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Partner Presentation: paiqo GmbH

Artificial Intelligence (AI) can be used to minimize production downtime, reduce waste and accelerate and automate decisions within the company. paiqo is our reliable and competent partner for big data architectures in conjunction with AI algorithms.

The company offers customized solutions for the design and implementation of cloud-based data platforms in conjunction with state-of-the-art AI algorithms. From anomaly detection, predictive quality and predictive maintenance to AI assistance systems, paiqo supports companies on their way to efficient and future-proof production.

BI tools and data analysis are used to analyze past scenarios in order to identify sources of error and implement future improvements. In combination with artificial intelligence, predictive analytics makes it possible to avoid errors before they happen. To do this, it is necessary to use software such as FASTEC 4 PRO to record data and collect it over a longer period of time. Based on historical data, it is possible to make predictions about future events that can be traced back to certain constellations of parameters (e.g. machine settings in production). 

An Example from Practice

Classification of Bündnerfleisch with AI

Bündnerfleisch is a specialty made from beef from the Swiss canton of Graubünden. This high-priced product is subject to strict quality criteria, which must be checked during the production packaging process. In the example company, this inspection was carried out manually for a long time. One employee walked up and down the line and only had a fragmented view of the packaging process due to time constraints. This led to a product recall because products of inferior quality (too much fat in Bündnerfleisch) were put into circulation.

The products produced are assigned quality criteria from quality A to D. For exclusive customers with a high-priced range, only quality A and B are sold; C and D are sorted out and processed into other products, such as salami, and sold at a lower price.

The manual allocation of quality criteria is very time-consuming and error-prone. This is the ideal opportunity for a process change using an AI solution. This is implemented using a camera that scans the product. The AI decides which pack receives which quality criterion. This required around 200 images, which were initially assigned to the quality criteria in order to train the AI. Based on this, AI models can be retrained to imitate human behavior with 98% certainty. 

What We Appreciate About Our Partner paiqo

The hands-on mentality is very important at paiqo. The company is able to map numerous scenarios with AI support, works in close partnership with customers and also derives particular benefit from the data we collect in FASTEC 4 PRO.

After all, it is necessary to collect and report data throughout the entire production process in order to ensure the quality of products and detect errors at an early stage.

Non-aggregated process and quality data recorded in FASTEC 4 PRO is collected in the cloud via the IoT connector and is then available to AI applications as historical data. The data can also be made available to additional applications for machine-to-machine communication via an MQTT broker. For example, the AI learns that more rejects were produced in the past with specific process parameters and can then issue real-time warnings if certain processes are more prone to errors. This results in significant cost savings and therefore sustainable production.

A solid foundation of digitally recorded production data is a prerequisite for future AI projects. Real-time data from production can be used via the IoT or BI connector in BI applications, for example for live monitoring.

We support you on this path with our FASTEC 4 PRO software solution! Our partner paiqo offers the right advice on big data architectures and AI algorithms. So you are well prepared for the future.

Learn More:

Author: Linda Bauer

Team Lead Marketing
Experience in B2B communication and target group-specific copywriting in print and online since 2019.

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