Optimized Operation of Plant Using Process Analytic Techniques

该项目旨在将新一代的数字化工具嵌入联合利华的研发，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，以解决原材料、配方和加工过程中的无形差异。这些校正阶段是耗时的并且导致生产时间的损失。将研究影响产品质量的原材料质量、组成和工艺因素以及作为工艺最后步骤的质量调整需求。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，以确保在流程结束时达到良好的质量，而不需要最后的调整步骤。将在实验室规模开发预测性批次控制，以消除校正阶段。正确的第一次生产将在试点规模。

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.