- Natural products sector

AI-supported quality assurance for wood, stone, tiles and ceramics - perfection for Natural and heterogeneous products.

Natural diversity inspires with its uniqueness. At the same time, they present manufacturers with particular challenges in terms of quality assurance, as inclusions, cracks, discoloration or glaze defects can impair the appearance and lead to rejects, rework or complaints. In addition, there are typical processing defects such as burn marks, grinding marks, polishing defects, chipping or uneven coatings, which reduce the value of a product.

Discovering AI in the timber industry

Artificial intelligence creates clear standards for unique products.

For the highest product quality, image processing and analysis is crucial to distinguish between natural deviations and real defects, ensure batch consistency and at the same time comply with complex standards and inspection procedures. This is exactly where our deep learning-based, AI-supported inspection software comes in. They enable objective, high-precision and reproducible surface inspection that works independently of subjective assessments. Intelligent algorithms are used to precisely check properties such as cracks, knotholes, discoloration, structural deviations or completeness. This allows defects in the machines to be reliably detected both during production through in-line inspection and in the end-of-line inspection.

The cloud platform is used to develop AI models individually and efficiently for each application. It is initially trained with known characteristics and can be continuously improved through interaction with employees. It adapts flexibly to new product types, applications and production conditions and standardizes quality decisions worldwide.

Images from industrial cameras are analyzed autonomously, on-premise and in real time with the trained models, error patterns are detected with the highest precision and products are objectively evaluated.

The advantages for manufacturers are obvious: fewer rejects and reworking reduce material and production costs, while consistent quality and a flawless appearance enable clear differentiation from the competition. Premium quality strengthens margins and at the same time increases customer confidence in the brand. Furthermore, processes become more efficient, error rates are reduced and the continuous analysis of image data provides valuable insights for proactive process optimization. Last but not least, manufacturers actively contribute to sustainability and the fulfillment of ESG requirements by reducing waste and energy consumption.

The possible applications are diverse: from solid wood, parquet, laminate, chipboard and painted materials to kitchen fronts, doors, windows, concrete slabs and tiles - the 36ZERO Vision KI can be used across all materials and is flexibly scalable.

With this technology, companies combine maximum precision in quality assurance with increased efficiency and sustainable added value - giving them a decisive competitive edge.

Typical error types for
natural and heterogeneous products:

1. natural and material-related defects

Color deviations:
Natural variations in the raw material (stone veins, tile firing).
Structural differences:
Uneven grain, veins or inclusions in the natural stone.
Inclusions & pores:
e.g. quartz inclusions in granite, porosity in limestone, resin pockets.
Cracks & fissures:
Drying cracks in wood, hairline cracks in stone or burnt tiles and concrete.
Discoloration / staining:
Fungal attack, oxidation (e.g. iron stains in the stone), natural mineral courses.

2. production and processing defects

Wood:
- Fire spots due to blunt tools or incorrect cutting speed.
- Runawaysplintering on edges and surfaces.
- Sanding stains / Sanding marks due to uneven grinding.
- Adhesive, glue or Paint stains. Uneven stain or lacquer absorption.
Natural stone:
- Polishing errors
- Cut marks of saw or water jet.
- Spalling / Edge chipping due to transportation or processing.
- Uneven joint patterns when laying.
- Surface burns due to incorrect cleaning agents (e.g. acid for limestone).
Tiles / ceramics / concrete:
- Error in the Wet and dry process (cracks, edge fractures)
- Glazing error (blisters, pinholes, dull spots).
- Burn marks / Color deviations due to uneven firing.
- Hairline cracks (Craquelé) in the glaze.
- Decoration error with printed tiles (offset patterns, blurring).

Challenges
for the Quality management

Natural material variability

Variations in color, structure, grain or veining are unavoidable

Visual error detection & assessment

Many types of defects are purely optical (color deviation, gloss differences, stains, glaze defects) and are assessed manually.

Batch and lot consistency

Deviations between production batches lead to complaints.

Fluctuating raw material quality & supply chain

Natural products depend on the extraction area, season, storage conditions and transportation.

Customer expectations vs. reality

Customers expect "perfect surfaces" with natural products that look "authentic" at the same time.

Standards & test methods

Automatic fault detection must implement complex sets of rules (DIN/EN standards).

break_edge_facet

A break can be seen on the beveled edge, which was caused by mechanical damage during the milling process.

color deviation

The plank surface shows a clear color deviation, caused by differences in the wood pattern or uneven surface treatment.

deformation_groove

The groove is deformed, which indicates incorrect tool guidance or excessive contact pressure during production.

Added value through
AI-supported quality assurance

Less waste & rework → Material and production costs are reduced as fewer parts need to be sorted out or reworked.
Greater competitive differentiation → Manufacturers can set themselves apart with a consistent, flawless look.
Better pricing & margins → Premium quality justifies higher sales prices and increases profitability.
Optimized processes & efficiency → Improved production control reduces error rates, saves energy, time and resources.
Higher customer satisfaction & brand image → Fewer complaints, a more positive image, confidence in consistent quality.
Sustainability and environmental benefits → Less waste and energy consumption thanks to fewer rejects → Strengthens sustainability profile and ESG balance sheet.

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KI - Applications for Wood, stone, tiles, ceramics

1 // Wide range of inspection methods:
Inspection of wood surfaces, crack detection, knothole detection, discoloration analysis, wood edge detection and completeness checks (sawmill, etc.)
2 // Cross-material applicability:
Automatic analysis of solid wood, parquet, laminate, chipboard, lacquered materials, kitchen fronts, doors, windows, concrete slabs and tiles.
3 // Automated error and deviation detection:
Artificial intelligence reliably identifies visual defects such as cracks, knotholes, flaking, stains or glazing defects.
4 // Objective quality assessment:
Reduction of subjective differences in visual inspection, consistent results across all production lines.
5 // In-line and end-of-line inspection:
Inspection during production (in-line) for immediate process correction, as well as end-of-line inspection before delivery.
6 // Ensuring batch consistency:
Monitoring of color and structure uniformity.
7 // Data-based process optimization:
Continuous evaluation of large volumes of image and production data provides insights into the causes of errors and enables proactive quality improvement.

AI solution for the timber industry

Digital transformation through AI in the timber industry.

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