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Digitization – Machine Level Energy Monitoring in Factories

The cost of computing has decreased exponentially over the past many decades. Your smartphone is more powerful than the supercomputers of the 1960s that were used to land on the moon – and it is available at a price point which you can afford. This reduction in cost has seen computers penetrate almost all parts of our lives and improve our productivity.

The advances in computing and connectivity via the internet has created a market for connecting mundane devices to the internet for getting information about its state and controlling it.


In factories the interconnectedness of machines to the internet has led to a multifold increase in productivity – large industrial facilities have a Supervisory Control and Data Acquisition (SCADA) system with from where every piece of equipment is controlled. For small and medium enterprises (SME) a full-scale SCADA is out of reach.

Moreover, even electricity, although it forms a significant cost item for most SMEs, for the most parts, is measured by the good old utility meter, at the end of the month by a meter reading person sent by the utility. At times, factories cross their allotted loads and pay penalties and at others, they underutilize the available capacity affecting uptime and production – ex-post. What’s measured is controlled! And electricity at a circuit level is not measured.


Although, in my recent conversations with plant operators in India, I found that most of the operators monitor electricity consumption (kWh) daily. An analyst would go to the meter at the end of the day, take the reading and input it in a spreadsheet program. Over the years, operators develop an eye for spotting a discrepancy in consumption trend and take corrective actions like lubricating the motors. Additionally, most of the operators I interviewed claim that their maintenance programs are well run and that there is no wastage of electricity due to worn out components etc.. I believe that they do a good job.


However, a 24hr sampling hardly provides any insight about what goes on within a shift or within an hour. Hourly energy consumption data by machine or by HVAC when matched with external data sources, like hourly temperature, hourly production or machine downtime reports reveal compelling value-added insights to optimize production.

One of Oorjaa’s clients, a steel pipe manufacturer, discovered that its mills were idling with no production reported on more than five counts last May costing it thousands per day. Supported by Oorjaa, the client matched its daily production data with time-stamped electricity consumption recorded by CircuitMeter platform,[1] at the respective machines. The client then got the exact days on which machines were idling. Corrective action, as a daily report matching production with electricity consumption, will save thousands per month.

[1] https://www.circuitmeter.com/

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