Industrial Automation Magazine India

AR, VR and digital twins are business-enabling technologies

Published on : Monday 07-06-2021

Jasbir Singh, Director, ECPR Technologies.

How has technology impacted maintenance practices in recent years?
Maintenance at many companies becomes purely reactive, which means they are fixing or replacing parts after they fail or start giving abnormal sound. The second most popular maintenance practice from the past is servicing the equipment on a routine schedule decided by OEMs whether service/replacement of parts is needed or unnecessary. Another maintenance practice becoming popular is condition based maintenance (CBM), which is developed by considering the equipment’s current degradation trend and forecasting the probable date of failure. Engineers get time to arrange spares and resources to take a planned stoppage for maintenance. Presently all the equipment/processes provide system and process alerts, audio visual alarms, and indicators for initiating attention for call of correction. When the alarm sounds, it’s sometimes late to prevent the stoppage. Alarms are popping up in the DCS system to alert the operator but these are often ignored as it causes disturbance to the operator. They change the upper or lower settings without consulting the engineers or keep the reset button pressed permanently to avoid the alarm sound. The number of alarm alerts (high/low)/settings are done as per process requirement during the engineering phase. Such configured alarms in the DCS system help operators during abnormality. But many times critical alarms go unnoticed due to high frequency of non-critical alarms and then major failure happens.
 
Often companies concentrate on operations rather than assets when it comes to maintenance. Is this the correct approach?
Process operations are under enormous stress for trouble free process running, maintaining productivity of the plant/unit or keeping customers happy. The Operation Manager consistently focuses on plant/machine operation/line running, availability of raw materials, chemicals, staff and machine health. They are concerned with bottlenecks if any to meet the customer requirements in time. They pay attention to improve manufacturing cycle times, by reducing turnaround time, and avoiding reworks in process or maintenance. The bigger challenge is to continuously improve the process and consider how well the newer challenges in the process can be addressed within the framework of operation. Some of the factors are as follows:
a. How to decide about the maintenance schedules considering the shop-floor reality and customer demand? 
b. How to train and conduct knowledge sharing with staff for smooth running of the process? 
c. How to avoid slippage in maintenance for smooth running of unit as per corporate strategy and objectives? 
d. How to plan production scheduling based on machine maintenance requirements?
 
How do emerging technologies like digital twins and AR/VR help remote troubleshooting?
Digital twins increase reliability of equipment and improve performance of production lines. It helps improve the overall equipment effectiveness or OEE by reduction of process downtime and improves overall performance which in turn increases productivity, reduces risk in all areas, and improves product availability and market reputation for the organisation. Most of the companies have pilot plants or laboratories for digital twin function. It largely helps in collection of data and analyses. Augmented reality (AR), virtual reality (VR) and digital twins are business-enabling technologies to visualise insights about machine, equipment or operational technologies. The ability to view virtual environments and compare them with the physical are a distinct tool for training in industries like manufacturing and energy, where machinery and other physical equipment can be discussed in offline training.
 
Maintenance-as-a-Service model is an emerging trend, but is this a sound strategy?
Operations often consider themselves as the customer of the maintenance department and maintenance is viewed as a service provider as a concept adopted in many organisations. They call it an internal customer. Operation is mainly responsible to deliver on production at lowest cost considering maintenance work stoppages, quality work delivery and quick response at time of failure or problem in machines. However this concept sometimes leads to differences when failures cannot be properly identified as it happened because of operation/process or equipment malfunction. It could go wrong with many other issues and that results in strained relationships, lack of trust due to poor communication and pointing fingers when some problems occur in the process/machine.
 
What should be the ideal maintenance practice for companies in process or discrete manufacturing industries?
The convergence of digital technology in industry is fuelling the development of a high level technology of predictive maintenance. Leveraging industry knowledge and technological development leads to providing information, when maintenance is to be done and what kind of maintenance is needed. Building the experience gained from asset management/diagnostic software, the computing algorithm behind the software is getting strengthened day by day. With the information thus available, the user can predict the life of critical devices and develop condition guidelines for future deterioration. Systematic storage and graphical display representation of the measurement help the process to streamline quickly. The system abnormalities, transient failure of process and device gets quickly highlighted on the operator screen without user intervention even along with the help window for corrective action if needed by the operator. These are data intelligence tools, which add value over data acquisition tools. These tools not only capture the data but manipulate, format and present in result form so that the user can take corrective action without the loss of time for analysis even in complex processes.

Jasbir Singh is an Automation Expert having long experience in Factory Automation, Line Automation, Implementation Strategist, Business Coach, Regular writer on automation, Artificial Intelligence, Robots/Cobots, Digital Technology, Network Communication, Industrial Internet of Things (IIoT), Wireless Communication, Block Chain and use of advance digital technologies. He has established a long association with Business Houses/large production houses to improve factory automation in their production lines as well as productivity improvement in factories in India and overseas; and in advising and designing the units to transform into digital platforms by use of Artificial Intelligence.