乳制品生产中的数字孪生

全球领先的乳制品生产商

制造商必须像工匠一样培育奶酪，但要大批量生产——因此需要生产技术。大规模生产奶酪需要难以管理的机械和复杂的加工厂。为了更好地了解他们的运营，乳制品公司越来越多地转向数据分析。

乳品厂的化学家和工程师遇到了瓶颈，尤其是在以下方面：

-原料中蛋白质和脂肪的混合
-从上游炊具出来的批次的温度
-上游发酵过程输出的pH值

Sight Machine 的专家设计了乳品厂整个生产过程的数字模型。他们在机器上放置传感器并收集加工线各个方面的数据。专家们训练模型分析炊具和发酵数据，他们可以从中提出改进生产线的建议。例如，他们确定了发酵罐的最佳温度和释放时间；分离过程中使用的离心机的最佳速度和运行时间；并考虑了每日生产计划和原材料（牛奶和添加剂）到达工厂的变化。

Sight Machine 很高兴地发现，集成过程和批次数据使公司能够优化上游和下游制造过程的生产设置。我们最大限度地提高了其生产过程的质量和产量——奶酪的混合、混合和包装。结合化学和统计学，我们还计算了添加到大桶中的最佳水量；清洁大桶以避免浪费（凝乳和水）的最佳时间；以及减少乳制品公司能源使用的方法，从而提高可持续性。此外，我们的模型解释了来自原材料的数据，也来自传感器，以预测奶酪桶的完成时间。

数据科学团队与工厂的化学家合作，还设计了一个基于物理的数字双胞胎生产奶酪的机器。数字双胞胎模拟了基本信息，例如牛奶在分离器内的作用、发酵需要多长时间以及何时排空罐。

• [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.