Quality assurance through precise predictions

About Pfleiderer Gruppe

The Pfleiderer Group is a leading manufacturer of engineered wood in Europe with its headquarters in Neumarkt in der Oberpfalz. Since its foundation, the Group has focused on the sustainable production and recycling of materials. With nine production sites in Germany and Poland and sales offices in several European countries, the Pfleiderer Group is known for its high-quality engineered wood panels, which are used in furniture, kitchens and laminate.

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The Challenge

The Pfleiderer Group was faced with the challenge of making the production process for wood-based panels more sustainable. In particular, the aim was to improve the quality of the decorative wood panels, which was burdened by a high number of unexplained quality problems. The subjective nature of visual inspections and the difficulty of modelling qualitative data made it considerably more difficult to optimize the production process.

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The Solution

Kineo responded to the Pfleiderer Group's challenges by deploying its expert team of machine learning scientists. They worked closely with the internal team to solve the data problem and gain clear insights. Through intensive analysis, they identified press time as a key indicator of product quality. A customized machine learning algorithm was developed to predict the pressing time and minimize the error rate in the production process.

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The Impact

The implementation of the machine learning model led to significant improvements in the predictability of pressing times. These findings not only offer potential for further optimization in decor board production, but also lay the foundation for future projects to increase efficiency and quality assurance at Pfleiderer. The cooperation with Kineo was particularly appreciated by the Pfleiderer Group for its transparent working methods and its confidence in technical and organizational solutions.

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AI for the optimization of production processes

The application of artificial intelligence and machine learning has shown that it can not only improve product quality, but also promote sustainable production processes. Through precise predictions and targeted optimizations, AI helps companies like the Pfleiderer Group to produce more efficiently and conserve resources, leading to increased customer satisfaction and an improved market position in the long term.