Transmit capabilities in Pleora’s eBUS SDK simplify the design of a “digital twin” that virtually replicates an inspection line

Transmit capabilities in Pleora’s eBUS SDK simplify the design of a “digital twin” that virtually replicates an inspection line to help optimize performance.

Traditionally, an inspection line operator maintains a diagnostic labs with a stock of cameras used in the system. If an error is detected, the technician will attempt to reproduce the error in the lab. This approach adds significant costs, as production is often halted and a full suite of duplicate cameras must be purchased solely for diagnostics purposes. In addition, the error on the production floor is often difficult to reproduce in the lab environment.

In comparison, an inline “digital twin” can run in parallel with its real-machine counterpart to help diagnose issues. In this system, GigE Vision cameras are used for inspection. Alternatively, external frame grabbers can convert legacy cameras into GigE Vision devices. Pleora’s vDisplay receives GigE Vision data and outputs it in real time with low, consistent latency over an HDMI/DVI interface to displays for manufacturing line monitoring.

Digital twin factory inspection diagram

eBUS Tx is a software implementation that allows an operator to replicate any type of camera on the inspection line as an Industry 4.0 “digital twin” and view real-time video from the production floor or record a stream for further root cause analysis. Operators and technicians can select, monitor, and diagnose any of the inspection cameras without removing them or taking them offline.

Using eBUS Tx to replicate imaging data from the inspection line without impacting production, operators can evolve to more advanced digital twin systems that help improve performance and equipment lifecycle. For example, artificial intelligence and machine learning techniques can use the collected data to model future behavior for predicative maintenance. New algorithms to improve inspection can be developed and tested in the digital twin environment before being put into production.  Operators can be trained on a virtual machine until they have the skills and confidence needed to operate the real machine.

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