Casting defects is one and the only limitation in any casting process. Sand casting process too suffers from the same problem. Finding out the optimum condition towards acquiring minimum casting defects is very critical. The normal method that most of the companies use is the trial and error method. But due to limitations like error prone results, expensive and time consuming, this method causes too much cost to company. In this paper, an attempt has been made to minimize the casting defects by optimizing the process parameters of sand casting defect using Artificial Neural Network (ANN). The Toolbox of the MATLAB software is used to run the different values of the parameters. Parameters are selected on the basis of survey from different industry and a rigorous research of the previous paper on this topic. Before that a program was prepared in MATLAB to generate the values of different parameter by using their highest and smallest values which has been collected from a local casting industry. In our first attempt to optimize the sand casting process parameters, it is found that if we consider randomly both input and output just by considering their limits the results are satisfactory just up to a limit. And it changes if the parameters are being changed. For specific conditions the result is found to be 3.175 as casting defect. Later on a new type of program is generated based on the relation of sand casting parameters and sand casting defects. Three specific casting defects are considered called, Expansion