This study deals with the fundamentals of intelligent computer-aided processes in thermal and thermochemical treatments. The aim of this study is the improvement of the conformity of the actual post-treatment properties with the assumed properties, thereby improving the repeatability of the process results. A detailed study was conducted involving low-pressure carburizing and low-pressure nitriding. The principal objective of the literature review was to better understand the cause-and-effect relationship in these processes and to develop a methodology of designing functional and effective processes of low-pressure thermal and thermochemical treatment, using effective computation methods. The paper contains a synthetic presentation of modeling methods, in particular of artificial intelligence methods; it also analyses the opportunities and threats associated with the methods.

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