Factories and Manufacturing Plants: Why Invest in Energy Analytics Software?

 Almost all businesses have already taken some energy and demand reduction programs, mostly because the laws of the land insist upon it.But, most of them have chosen the low hanging fruit and have undertaken lighting retrofit projects, signed up for utility audits and demand response programs, and some have even gone further installing smart meters, sensors and by investing in roof-top solar or other distributed energy generation methods.

Unfortunately, with all that investment and effort undertaken, the businesses are still far away from achieving their desired operational savings and successfully meet their corporate sustainability goals. And to make the matters worse, the energy portfolio of these business and the cost of their energy continues to rise.

Most of the companies in this position truly do not know how to prioritize the next step or how to get a return on their investments already made in the energy saving schemes and programs. Hence, there is an imminent need for actionable and intelligent information that would help them in further energy decision-making and reap the benefits of investments made in green-field projects. Energy analytics provides that actionable information which could help them achieve their desired goals of energy optimization and cost reduction.  A real-time, easy to use, energy analytics software and monitoring platform available 24*7 could help these industries  identify and optimize the cost of energy in the products they make. It would be equally applicable for discrete manufacturing, process manufacturing, batch process and distribution environments with a sole focus on reducing the cost of energy for the customer. An ideal software would combine the three critical data sources listed below, convert data into actionable intelligence and send alerts to the concerned personnel to take action when it matters the most.

  1. Energy and Power data – data obtained from energy-meters, submeters, data loggers etc. from the key load centers, both physical and virtual.

2. Production Data – Integrated with customers’ existing ERP system.

  3. Cost – Combining the tariff schedule with energy consumption and demand charges.
The software should integrate historical and real-time data, live weather data, location data and apply that data in the context of individual businesses, their utility tariffs, and make valuable and actionable predictions to guide the managers 24 hours on all 365 days of the year.
In addition, it must integrate and correlate all Energy Cost Influencing Factors and provide the industrial customers actionable and usable data in real-time helping them reduce their operational costs, improve their energy efficiency and reduce their carbon footprint.