Process Predictive Analysis in Pulp and Paper Mill

• 分析与建模 - 预测分析
• 分析与建模 - 过程分析

• 造纸

• 流程制造

• 过程控制与优化

因此，常见的纸张破损会导致长达 60 分钟的停机时间，从而延迟每小时 1 万美元的潜在生产价值流程。因此，有缺陷的产品会造成财务损失并损害公司的声誉。提高质量和降低缺陷率每年可为您的公司带来数百万美元的收入。

Qsee 能够在生产过程中预测和优化质量测试，让操作员节省时间并获得所有生产产品的正确见解。

• The predictive quality AI technology analyzes and generates predictions during the production and alerts the operator the quality of the paper based on the parameters collected at that moment.

  It is able to create an automated independent tool to predict the CMT and other tests results during the production with 99% accuracy. Resulting also in 4 times more tests done than the quality control lab. False positives and negatives from the lab's results can be detected with 97% accuracy.

• Qsee predicts and explains (at least 40 minutes on average) paper strength and prevents paper web breaks to help manufacturers improve productivity and product quality before problems occur.

  Within a one month window, data was analyzed and predicted over 80% of the events. The predictive quality AI technology alerted (on average) 2 times and 40 minutes in advance per event.

• Reduction in downtime by predicting and preventing tears. Enabling the operators to proactively take action and reduce 50% of the web breaks. Automate ongoing Quality tests and reduce depreciation online in production. Optimize raw materials to reduce waste and returns due to bad quality and provide optimum and peak quality. It instills greater confidence with the increase in productivity and peak quality, resulting in significant yield improvement.

• Continuous failure prediction and root cause analysis, secured and backed up, improves process stability