Quality insights: artificial neural network and taxonomical analysis of activity networks in quality engineering

The resurgence and advancement of artificial intelligence (AI) has spurred new research interests in applying or re-applying proven techniques from the 1990s to challenges in business and industry. The area of quality engineering and technology is particularly amenable to the application of AI techniques. Quality engineering programs are predicted on recurring quality projects that are made up of specific activities. The proper management of such activities is a precursor for the success of any quality program. This research paper explores the application of the proven technique of artificial neural network to activity networking in the management of quality programs.