Become one of many major companies all making significant investments in machine learning-powered approaches to improve all aspects of their manufacturing. Empower technology that is being used to bring down labour costs, reduce product defects, shorten unplanned downtimes, improve transition times, and increase production speed, with the ease of advanced computing. For years, automation, robotics, and complex analytics have all been used by the manufacturing industry. Now you can too.

For decades, entire businesses and academic fields have existed for looking at data in manufacturing to find ways to reduce waste and improve efficiency. Working with Novatech, our experienced team of engineers and architects' can quickly help and guide you through the process of understanding the implementation of Deep Learning platforms within your organisation.

Current and future uses and benefits.

Today, Deep Learning is an established technology that is being employed in a number of areas:

  • Deep Learning for Manufacturing, current and future uses of Surface defect inspection:

    Smart sensor technology for identifying defects

  • Deep Learning for Manufacturing, current and future uses of Internal defect detection:

    Using X-rays, Magnetic particle testing, Ultrasonic, Electromagnetic, Laser testing, Leak testing, can highlight potential weak points in the manufacturing process of critical conponents

  • Deep Learning for Manufacturing, current and future uses of Visual analytics for safety:

    visual analytics as an enabler for manufacturing process decision making

  • Deep Learning for Manufacturing, current and future uses of Predictive maintenance:

    Taking data points from multiple sources combining it with AI based platforms to predict failures before they happen.

  • Deep Learning for Manufacturing, current and future uses of Autonomous production lines:

    Intelligent systems that can replace, augment of compliment your existing human workforce.

  • Deep Learning for Manufacturing, current and future uses of Autonomous production:

    Robotics and autonomous systems (RAS) using hardware, software, sensors and communication technology.

  • Deep Learning for Manufacturing, current and future uses of Root cause analysis:

    Automated root cause analysis.

  • Deep Learning for Manufacturing, current and future uses of Process monitoring:

    Virtual sensors, and non linear model based monitoring (e.g. Neural Nets) and anomaly detection in high dimensional data points.