Optimized Operation of Plant Using Process Analytic Techniques

该项目旨在将新一代数字工具嵌入到联合利华的研发中，然后进入工厂。个人护理产品（如洗发水）的批量生产目前需要校正阶段，以考虑原材料、配方和加工过程中的无形变化。这些校正阶段非常耗时，并导致生产时间的损失。将调查影响产品质量的原材料质量、成分和工艺因素以及作为工艺最后步骤的质量调整的必要性。由Perceptive Engineering提供的最先进的过程分析技术和材料表征方法将用于了解产品质量在过程中如何演变。将确定早期干预的机会，以确保在过程结束时实现良好的质量，而无需进行最后的调整步骤。预测批控制将在实验室规模上发展，以消除校正阶段。正确的第一次生产将在试点规模上进行演示。

This project aims to embed a new generation of digital tools into Unilever's research & development and then into factories. Batch production of personal care products, such as shampoo, currently requires correction stages to account for intangible variations in raw materials, formulation and processing. These correction stages are time consuming and result in lost production time. Raw material quality, compositional and process factors affecting product quality and the need for quality adjustments as a final step of the process will be investigated. State-of-the-art process analytic techniques, supplied by Perceptive Engineering, and material characterisation approaches will be used to understand how product quality evolves during the process. Opportunities for early intervention will be identified to ensure good quality is achieved at the end of the process without the need for a final adjustment step. Predictive batch control will be developed at the lab scale to eradicate the correction stage. Right first time production will be demonstrated at pilot scale.