Improving the Performance of Manufacturing Technologies for Advanced Material Processing Using a Big Data and Machine Learning Framework. (2019)

• Record Type: Journal Article
• Authors: Kotenko, Igor; Saenko, Igor; Branitskiy, Alexander
• Is Part Of: Materials today. Volume 11:Part 1(2019)
• Page Start: 380
• Page End: 385
• Publication Date: 2019
• Subjects: material processing -- big data -- machine learning -- principal component analysis -- classifier; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2018.12.162
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: The paper offers a new approach to improving the performance of the materials knowledge analysis based on Big Data processing and machine learning. We consider a framework in which thread functioning of five machine learning mechanisms intended for solving the classification problem is realized. Classifier operation results are exposed to majority voting. The experimental assessment of performance and accuracy of framework operation is made on the data set containing technological data of the production line. Assessment showed that the offered framework provides a scoring on productivity of materials knowledge processing by 7.4 times.