In this work, the effects of 75 mm thick cast iron, (casting mould YIV) composition (Cu) and heat treatment were investigated on the microstructure and mechanical properties (hardness, elongation, tensile strength, yield strength) of ductile iron castings. As a result of adding Cu, the amount of pearlite is at 80% reduces of amount of ferrite. Normalizing of non-alloy cast iron increases the amount of pearlite to 70%. It also, increases tensile strength (659 MPa) and hardness (248 HB). Studied metallographic crossections were made from the grip sections of the tensile specimens. The structure composition and the characteristics of graphite were determined by computer image analysis. Measurements of graphite of non-alloy cast iron after normalizing and in cooper cast iron indicate the approximate amount of precipitates of graphite and their approximate average diameters. The applied normalizing and the additive alloy (Cu) were established to give comparable mechanical properties and structure of matrix in thick-walled castings.
The paper presents Gupta's relational decomposition technique expanded on linguistic level. It allows to reduce the hardware cost of the fuzzy system or the computing time of the final result, especially when referring to First Aggregation Then Inference (FATI) relational systems or First Inference Then Aggregation (FITA) rule systems. The inference result of the hierarchical system using decomposition technique is more fuzzy than of the classical system. The paper describes a linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system. It allows to decrease or even totally remove a redundant fuzziness of the inference result.
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