Industrial Automation Magazine India

The link between predictive maintenance solutions and sustainability is profound

Published on : Tuesday 05-09-2023

Prashant Verma, Co-Founder & Country Head, Nanoprecise Sci Corp.

Can you explain the role of predictive maintenance solutions in industries today?
Predictive maintenance is transforming the way maintenance activities are conducted. They are turning traditional maintenance practices into proactive, data-driven strategies that leverage advanced technologies such as IoT, AI, and machine learning. The primary goal of predictive maintenance is to optimise asset performance, minimise downtime, and maximise the overall efficiency of industrial processes.

In manufacturing industries, traditional maintenance approaches have relied on scheduled maintenance or reactive measures, leading to potential disruptions, costly repairs, and inefficient use of resources. Predictive maintenance shifts this paradigm by predicting when equipment failures are likely to occur based on the real-time information about its health and performance. This predictive capability empowers manufacturers to take preventive actionsat the most opportune times, and avoid unexpected breakdowns, thereby significantly enhancing their operational efficiency. Additionally, industries can reduce their environmental footprint by optimising energy consumption, while minimising equipment failures. Fewer breakdowns lead to less waste generation and optimised energy usage aligns with energy efficiency goals, contributing to a more environmentally responsible approach.

How has the technology surrounding predictive maintenance evolved in recent years, and what advantages does it offer to industries?
The evolution of predictive maintenance in recent years has brought transformative advantages to industries. The convergence of advancements in IoT sensors, cloud computing, edge computing, data analytics, and machine learning have collectively propelled predictive maintenance to new heights.

In the past, maintenance practices were reactive, relying on fixed schedules or equipment failure. However, with IoT sensors, operators can now collect real-time information about the health and performance of their equipment. This continuous stream of information forms the foundation of predictive maintenance, allowing them to monitor equipment health in real-time, and detects even subtle anomalies. Moreover, cloud computing has revolutionised data management and analysis, allowing for the aggregation and storage of vast amounts of data securely. This results in predictive capabilities providing insights into equipment health, performance trends, and potential failure scenarios.

Could you provide examples of how your company leverages data analysis to optimise maintenance practices and improve asset efficiency?
At Nanoprecise, we employ advanced 6-in-1 wireless sensors to gather real-time data on machine health, including parameters like temperature, vibration, and acoustic emissions among others. Our AI-based Energy Efficiency and Health Analytics Platform utilises patented signal processing algorithms to spot early signs of potential failures. Highlights include: automated prediction and prescription; tracking energy consumption to reduce CO2 emissions; physics + AI; and wireless and non-intrusive system.

The system establishes performance thresholds for industrial assets, triggering automated alerts when certain parameters exceed them. For instance, in a cement plant, if the vibration levels of a critical motor start to deviate from the expected range, our system immediately triggers an alert. Maintenance teams receive this alert, enabling them to take proactive measures before a potential failure occurs. This minimises unnecessary maintenance tasks while ensuring timely interventions. We also usea data-driven approach to monitor energy consumption patterns of industrial assets, helping maintenance teams mitigate any inefficiencies in their energy consumption. Our solutions translate data into actionable insights, empowering industries to achieve higher levels of operational excellence.

In your opinion, what is the connection between predictive maintenance solutions and sustainability?
The link between predictive maintenance solutions and sustainability is profound. At Nanoprecise, we understand the pivotal role predictive maintenance plays in advancing sustainability goals across various industries. We assist global manufacturers in optimising operations through predictive maintenance technology.

Predictive maintenance delivers a multi-faceted impact, ranging from improved resource management to higher operational efficiency. By detecting equipment issues in advance, predictive maintenance solutions streamline resource allocation, including labour, spare parts, and energy, resulting in minimised wastage and reduced environmental footprint. Proactive equipment health monitoring enhances workplace safety and fosters a secure work environment. The use of IoT sensors and AI-driven analytics adds another layer to the sustainability efforts, by empowering manufacturers to manage energy consumption of machines by pinpointing energy-intensive areas and suggesting optimisation strategies.

As industries strive for net-zero emissions, how do you envision predictive maintenance contributing to this goal?
Predictive maintenance empowers industries to operate in a more resource-efficient and environmentally conscious manner. By proactively identifying and addressing equipment issues before they lead to failures, we minimise energy waste, reduce unplanned downtime, and optimise the use of valuable resources. This directly contributes to energy savings, reduced carbon emissions, and overall operational efficiency. Additionally, by extending the lifespan of equipment, it promotes a circular economy, minimising the need for new manufacturing and reducing the environmental impact associated with resource extraction. Essentially, predictive maintenance is a crucial enabler of sustainable practices, aligning industrial operations with the principles of environmental consciousness and responsible resource management.

How does predictive maintenance play a role in minimising carbon footprints for various industrial processes?

Implementing predictive maintenance in manufacturing offers maintenance teams the opportunity to optimise energy usage. Conventional manufacturing processes often encounter energy inefficiencies due to equipment defects. For instance, machines experiencing faults can suffer from heightened frictional losses, leading to increased energy consumption. However, the integration of IoT-enabled sensors and AI-driven analytics enables manufacturers to achieve effective energy usage. Placing IoT sensors strategically across the manufacturing floor facilitates the collection of real-time energy consumption data, which is then processed by AI algorithms to analyse patterns and provide actionable insights for optimisation, thereby enabling manufacturers to mitigate energy wastage and refine energy consumption practices. Predictive maintenance empowers industries to take proactive steps towards achieving their sustainability goals, meeting environmental regulations, and fostering an environmentally responsible future.

What is your company's long-term vision for sustainable predictive maintenance solutions?
We envision a future where predictive maintenance solutions revolutionise and redefine industrial operations. Our long-term vision revolves around seamlessly integrating cutting-edge technology with sustainability principles to drive transformative change.

Our vision is to empower manufacturers to make informed decisions through data-driven insights. We enable them to maximise their operational efficiency, enhance safety standards, and allocate resources judiciously, by providing actionable intelligence. We see our solutions as catalysts for positive change, encouraging industries to adopt more sustainable practices while achieving operational excellence.

We are collaborating closely with our customers, partners, and stakeholders in a dedicated pursuit to enhance the significance of predictive maintenance in the realm of sustainability. Our goal is to be at the forefront of this transformation, enabling industries to not only optimise their operations but also contribute meaningfully to an environmentally responsible and sustainable future.

Reference
1. https://nanoprecise.io/products/nrgmonitor/