Knowledge discovery in manufacturing datasets using data mining techniques to improve business performance

Recently due <span>to the explosion in data field, there is a great interest science areas such as big data, artificial intelligence, mining, and machine learning. Knowledge gives control power numerous manufacturing areas. Companies, factories, all organizations owners aim to benefit from their huge; recorded that increases expands very quickly improve business quality of products. In this research paper, knowledge discovery databases (KDD) technique has been followed, “association rules” algorithms “Apriori algorithm”, “chi-square automatic interaction detection (CHAID) analysis tree” have applied on real datasets belonging (Emisal factory). This factory annually loses tons production breakdowns occur daily inside factory, which leads loss profit. After analyzing understanding product processes, we found some lot days during lifecycle, these affect badly lifecycle led decrease sales. So, mined used mentioned methods above build predictive model will predict breakdown types help owner manage risks by taking accurate actions before happen.</span>