By Rohit Pande, AI Applications Sales Leader, IBM India/South Asia
One of the hallmarks of Industry 4.0 is the ability for industries to predict the likelihood of future failures of assets and optimize maintenance planning. For businesses that manage vast number of complex assets, achieving Industry 4.0 grants them a powerful edge as predictive maintenance helps achieve multiple objectives: reduced downtime, greater productivity, enhanced safety and lower costs of maintenance and replacement.
Minor issues always cost less to rectify than major ones. Through predictive maintenance, organizations can improve asset reliability with condition-based maintenance based on asset health insights from operational data and analytics, as opposed to routine scheduling or reactive repairs.
For large organizations, unfortunately, the complexities increase multifold. A single factory, energy distribution company, power plant or oil refinery often have thousands of assets, from production equipment to safety equipment to the HVAC systems that run through their facilities.
In today’s time with Industry 4.0, it is possible for sensors and cameras to monitor all those assets, and with a strong hybrid cloud digital infrastructure, organizations have access to all necessary data or software, whenever and wherever they need. With the current advanced analytics and machine learning capabilities, AI can assign holistic asset health scores and even help determine the likelihood of breakdowns and outages.
As an example, India Grid Trust (IndiGrid), India’s leading infrastructure investment trust, which currently has 14 operating projects, consisting of 40 EHV overhead power transmission lines with a total circuit length of approximately 7,570 kms, 11 substations and 100 MW (AC) of solar generation capacity, across 18 states and 1 union territory. The company has been leveraging an AI-enabled asset management platform to monitor, manage & maintain these multi-component assets efficiently. IndiGrid has also been leveraging AI for detecting anomalies at scale – thus proactively preventing their breakdown and boosting availability.
To achieve Industry 4.0, it is thus important for the insights that are derived from operational data to be applied in near real-time, to leverage their full value. And this is possible by making predictive maintenance available to the field workforce, in an accessible manner.
After all, it is the on-ground technicians that organizations and consumers rely on to fix broken parts, to keep plants, factories and refineries running smoothly, to keep the lights on.
As assets become more complex and more sophisticated, technicians will always require instant access to all relevant & updated information and insights. In other words, it is necessary for predictive maintenance to be mobile.
Making predictive maintenance on the go
Smartphones have now become ubiquitous among Indian workforce, especially in the industrial sector. With AI offering a huge advantage with data driven insights for predictive maintenance, mobile technology makes preventive maintenance more actionable, in real time. Maintenance work of a complex asset in the field will be much faster and efficient since there will less time spent traveling back and forth researching repairs. With Industry 4.0, AI-enabled insights can be made available offline, and organizations can make it possible for technicians to access operational data, scheduling optimization, asset health scores and even guided repairs.
With constant advancements in AI and hybrid cloud, there are more accessible applications being made available on mobile devices. Now, a technician can take a photo of an asset, and AI will identify and annotate the likely faults. AI can tap into the organization’s operational data and analyze all the similar parts that had breakages and help the technician figure out what the likely problem is.
Virtual assistants can guide them through repairs and take them through tasks step-by-step, and augmented reality can be used to connect technicians with experts to walk them through the right fix, the first time. Technicians can even have access to a ‘digital twin’ of an asset on the mobile devices to study its ins and outs. The soon to launch 5G network in India will boost connectivity and make preventive maintenance technology faster and more prevalent.
To sum it up, by making AI-driven insights accessible for the field workforce, organizations can make predictive maintenance more effective. This will make it easier to manage the health of all of assets, leading to a more resilient, profitable and sustainable organization – all of which are the telltale signs of successful Industry 4.0 adoption.