Factories
5 min read

Here’s how a leading tube pipe manufacturer increased its efficiency using SmartSense

Published on
January 25, 2023
Highlights
% + Productivity Gain
People statistic if applicable.
% - Emissions Reduction
Planet statistic if applicable.
% - Cost Reduction > Increase
Profit statistic if applicable.
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Exploratory project to modernise the monitoring system of a leading piping and tubing manufacturer. The goal was to integrate our technology into their infrastructure, giving them coherent energy data in order to build KPIs, improve efficiency, and predict downtime.

In the manufacturing industry, efficiency without overburdening the workforce is key to maintaining productivity. Traditionally, manufacturers have relied on supervisors and middle managers to pinpoint inefficiencies, but that solution is both labour intensive and prone to oversight. To grow with the times, enterprises now must turn to more innovative solutions to maximise productivity.

One of our clients is just such a leading manufacturer, in the business of providing comprehensive, end-to-end engineering solutions in the key areas of piping, tubing, forging and heat transfer. Headquartered in Chennai, with 18 high class manufacturing plant facilities across India, the group has a total combined spread area of over 1.5 mil. sq ft. The plants are equipped with the latest manufacturing equipment for hot and cold pipe forming, induction bending, forging, heat treatment, machining, profile cutting, welding, testing and a variety of other material handling jobs.

The company approached us, looking for a better way to monitor their assets, identify energy wastage and achieve peak productivity. They were hoping to achieve savings of $250,000 thanks to our application of cutting-edge technology and human innovation.

Pain points

Before Ecolibrium stepped in, the client had an existing energy management system, complete with sensors, with all major loads connected. However, they had no way of analysing this data and gaining insights into daily operational inefficiencies, and therefore couldn’t build energy KPIs for better management.

Additionally, they had no way to measure Specific Energy Consumption (SEC), and no dashboards to monitor energy consumption. All of this put together meant the company, though successful, was racking up avoidable losses thanks to unoptimised systems.

Solutions

Instead of dismantling and replacing the current infrastructure, which was found to be problematic in many areas, we believed we could achieve greater success by integrating our solutions as an additional layer on top of the existing landscape. Our team identified 289 energy meters connected to local systems at the client’s manufacturing facilities, that would reveal crucial data about their energy consumption.

When we first connected to the company’s existing system, we found that their sensors were outputting raw data with far too many junk values. Left unchecked, these would invalidate any analytics attempted because of the numerous inaccuracies they cause.

Using our IoT-powered sensors and SmartSense, our AI-powered Asset Intelligence software, we went about validating the data between the 289 energy meters at the ground level, before verifying them once more to increase data accuracy.

We then came up with a centralised energy dashboard for all departments, which displays everything from energy consumption, sources of power, shift-wise power consumption and losses, across departments. This also included a SEC dashboard for different departments, with production data uploaded for monitoring on SmartSense. Multiple user dashboards were created from plant heads down to floor engineers, each able to access the data relevant to their role.

Next, we went about creating an Availability dashboard to track idle operations across manufacturing equipment departments like ERW, CDW, IBP and CRSS. For this, we used SmartSense to generate availability data to indicate how many machines were running idle and for how long, across departments, using real-time measurements of the current drawn by each machine. We then used this data to trigger alerts to users about idle operations, which can then be looked into by the maintenance team. Based on the insights and patterns derived from SmartSense on idle running, we were also able to build automation logics to switch off the tube mills, furnace and other equipment when it was predicted they would be idling for long periods.

We also found that there was a potential to reduce the company’s contract demand with the local Utilities authority from 13,500 kVA to 11,663 kVA. Our energy readings and analytics showed that the maximum demand had risen above 10,000 kVA only a few times in three months, which could also be controlled by proper load management. This would allow to company to potentially save around $80,000 annually on conserved electricity.

We were also able to use the data to identify a number of streamlining measures that would benefit the client. These included a potential 10 percent reduction of the SEC for tube mills and furnaces, a drastic improvement in solar power generation simple by cleaning the panels, and more.

Finally, we built the parameters for an energy KPI report that included details indicating the consumption across plants and departments, maximum demand tracking across plants, units/tonnes across departments, sources of power (TNEB, DG and Solar), availability of machinery, and utilities. This report is generated automatically, on a daily basis, instead of the traditional method of relying on department heads regularly reporting in with data. As a result, skilled manpower can be engaged in crucial jobs where they’re needed, instead of report generation.

All told, with a $20,000 investment over eight months, the client stood to potentially save up to $175,000. Our proposal however was that the client invest an additional $30,000 over the next three months, including a fee for us to provide a dedicated analyst to run the program, and we could save them $385,000. A not insignificant bit of saving as a bonus for when the company’s production is also more efficient.

Conclusion

  • Data capture is now on track, with 289 energy meters integrated with SmartSense
  • Potential to recalibrate Maximum Demand to 1,837 kVa less than before
  • At least 10 percent reduction of Special Energy Consumption for tube mills and furnaces
  • Potential to save approximately $77000 annually on utility contract bills
  • $175,000 potential savings over 8 months with a $20,000 investment

Thanks to the changes implemented on ground by Ecolibrium, the company is now well on its path to undergoing a digital transformation. Our innovative solutions have freed up essential manpower, and also saved hundreds of man hours. But, more importantly, the company stands to see over $ 400,000 in projected savings on their way to achieving sustainable prosperity.

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