A Study of Data Mining Methodology and Its Application to Industrial Engineering

  • Sami Abdul Qader Mahammed Al - Ademi, Dr. Sanjay Singh Bhadoriya


Data mining has recently become one of the most progressive and promising fields for the extraction and manipulation of data to produce useful information. Thousands of businesses are using data mining applications every day in order to manipulate, identify, and extract useful information from the records stored in their databases, data repositories, and data warehouses. With this kind of information, companies have been able to improve their businesses by applying the patterns, relationships, and trends that have lain hidden or undiscovered within colossal amounts of data. For example, data mining has produced information that enables companies to create profiles of current and prospective customers to help in gaining and retaining their customers. Other uses of data mining include development of cross selling and marketing strategies, exposure of possible crimes or frauds, finding patterns in the access of users to their web sites, and process improvement. The power of data mining is yet to be fully exploited by industry. Manufacturing, for example, is one of the new fields in which data mining tools and techniques are beginning to be used successfully. Process optimization, job shop scheduling, quality control, and human factors are some of the areas in which data mining tools such as neural networks, genetic algorithms, decision trees, and data visualization can be implemented with great results.