AI solutions for manufacturing

We build AI-powered solutions to address a range of industrial challenges

Up to 30%

cost savings thanks to automated and consistent defect detection

Up to 10%

production volume increase and maintenance costs reduction

INCREASED 

Safety standards by applying perceptive scene analysis

Use cases

Predictive maintenancePredictive maintenance

Preventing failure and equipment downtime before it happens, using predictive modelling

  • Forecast potential failures & optimal repair planning
  • Ensure fewer breakdowns
  • Optimize repair timing, minimizing idle time and total repair costs

Workflow optimizationWorkflow optimization

Leveraging digital tools to improve your facility’s operations

  • Digitize factory plans to shorten facility modernization timeline and smoothen workflow changes
  • 3D modelling and Augmented Reality (AR) solutions

Worksite safetyWorksite safety

AI-driven solution to increase worksite safety

  • Automatically identify and authorize employees
  • Monitor usage of personal protective equipment
  • Automatically identify violations of safety regulations and send real-time alerts

Workflow optimizationQuality control

Computer vision based, intelligent quality control solution

  • Detect incorrect labels, shapes, items orientation or contamination
  • Identify products surface defects, topping/sauce cover defects as well as products spills
  • Monitor moisture presence and correct arrangement of products

Let’s connect!

Are you curious if your business challenge can be tackled with AI?
Contact us and we’ll give you a free assessment and a quotation

Contact us!

Case study

Defect detection in tyre manufacturing

Project challenge:

Quality control in a manufacturing setting can be a difficult challange. There is a set of problems, where out-of-the-box solutions can help, however there is also an abundance of challenges, where bespoke models are required.

We solved such a complex quality control problem for a global tyre manufacturer. We created a solution for real-time detection of multiple defects in images of tyres (molding, cord spacing, air bubbles, external particles, stains) within the production process.

We applied and developed multiple neural networks (CNN, defect segmentation, anomaly detection, image enhancing) machine learning architecture optimized for quality of the prediction and minimal processing time.

As a result, we reduced human QA cost by over 80% while improving the detection rate of several complex defects. Additionally, our solution enables precise assessment of defect type, severity and location – even in cases barely detectable by a human expert.

About company:

  • One of the world’s largest tyre manufacturer
  • EUR 20+B revenue
  • Wide product portfolio
  • Several factories across the globe

Success stories

Autonomous vehicles

Volkswagen Generated over 100 years of simulated driving experience for vehicle training Learn more

#automotive#reinforcementlearning

Predictive maintenance

Global medical device manufacturer Downtime reduced by over 15% Learn more

#healthcare #predictivemodeling

Digitizing industry installation documentation

A global leader in digital solutions 90% workflow time reduction Learn more

#manufacturing#computervision

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Contact us

Locations
  • deepsense.ai, Inc.
  • 2100 Geng Road, Suite 210
  • Palo Alto, CA 94303
  • United States of America
  • deepsense.ai Sp. z o.o.
  • al. Jerozolimskie 44
  • 00-024 Warsaw
  • Poland
  • ul. Łęczycka 59
  • 85-737 Bydgoszcz
  • Poland
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