This paper is in two parts describing the study and selection of grinding conditions. This first part is concerned with the study of grinding conditions and selection strategy. Grinding is a complex manufacturing process with a large number of interacting variables. Before designing the selection system, it is necessary to define the variables and to find which variables should feature in the selection process. Consideration is therefore given to the relationships and interactions between these variables. The study is limited to the external cylindrical plunge grinding operation. Existing techniques employed to deal with the selection of grinding conditions are investigated, including data retrieval methods, empirical models and artificial intelligence methods. Finally, a blackboard strategy is presented for the selection of grinding conditions. The knowledge agents consist of case-based reasoning, neural network reasoning and rule-based reasoning.
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