Remote Maintenance  – GoDigital

Manufacturing companies utilize large number of machines at every stage of the production process. A failure in any of these machines or line of machines could cause shutdowns that cost thousands of dollar per hour in lost production and other cascading impacts. Keeping these valuable machines/equipment running depends upon the experience of the service technicians who have the responsibility to maintain, diagnose and fix problems, preferably before they fail. Today’s challenge is that these experienced service technicians are reducing due to ongoing retirement and lack of availability and skilled potential entrants to the service field. There is a need for digitizing the industrial maintenance and field service process.

The Remote Maintenance Solution enables manufacturers and machine/equipment builders to increase machine uptime by:

  • Collecting real-time data from  Machine Controls (PLC/CNC), SCADA and other sensors and smart devices
  • Analyzing the data from machine and using previous predictive analytics & knowledge-based systems to  identify current and upcoming problems
  • Enabling problem to be solved remotely with diagnostic information and access to the machine controls
  • Complementing the service technician skills in the field with AR to increase their productivity in diagnosing and fixing problems.

Connect to your machines

Machines/Lines are already equipped with sensors that monitor various parameters like flow, pressure, vibration, voltage, current, speed and many others. These are transmitted as data to the control systems like PLC/CNC where operating decisions are made. By connecting to these controllers and/or the sensors/devices, you get access to the various readings of these sensors.

Collect & aggregate data

The data from sensor readings and control system states are aggregated to perform some local analytics. This data is sent for further analysis and stored. Also a decision is made on the amount of information to be sent to the next level to reduce bandwidth consumption and overall latency.

Analyse data to detect problems

The aggregated data now can be converted into actionable information to be viewed in real-time and to diagnose problems faster than before. Predictive maintenance detects patterns in aggregated data collected from sensors and controllers from the machine and knowledge-based systems, and analyses this data to identify current and upcoming problems. Now you can predict when specific components might be nearing failure and alert the need for maintenance in an in-service equipment. Machine learning and other techniques provide insights into what goes on deep inside a complex machinery. This moves the maintenance from a time-based preventive maintenance approach to predictive when it is actually needed.

Alert and attempt to solve the problem remotely

As the predictive maintenance system detects an existing or impending problem on the machine, the same is alerted to a remote command centre or to the service technician at a  remote location. With information available  from the machine, the remote technician can diagnose the problem and may be able to address some or all of the possible causes remotely. For example technician may be able to recalibrate some devices to see if that fixes the problem.

Field maintenance

If the problem cannot be solved remotely, a field technician is deputed to the site along with all the information on the problem gained through the remote diagnosis. The field technician now has access to real-time machine data and remote diagnosis output. This allows him/her to be more prepared and take the special tools and spares required for the service call.

Augmented assist

Once the field technician arrives at the site, he/she can use the AR application on his/her smartphone or tablet to see machine readings and other diagnostic information, parts lists, repair instructions and other information superimposed on a view of the machine. As in-context access to this detailed information is possible, the problem can be solved even using a less experienced and lower cost field technician. When necessary the field service technician can call for more help from an expert to solve the problem.


  • Improved machine reliability
  • Improved availability
  • Improved maintainability
  • Improved performance
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