Industry 4.0 promises a lot – efficient production through connected machines, data-driven insights, and better machine availability via predictive maintenance
These capabilities are no longer desirable, but business critical. In today’s manufacturing industry, where efficiency is top priority and unplanned downtime can quickly hit the bottom line, smart technologies are basic requirements.
In fact, a report by Deloitte shows that downtime is costing manufacturers around $50 billion every year. If manufacturers are going to evolve and recoup after 18 months of turbulence, they need to embrace digital transformation, digital solutions and predictive maintenance. Whether it’s Artificial Intelligence (AI), Augmented Reality (AR) or Internet of Things (IoT) – they each have an essential role in keeping equipment running reliably, identifying faults at an early stage, and solving problems quickly regardless of location. The future of manufacturing is digital, so it’s time for businesses to step up.
Predictive maintenance with IoT and AI
In day-to-day activities, manufacturing sites generate data during operations that provide a comprehensive picture of its condition, for example based on vibration patterns, temperature development or noise levels.
The collection of this data via an IoT network and its analysis enables manufacturers to implement predictive maintenance. This means manufacturers can detect faults at an early stage before they lead to damage or machine failures. Often, easily prevented faults can snowball into larger issues, sometimes even shutting down the manufacturing line.
However, since the amount of data that needs to be analysed is enormous, AI is crucial to gaining helpful and actionable insights. AI will assess and benchmark the normal state of a machine and the optimum characteristics of all parameters. If the sensors on the machine detect deviations, for instance a sudden rise in temperature, this is registered by the system. The solution can then use this information to predict and pre-empt upcoming scenarios, saving the business time, money and useful resource.
This is not just a one scenario fits all tool, predictive maintenance has huge potential to revolutionise and streamline the way manufacturers and their teams operate.
Predictive maintenance in action
One such example can be seen when a temperature rise is detected at a machine, the system checks whether it returns to normal within a certain period, if so, the incident is documented. If the temperature does not drop, the AI triggers the first escalation step: an employee receiving a message about the incident via the IoT system. However, as the AI will continue to monitor the situation, they do not have to act yet.
If the temperature remains high or even continues to rise, the next escalation step comes into effect: the system automatically increases the cooling capacity and checks whether this brings the temperature back to normal. The employee then receives another notification about this.
In the event the problem isn’t solved, the AI alerts the employee that action is required. The employee can now access the system remotely using an IoT connection, either from their office or from another location. The AI would then be able to provide the relevant data, such as error code and machine type required to make a quick diagnosis. If it is a software problem, the machine can be configured directly from a distance. However, if it’s a hardware issue, employees also receive digital help – through AR. Thus, allowing manufacturing sites to effectively identify and address problems before they escalate, saving time, money and ensuring a smooth-running production line.
Smart maintenance with wearables and AR
Most of the time, it is only small manual operations that can prevent major failures, be it refilling coolant, replacing bearings, or changing moving parts. Such maintenance procedures are provided as step-by-step instructions, also called workflows, to service technicians directly on a wearable device, such as smart glasses, via AR. The AR elements are superimposed on the technician’s field of view as they work on the equipment, so they can see the steps in front of them but have both hands free to perform the maintenance tasks. To ensure quality management and auditability, all hand actions can be documented via a built-in camera in the goggles.
If assistance from an external expert is needed to fix a problem, AR helps here as well. Equipped with smart glasses or a smartphone running the AR application, technicians on site and the expert from a distance take a joint look at the situation. Through the camera of the end device, the same image is transmitted to both parties. Instead of relying on verbal directional instructions, as would be necessary in a phone call, visual markers can be placed here to stick to their position.
This ensures clear communication and means that expert knowledge doesn’t have to be limited to within one company. AR opens up new opportunities for machine builders to support their customers, offering a more streamlined service experience, and new business potential at the same time.
The future of manufacturing
As the world moves towards digital, the manufacturing industry needs to adapt with it. Technologies such as AI, AR and IoT are essential to keep modern production lines running through predictive maintenance, and pre-empting issues before they become detrimental to the supply chain. In a highly competitive business world, companies simply cannot afford to lose precious time to manufacturing issues or allow small defects to spiral into a closure of a production line. The future of efficient and profitable manufacturing now lies in digital and businesses truly embracing the technologically driven insights of predictive maintenance.
About the Author
Dr. Hendrik Witt is Chief Product Officer at TeamViewer. As a global technology company and leading provider of a connectivity platform, TeamViewer makes it possible to remotely access, control, manage, monitor and repair devices of all kinds – from laptops and mobile phones to industrial machines and robots. In addition to the high number of private users for whom the software is offered free of charge, TeamViewer has more than 550,000 paying customers and helps companies of all sizes and from all industries to digitize business-critical processes by seamlessly networking devices.