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Deep Learning

Deep Learning for Factory Automation

Deep learning technology is used in advanced manufacturing practices for quality inspection and other judgment-based uses. It combines artificial intelligence with machine vision.

Deep Learning Solutions:

What is Deep Learning?

Deep learning software teaches robots and machines to do what comes naturally to humans i.e. to learn by example. New, low-cost hardware has made it practical to deploy bio-inspired, multi-layered “deep” neural networks that mimic neuron networks in the human brain. Starting from a core logic developed during initial training (with human interaction), deep neural networks can improve performance as they are presented with new images, speech, and text after. This gives manufacturing technology amazing new abilities to recognize images, distinguish trends, and make intelligent predictions and decisions.

Deep Learning Software Solutions

Deep learning-based image analysis combines the specificity and flexibility of human visual inspection with the reliability, consistency, and speed of a computerized system. Deep learning models can precisely and repetitively solve difficult vision applications that would be too complicated to program and frequently impossible to maintain using traditional machine vision approaches. Deep learning models can distinguish unacceptable defects while tolerating natural variations in complex patterns. And they can be readily adapted to new examples without re-programming their core algorithms.

Deep learning-based software can now perform judgment-based applications more effectively than humans or traditional machine vision solutions:
Increasingly, leading manufacturers are turning to deep learning solutions and artificial intelligence to solve their most sophisticated automation challenges.

  • Part location
  • Inspection
  • Classification
  • Character recognition

New deep learning-based software helps machines recognize images, distinguish trends, and make intelligent predictions and decisions.

Deep Learning v Machine Vision Systems

Traditional machine vision systems perform reliably with consistent, well-manufactured parts. They operate via step-by-step filtering and rule-based algorithms that are more cost-effective than human inspection. But algorithms become challenging to program as exceptions and defect libraries grow.

Deep learning-based image analysis excels at:

  • Complex cosmetic inspection
  • Texture and material classification
  • Assembly verification
  • Deformed and variable feature location
  • Challenging OCR, including distorted print

Manufacturers are turning to deep learning solutions to solve their most sophisticated automation challenges.

Deep learning has turned applications that previously required vision expertise into engineering challenges solvable by non-vision experts. Deep learning transfers the logical burden from an application developer, who develops and scripts a rules-based algorithm, to an engineer training the system. It also opens a new range of possibilities to solve applications that have never been attempted without a human inspector. In this way, deep learning makes machine vision easier to work with, while expanding the limits of what a
computer and camera can accurately inspect.

Deep learning-based software optimized for factory automation now allows companies across many industries to create ground-breaking inspection systems that push the boundaries of machine vision and invite the future of industrial automation. These new inspection systems combine the specificity and flexibility of human visual inspection with the reliability, repeatability, and power of a computerized system.

This will make it possible to: ·

  • Automate previously unprogrammable applications·
  • Reduce error rates
  • Decrease downtime
  • Quicken inspections
  • Improve yields

Deep learning-based image analysis combines the specificity and flexibility of human inspection with the reliability and speed of a computer.

Implementing Deep Learning Solutions in Partnership with Fisher Smith

As with any technology there is a learning curve to its use and by utilising an experienced integration partner you can extract full value from this processing technique. There is also a considerable amount of involvement in correctly labelling and training images for deep learning and we have the skill, real world experience and cutting-edge hardware to best train and deploy a robust DL solution for your application. All hardware solutions run as edge inference, i.e. no data is exfiltrated to the cloud for processing, all decisions are made locally at production speeds making industrial deployments reliable, fast, secure, robust and scalable.

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