Applying Mechanistic AI for Accessing the Production Technology Flexibility Potential

Machine control systems have undergone a significant transformation, transitioning from centralized computer numeric control to automatic control. One of the key challenges in this evolution stems from the complex and varied nature of many manufacturing systems, characterized by multiscale, Multiphysics, dynamic, and stochastic elements. This complexity has spurred numerous innovations at the convergence of artificial intelligence (AI), data analytics, and manufacturing sciences. Consequently, the question of how the manufacturing industry can leverage the technology flexibility available is addressed through the inherent adaptive capabilities of AI. This research aims to articulate and establish a process for imbuing flexibility into manufacturing processes, leveraging the technology of the manufacturing system with the integration of AI. The objective is to harness the adaptive potential of technology-based flexibility using AI, employing a combination of AI methods, mechanism-driven principles, and engineering technology. In this context, flexibility denotes a manufacturing process's ability to respond effectively to new system requirements, whether planned or unforeseen. The paper asserts that the value of system flexibility is an intrinsic advantage of manufacturing system technology. A qualitative research approach is employed to investigate and elucidate how the manufacturing system can be modeled to unlock its flexibility potential, utilizing Mechanistic AI applications.