Digital Twin in Dairy ProductionSight Machine
Analytics & Modeling - Digital Twin / Simulation
Food & Beverage
|[Data Management - Data Analysis]|
Sight Machine was delighted to find that integrating process and batch data allowed the company to optimize production settings for its manufacturing process, both upstream and downstream. We maximized the quality and throughput of its production process—the mixing, blending, and packaging of cheese. Combining chemistry and statistics, we also calculated the optimal amount of water to add to the vats; the best time to clean the vats to avoid waste (of curds and water); and ways to decrease the dairy company’s energy use, thereby enhancing sustainability. Our models, moreover, interpreted data from raw materials, also derived from sensors, to forecast completion times for the vats of cheese.
|[Data Management - Data Simulation]|
Working with chemists at the plant, the data science team also designed a physics-based digital twin of the machinery that produces the cheese. The digital twin modelled essential information such as how milk acts inside the separator, how long it needs to ferment, and when to drain the tanks.
|[Efficiency Improvement - Productivity]|
Sight Machine’s experts designed a dashboard that generated automated recommendations for the employees on the production lines. The dashboard recommended optimal times to run and stop the machine’s lines and alerted workers when to begin and end the fermentation times. Those recommendations enabled a continuous flow of production.
Sight Machine helped this global dairy company increase the yield of its product line by 5 percent.