DOIONLINE 
DOIONLINE Publish In |
International Journal of Mechanical and Production Engineering (IJMPE)-IJMPE |
 Journal Home Volume Issue |
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Issue |
Volume-7,Issue-6 ( Jun, 2019 ) | |||||||||
Paper Title |
Continuous Monitoring and Control of a Production Process using Predictive Analytics | |||||||||
Author Name |
Saad Bashir Alvi, Johannes Gottschling | |||||||||
Affilition |
Faculty of Engineering, Institute for Technologies of Metals, Mathematics for Engineers, | |||||||||
Pages |
43-49 | |||||||||
Abstract |
Keeping a running production process in a proper working state requires continuous monitoring, anticipating potential problems in advance, looking for possible solutions to avoid these problems and selecting the most cost-effective solution among the choices. This work shows a solution approach, to the mentioned requirements using Machine Learning techniques, composed of three phases: a learning phase, a knowledge generation phase and a monitoring and control phase. Our approach, which is based on using a well-trained composite Machine Learning model to generate a sufficiently large database of pre computed prediction values, provides a method to reduce product defects, unplanned downtimes, energy consumption, CO2 emissions, and to increase the production speed and precision. Keywords - Casting, Machine Learning, Metal forming, Predictive Analytics. | |||||||||
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