Abstract
In this study, a design of Mamdani type fuzzy inference systems is presented to predict tensile properties of as-cast alloy. To improve manufacturing of light weight cast components, understanding of mechanical properties of cast components under load is important. The ability of deterministic models to predict the performance of a cast component is limited due to the uncertainty and imprecision in casting data. Mamdani type fuzzy inference systems are introduced as a promising solution. Compared to other artificial intelligence approaches, Mandani type fuzzy models allow for a better result interpretation. The fuzzy inference systems were designed from data and experts’ knowledge and optimized using a genetic algorithm. The experts’ knowledge was used to set up the values for the inference engine and initial values for the database parameters. The rule base was automatically generated from the data which were collected from casting and tensile testing experiments. A genetic algorithm with real-valued coding was used to optimize the database parameters. The quality of the constructed systems was evaluated by comparing predicted and actual tensile properties, including yield strength, Y.modulus, and ultimate tensile strength, of as-case alloy from two series of casting and tensile testing experimental data. The obtained results showed that the quality of the systems has satisfactory accuracy and is similar to or better than several machine learning methods. The evaluation results also demonstrated good reliability and stability of the approach.
Highlights
Casting is an important engineering area, which provides very effective methods to produce near net shape components and offers a great design freedom [12]
Each data set contains a set of input-output data pairs
The first data set, when x2 represents the percentage of Cu, contained 67 data points
Summary
Casting is an important engineering area, which provides very effective methods to produce near net shape components and offers a great design freedom [12]. The performance of a cast component depends on a number of factors. Deterministic models will be highly useful in a part design process as it will be distinct differences between different design and solutions It must be pointed out, that other imperfections resulting from melt treatment and casting process will inherently display a stochastic behaviour. One such example is oxide films [3] being discrete particles of varying size formed during processing that will end up in discrete locations but not in a repeatable fashion. This will affect many different material properties, because of their amount and through their orientation related to load direction
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