Darren Wilkinson

Using Machine Learning to recommend optimal configurations of production processes on the shop floor

Electronic manufacturer setups are optimised to match production orders to achieve improved productivity and efficiency. Using machine learning algorithms, forecasts can be made using simulations to select the optimal factory configuration.   Actual performance is then fed back into the learning loop comparing against predictions to further train the machine learning solution. With shop floor dashboards available, it provides instant feedback of performance and defects to measure operational efficiency.  

The LMAC example is applicable to a wide range of industries where process improvement and efficiency is required.  Learn how applying Industry 4.0 methods enables new insights to process efficiency that reduces costs and increases performance.