With increased attendance of digitalization among society and even in industry on which we primarily focused on paper below, there is also growing amount of data, which are collected in one way or another. Therefore we have presented machine learning as a tool that helps to analyze large amount of data. In our case, data is collected through sensors, while some of measurements are further modified for the purpose of visualization and deeper presentation of different process within manufacturing. Latter enables operators and leaders, to get insights over the work and to manage company business with ease. Results derived from comparative analysis of taken models show that in case of predicting manufacturing efficiency with previous data for this variable random forest method performs best, while other two methods perform similarly bad.
|
