The Internet of Things (IoT) has transformed the processes in the manufacturing sector by offering automation, more efficient operations while helping companies build valuable new business models. While the benefits of digital technologies are immense, it is in the area of predictive maintenance that manufacturers can derive a significant impact. In communication with Praveen Arora, Vice President – IoT, Tata Communications
Tell us how you are using IoT and other technology to eliminate unplanned downtime through having predictive maintenance?
Tata Communications India IoT solutions enable real time asset tracking, data driven demand forecasting, reduce human intervention and improve operational efficiency. Further, our solutions enable connected devices to operate with low battery consumption and minimal infrastructural setup due to LoRaWAN® technology. These solutions can also be easily integrated to any existing industrial environments and help enterprises grade devices that can withstand harsh industrial environments.
What are the latest trends in the predictive maintenance areas that shop floors are using?
According to McKinsey & Company, AI-based predictive maintenance can boost availability by up to 20% while reducing inspection costs by 25% and annual maintenance fees by up to 10%.
There is an increase in the importance of digitising supply chains as enterprises are realising the dynamics of industry 4.0. Today shop floors are going through a complete make over and more so a digital one where they are looking at new age technologies to scale their business. Predictive maintenance has a huge range of use cases across industries like oil and gas, manufacturing, aircraft maintenance and more.
Some trends to note:
- One of the key trends noticed in shop floor automation is Digital Twin, which is the virtual representation of the lifecycle of an object and is majorly used to streamline factory operations. It helps in understanding the condition of the asset and enables data driven decision making process.
- Whereas, in Remote assessments, the machine’s status is broadcasted live to the support agent and the machine can be assessed remotely. This proved beneficial mainly during the ‘social distancing norm’ and the lockdown period
- Asset tracking is another trend which helps manufacturers by providing alerts of unauthorized movement, remote monitoring of inventory and even real time tracking in the event of a possible theft.
- Artificial Intelligence will play a significant role in enhancing human capabilities and skills and thereby increase efficiencies. Artificial intelligence will continue to do what it does best – interpret data via advanced algorithms and in a much shorter time
- The rise of the smart factory is helping enterprises achieve a complete connected network inside and outside the organisation.
- Thermography Techniques is also picking up momentum, as it is enabling the better and easier maintenance of equipment. For e.g. it can sense ‘heat’ as an indicator to predict faults. This enhances worker’s safety in a way and also reliability of the equipment.
How smooth integration of the latest digital technologies can be achieved for predictive maintenance?
Digital technologies are helping us reimagine the manufacturing sector. They are creating cost efficient, quicker, and secured systems, and enhancing the overall customer experience. Internet of Things (ΙοΤ), Machine Learning and cloud computing have enabled the processing of massive volumes of tracking data. Data collected through IoT enabled devices power a predictive analytic engine, which can forecast faults, schedule preventive maintenance, and suggest options in case of a breakdown. For example, Thermographic technology uses ‘heat’ as an indicator to predict early faults in an equipment using machine learning. Furthermore, smart wearables like smart glasses are leveraging AR technologies by enhancing a technician’s view. This is done by superimposing digital data and images on the physical world allowing the worker to better understand the fault, minimising human error.
Hence, it is essential for manufacturers to select solution providers that are aligned with their vision of smart manufacturing. Tata Communications is well positioned to provide an automation-intensive environment, using a combination of mobile connectivity with cloud integration, supported by the internet of things.
What are the things to keep in mind or challenges manufacturers face while integrating IoT and other technology for the purpose of predictive maintenance?
The pandemic brought to light the gaps in logistics management as not many enterprises focused on digitizing their supply chain. Thus, building resilient supply chains by integrating IoT and Big Data to achieve predictive maintenance, became the key area of focus.One of the major challenges manufacturers faced was siloed data. The absence of protocols for interoperating with connected devices across IoT platforms is a significant obstacle encountered by manufacturers who want to implement IoT in their processes. Additionally, the massive data generated by IoT devices make organisations prone to cyber threats. IoT solution providers also need to comply with security standards to minimise privacy risks. This combined with the high cost of adoption of IoT makes its implementation a challenge in the manufacturing industry.