Case Study | Quality

Manufacturing Analytics to improve Quality and Utility Costs

Utilizing existing architectures and modern AI/ML tools; improving First Pass Quality by utilizing process (time series), manufacturing (event) data, and continuous analytics to reduce utility costs and optimize process.

The Results

plant applications industrial data visualization

The Challenge

Looking for the optimal way to roast their products. The current method of monitoring resulted with a lot of product in process. Wanted good quality product at the lowest cost.

The Solution

Current Historian and MES in place with years of data. Added several sensors like temperature, humidity, and others. Combined with the quality results, it was sent to a data scientist who was able to model the data and give the models back to the plant so they could predict product quality.

For Manufacturing Analytics, it is critical to have years of raw data before you know what issue you are trying solve or optimize.

- Kelly Forbes, VP Operations

industrial data visualization dashboard

INS3 Tip

Not sure where to start? Start by collecting the time and event series data. Analytics run best with a lot of correlated data and you never know the variable that will be the most important. Or if you’ve got questions, let us help.