dynamic complexity of external influences, such as volatility in commodity prices with time, which renders the optimal choice determined by the ICME framework redundant within a short duration. The complexity of the problem further increases as different commodity prices fluctuate in unsynchronized manner at different periods of time with different amplitudes. The 3 × increase in cobalt price in 2018, spikes in nickel price in 2008 and ferrochromium in 2006 are clear examples of such unforeseen asymmetric distortions of commodity prices. Consequently, for a specific component, if an ICME approach is used to simultaneously optimize materials grade, design and manufacturing process, the selected preferred grade due to their superior cost–performance attributes at that specific time may not remain so in the future. In the present work, the ICME framework has been expanded by including dynamic ranking of material types and grades to manage such asymmetric commodity price volatility with time. The effectiveness of this approach has been illustrated with use case of an axle shaft with multiple grade optionality. In this example, it has been demonstrated that by exploration of multi-optionality at the initial design stage, the preferred grade ranking changes with commodity price asymmetric volatility. Furthermore, a predictive model has been developed to develop future material ranking strategy for a specific component in an OEM.