Vorwärts gehen, indem man etwas Besseres zurücklässt

In einer sich schnell verändernden Welt ist Technologie alles. Sie ist in der Gesellschaft und der Wirtschaft verankert. Es ist eine große Macht, die mit großer Verantwortung einhergeht.

Learn more
TIPS AI - your personal AI agent

TIPS AI is an AI-powered agent designed for our order-to-cash industry-specific Manufacturing Execution System (MES). It is a scalable software product with rapid deployment available for current and new customers. The AI-based solution enables monitoring and analytics to machines, production lines, and IIoT (Industrial Internet of Things) devices.

Typical use cases of TIPS AI include helping plant personnel achieve better process control in the paper production process and reducing unplanned equipment failures, which indirectly reduces web breaks. Additionally, it offers benefits such as throughput and quality improvements. Dedicated data analytics will also uncover the main reasons for unplanned stops (including web breaks) and how to avoid them.

 

Max Rüber

Head of Global Sales, Pulp, Paper & Fibre, Tietoevry Industry

Our three pilars of activity

TIPS Copilot

An AI assistant with TIPS knowledge helps users with all their TIPS questions. The system is ready to be tailored with the business's unique content and individual processes and usage. In addition to offering knowledge support, the system helps with ad-hoc reporting and provides data analytics.

Paper Runability AI

The solution uses machine learning to predict the runnability (usability) of a paper roll in the next process stage. It has also been trained on past cases that include detailed quality data of paper rolls and their outcomes — whether they performed successfully or not. With the patterns learned from past data, it can now accurately predict the runnability of a paper roll.

Microsoft Manufacturing Cloud

Predictive Maintenance: AI and machine learning are utilized for predictive maintenance to minimize equipment downtime and optimize maintenance schedules. Production Optimization: AI-driven analytics help in optimizing production processes, improving efficiency, and reducing waste. Quality Control: AI technologies enhance quality control by detecting defects and anomalies in real-time, ensuring higher product quality.

Auf Facebook teilen Share on Threads Auf LinkedIn teilen