Use cognitive automation for your manufacturing processes and quality assurance.

AI Transformation in Manufacturing

Today, manufacturing companies face the challenge of continuously reducing costs and increasing efficiency while delivering high product quality in the long term. Leading manufacturers are taking a proactive approach to streamline their operations by using AI. Companies that make extensive use of AI-based image processing benefit from improved efficiency, less downtime, higher quality and thus higher customer satisfaction.

Our customers use AI-based image processing to reliably detect error patterns in production, to automate processes or to handle complex tasks between man and machine. Data Spree is empowering leading manufacturing companies to deploy AI-based computer vision solutions that are changing the industry.

Continuously Optimizing Quality

The challenge of production is to ensure a consistently high standard of quality while maintaining high cycle times. To continuously meet high quality requirements, especially in mass production, is always associated with effort and high costs. AI-based image processing, on the other hand, uses anomaly detection to differentiate parts with defects or deviations from good parts quickly and without much training. But also the classification of different defect types and variants is quickly very reliable by means of the corresponding training using production data. AI trainings driven by production data thus quickly achieve accuracies and qualities in the long term that conventional systems fail to achieve. Artificial intelligence thus also offers the possibility to continuously improve quality via the flow of production data or to react to new products or product changes quickly and without new development or integration efforts.

Key Applications
  • Quality Control
  • Surface Inspection
  • Defect recording and classification
  • Continuous quality optimization

Control Production with Many Variants

Product diversity requires flexibility in production in order to be able to react to a large number of variants and product changes. AI-based image processing can help to keep high variability under control and to automatically secure production and downstream logistics processes. Varying products can be classified in real time on the basis of AI, and can be assigned and controlled accordingly in ongoing production. The AI training for this is easily done using the current production data, which quickly ensures reliable classification of product variants. In the case of new product variants or product changes, the existing AI solution can be quickly and easily retrained, allowing you to react flexibly to changes. AI-based solutions therefore do not require any additional development, integration or hardware, but simply require a further "feeding" of data.

Key Applications
  • Classify product and manufacturing variants
  • React quickly and flexibly to production changes
  • Reliably detect and classify naturally grown crops or raw materials
  • Determine variable filling levels and placement correctly

Automate Complex Production Processes without Errors

Production processes rarely run optimally. Especially in production lines with automated and manual sections, errors, delays or avoidable malfunctions occur time and again. With AI-based image processing, critical production steps and inspection points can be reliably monitored during ongoing production. For example, the correct position of production carriers, or the correct number, placement and orientation of production equipment can be monitored in real time using object detection with appropriate AI training. Deviations in the production processes or manual interventions by employees can be taken into account and reacted to accordingly. Conventional vision systems reach their limits at this point at the latest and often lead to unnecessary production stops. With intelligent AI-based systems you can correctly detect any complex situation and react appropriately.

Key Applications
  • Object orientation
  • Pick and place tasks
  • Chaotic sorting
  • Positioning
  • Recognition of employees or manual intervention
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