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How you as a manufacturing company with over 50 employees can reduce your production costs through AI-based quality management from snap

Two-thirds of German companies see artificial intelligence (AI) as the most important future technology, and 64% expect it to increase productivity.

Reasons for excessive production costs in your company
abandonment of automated quality management
The Hidden Costs of Inaccuracy
partial automation and manual costs

Many companies rely on manual quality control rather than automation. However, this method can be time-consuming and error-prone, leading to increased scrap and rework. The lack of precision in automated systems increases production costs and puts product quality at risk.

High production costs are caused, among other things, by insufficient accuracy in quality management. If quality standards are not precisely maintained, this can lead to failures that affect product quality and cause additional costs.

Even partially automated systems can incur high costs due to staff absences and high staff turnover. Partial automation reduces manual tasks, but still requires human intervention. Staff shortages and frequent changes can affect efficiency and lead to additional costs.

How you can sustainably reduce production costs in your manufacturing step by step:

1

Initial consultation to determine your needs and analyze your cost-saving potential

2

On-site inspection of your production and analysis

3

Implementation of our complete system in your production

4

Earlier detection of errors, optimization of production, increase efficiency, costs and resources

5

Continuous support of your processes through our software and hardware

Download

Download our snap Vision brochure here!

How ATLAS improves its production quality with snap

Introduction : ATLAS was faced with the challenge of making quality control more efficient and precise. With snap, ATLAS was able to ensure that each shoe met its high standards while optimizing production processes.

Solution : With snap, ATLAS can successfully distinguish between faulty and faultless products. Defects are now precisely identified and further processing of faulty components is prevented. Our system increases the level of automation and ensures consistently high product quality.

areas of application
camera
surface inspection
Abstract Image
completeness check
Abstract Image
positioning errors
Abstract Image
OCR text recognition
robot arms
Pick and Place
development team
Mavin Heim
Mavin Heim

Chief Technical Officer

Mahdie Karbasi
Dr. Mahdie Karbasi

Head of Computer Vision

Kai Tybussek
Kai Tybussek

Head of Hardware

Moritz Mohr
Moritz Mohr

Software Development

Nour Saoud
Nour Saoud

Software Development

Bianca Suermann
Bianca Suermann

Development Assistant

references
ATLAS
A+B Electronic
SIEGENIA
DIMATE
IMS
Hettich

contact

Find out more about the savings potential in your production.

Sinah Dittmann

Danke für Ihre Nachricht!

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