This research project seeks to develop a new class of manufacturing decision-making methods based on machine learning, which refers to computational systems for deriving knowledge, strategies, or decision structures from such information as performance data, observations, or past experiences. The proposed methodology will provide a framework for intelligent, adaptive manufacturing decision making with learning capabilities. It will also incorporate a general model for automating manufacturing decision support that is capable of progressive performance improvements. Besides the development and analysis of the learning-based manufacturing decision methodology, the research plan also includes the validation of the methodology by simulation experiments and by testing it in real-world manufacturing environments. !K !K F : : ( Times New Roman Symbol & Arial 0 0 " h v Ev E A abstract of Shaw SBR-9321011 Hal Arkes Hal Arkes
