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Analytics enabling resilience in Manufacturing - Episode 2
Analytics enabling resilience in Manufacturing - Episode 2
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Asset maintenance amidst Covid-19: How can data analytics help?

  • Episode 2 of the thought-leadership series – Analytics enabling resilience in Manufacturing – looked at using data analytics & real time insights to monitor & improve health and performance of machinery.

The Covid-19 pandemic posed a major challenge to the manufacturing industry, especially for the first quarter after the pandemic hit India in March this year. Though demand has picked up from September, and the new levels are unprecedented for some sectors, businesses are looking at maximizing throughput and improving efficiencies to meet the surge.

Episode 2 of the thought-leadership series – Analytics enabling resilience in Manufacturing threw light on employing analytics for preventive equipment maintenance helping businesses in the manufacturing space to optimize their efficiencies.

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While digital transformation has been an area of focus for businesses for a long time, the Covid-19 pandemic has really brought it to center stage and has in many ways been an eye opener across business lines; technology is no longer viewed as a replacement to manpower.

“Covid has put the focus on digital from two angles – the ability to monitor risk and to maintain business continuity. Earlier, the mindset was that digital replaces people and won’t happen in India. But with Covid, it is not seen as a replacement but as a tool used for continuing business in the absence of people or when they are travelling. That’s where automation and predictive maintenance comes in," said Samip Mutha, Vice President and Head of Digital and Innovation, RPG Group.

The business that was lost out in the first quarter after the pandemic needs to be made up for – and some units are trying to make up for the losses by producing what they would in 12 months in just nine months now. With such high demands, downtimes can’t be avoided and technology will play the role of an enabler when it comes to asset maintenance.

“Till June, it was a complete washout for the auto industry. It started picking up with two wheelers first, followed by private vehicles. There was a sudden spurt in demand, first from rural areas and then urban areas from September. We assessed our losses and saw how to make up in the months to come. The first thing to ensure is that asset utilization is maximum and investments & expenses are being reduced," said Sridhar V, Director - Purchase, Honda Motorcycle & Scooter India Pvt Ltd.

Honda’s approach has evolved with the needs of the organisation. “When we started in 2001, we were one small factory and maintenance was a reactive approach. We had some planned maintenance, wherein you replace parts at a set frequency. But, as we expanded our business, and as we increased the number of factories, we changed our approach to maintenance from purely reactive, to a proactive and to an extent a predictive approach. Now, in one of the factories, we have implemented a smart intelligent software and we have been able to get all the benefits like OEE as well as asset utilization," he added.

The change is being felt not just in India, but globally too in the field of manufacturing. “Certain use cases turned to imperative and vital projects for businesses. So, if there was a requirement, they had to go with the most skeletal crew," said Peter Pugh-Jones, Head of IoT Operations, EMEA & AP, SAS.

The main objective behind using data and analytics is to maximise asset life and reduce unplanned downtime of machinery, without compromising on safety and reliability.

“Predictive maintenance can be enhanced through assimilating the data from sensors, from maintenance data, combined with historical area data to uncover the hidden messages which can be leveraged to build a robust model and continuously track it while the data is still in motion and understand what may be coming your way and avoid any kind of unscheduled downtime," said Nabuath Ulla Khan, Practice Head Manufacturing and IOT Analytics, SAS.

SAS is focussed on offering a robust, holistic solution which can integrate with various systems and is predominantly towards data, discovery and network. It works across industries ranging from truck fleets and turbine engines to wind turbines, gas treatment plants and oil wells.

Automation is not just about viewing downtime and maintenance as failures. It is also about improving efficiencies and not letting the throughput fall. “In the newer age plants where there is a lot more automation, that’s where the power of analytics is something that we really look at very differently. It’s not only about downtimes. When you are operating at 95 percent throughput capacities, it is about getting the rea; juice out of the data from these automated machines which can leverage the efficiency rates," explained Aashish Kshetry, VP- Human Resources and Information Technology, Asian Paints.

So, what are the fundamental benefits that predictive analytics it can provide to an organisation? “In an automated, predictive factory, in a manufacturing unit, the element of ensuring that the various connected systems work at the desired levels to provide the optimum output and operating levels," Kshetry added.

For an organization that is embarking on its digitization journey in the manufacturing sector, it is key to select the right areas in the first phase so that the effect is visible on the RoI. It is also very important that the people on the shop floor understand the benefits this process of analytics will bring.

“Firstly, we need to select key areas which are critical to the books and ROI. Secondly, you need to have some kind of historical data which is sitting in a non-digital format. To get the best results from analytics, you must merge these two worlds together and map it back to your ROI," concluded Khan.

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