Application of machine learning for production optimization

The photovoltaic industry is driven by manufacturing cost and is continuously working on optimizing its production output. As production sites are increasing significantly in size, large data sets are generated that require adequate processing for line optimization. As in other industries machine learning is one way to address this task. In this study a machine learning algorithm is used for trouble shooting of production data to identify parameters which are responsible to high variances in energy conversion efficiency.