Digital twin

We have developed a digital twin model capable of pairing virtual and real equipment, including sensor readings.

The most significant features are as follows:

  • Fully integrated on a virtual reality (VR) environment.
  • Integration of as-built 3D models of equipment from different CAD packages, together with point cloud scan data on a seamless environment.
  • Integration of real time data from live SCADA systems or data sets enabling the presentation of real-time status and operating condition, including alarms.
  • Integration and visualization of SQL databases of equipment, including equipment and part datasheets, maintenance logs, etc.
  • Capable of connecting remotely with users, allowing for remote design reviews and/or remote collaboration thorough the life cycle of the equipment or installation.
Sensor readings

Automatic defect detection system

Undergoing development of an automatic defect detection system in manufactured parts, using convolutional neural networks to detect features in an image while simultaneously generating a high-quality segmentation mask for each instance.

Common defects include cavities, pores, lack of penetration, and other type of volumetric defects frequently found in castings and welded parts.

Early detection of these defects can allow faulty products to be identified early in the manufacturing process, resulting in improvements in quality, as well as time and cost savings.

The defect detection system is trained and tested on publicly available X-ray dataset and is currently at an early development stage.

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Visit to Glasgow

We are priviledged to be visiting Glasgow this week following up on a project to retrofit an exhaust gas cleaning system onboard a SuezMax class oil tanker.

We thank our client and friends for their continuous consideration and support during our stay.

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