One of the hallmarks of Industry 4.0 is the ability of industry to predict the likelihood of future system failures and to optimize maintenance planning. For companies that manage a large number of complex systems, the achievement of Industry 4.0 gives them a strong head start, as predictive maintenance helps to achieve several goals: less downtime, higher productivity, improved safety and lower maintenance and replacement costs.
Smaller problems are always cheaper to fix than larger ones. With predictive maintenance, companies can improve asset reliability with condition-based maintenance, which is based on asset health insights from operational data and analyzes, as opposed to routine planning or reactive repairs.
Unfortunately, the complexity increases many times over for large organizations. A single factory, power distribution company, power plant, or oil refinery often have thousands of assets, from manufacturing equipment to safety equipment to the HVAC systems running through their facilities.
In today’s Industry 4.0 era, it is It is possible for sensors and cameras to monitor all of these assets, and with a strong digital hybrid cloud infrastructure, companies have access to any data or software they need anytime, anywhere. With the latest advanced analysis and machine learning capabilities, AI can assign holistic asset health assessments and even help determine the likelihood of failures and failures.
An example of this is the India Grid Trust (IndiGrid), India Leading infrastructure investment fund with currently 14 operating projects, consisting of 40 EHV overhead lines with a total line length of approx. 7,570 km, 11 substations and 100 MW (AC) of solar generation capacity in 18 states and 1 Union territory. The company uses an AI-enabled asset management platform to monitor and manage & and efficiently maintain these multi-component assets. IndiGrid also uses AI for large-scale detection of anomalies – and thus proactively prevents their failure and increases availability.
In order to achieve Industry 4.0, it is therefore important that the knowledge gained from operating data is applied almost in real time to develop their full value. And it can do this by making predictive maintenance accessible to field workers.
After all, it’s the on-site technicians that businesses and consumers rely on to repair defective parts and keep plants, factories and refineries running smoothly and keep the lights on.
As assets become more complex and sophisticated, technicians always need instant access to all relevant updated information and insights from &. In other words: Predictive maintenance has to be mobile.
Smartphones are now ubiquitous among Indian workers, especially in industry. Since AI offers a huge advantage with data-driven insights for predictive maintenance, mobile technology makes preventive maintenance more feasible in real time. Maintenance work on a complex facility in the field will be much faster and more efficient, as less time will be spent looking for repairs. With Industry 4.0, AI-based insights can be made available offline, and companies can give technicians access to operational data, planning optimization, system condition assessments and even guided repairs.
With the constant development of AI and hybrid cloud, applications on mobile devices are becoming more and more accessible Devices made available. Now a technician can take a photo of an asset and the AI will identify and comment on the likely errors. AI can tap into the company’s operational data and analyze any similar parts with breaks and help the technician figure out the likely problem.
Virtual assistants can walk them through repairs and walk them step-by-step through the tasks, and augmented reality can be used to connect technicians with experts to guide them through the right solution the first time. Technicians can even access a “digital twin” of an asset on the mobile devices to investigate its advantages and disadvantages. The upcoming 5G network in India will improve connectivity and make preventive maintenance technologies faster and more widespread.
In summary, companies can make predictive maintenance more effective by making AI-powered insights available to field workers. This will make it easier to manage the health of all assets, resulting in a more resilient, profitable, and sustainable organization – all of these are the tell-tale signs of a successful Industry 4.0 adoption.
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Express Computer is one of India’s most respected IT media brands and has been published for 24 years in a row. We cover enterprise technology in all its facets, including processors, memory, networks, wireless, business applications, cloud computing, analytics, green initiatives and anything that can help companies get the most from their ICT investments. We also report on the rapidly evolving e-governance area in India.
We are going through a radical change with our 4.0 outlook: Kishan Sundar, Maveric …
Express Computer is one of India’s most respected IT media brands and has been published for 24 years in a row. We cover enterprise technology in all its facets, including processors, memory, networks, wireless, business applications, cloud computing, analytics, green initiatives and anything that can help companies get the most from their ICT investments. In addition, we also report on the rapidly developing e-governance area in India.