Self Optimising Clean in Place (SOCIP)

生产线的清洁是食品和饮料生产中最耗时和最昂贵的阶段之一。清洁也是效率最低的阶段之一，因为原位清洁（CIP）系统是为最坏的情况而设计和调试的。这是食品原料和操作条件，已知的污垢设备最.在日常使用中，这通常会导致生产线的过度清洁，给食品制造商带来巨大的损失。这主要是由于不必要的生产线停机和资源利用。该可行性项目将开发一个小型实验室规模的实验装置，并评估不同的在线传感器和人工智能的潜力，以量化内部污垢的水平，并真实的时间自动优化CIP过程。这项技术将大大减少清洁所需的时间、成本和对精神的影响。blic项目摘要

Cleaning of production lines is one of the most time consuming and costly stages of food and drinkmanufacturing. Cleaning is also one of the most inefficient stages as Clean in Place (CIP) systems are designedand commissioned for the worst case scenario. This is the food materials and operating conditions which areknown to foul the equipment the most. In daily use this often results in the over cleaning of the productionlines coming at a great expense to food manufacturers. This is primarily due to unnecessary line downtime andresource utilisation. This feasibility project will develop a small lab scale experimental rig and assess thepotential of different online sensors and artificial intelligence to quantify the level of internal fouling andautonomously optimise the CIP process in real time. This technology will dramatically reduce the time, cost andenvironmental impact required for cleaning.blic Project Summary