Customer Focus

A leading food manufacturing company based in Madhya Pradesh, India, operates large scale production facilities catering to growing consumer demand across regional and national markets. As production volumes continued to expand, energy consumption across utilities, processing units, and auxiliary systems increased significantly. Managing plant wide power utilization while maintaining operational efficiency became a strategic priority for the organization.

Requirement

With rising energy tariffs and increasing production intensity, the organization required a structured approach to monitor and analyze energy consumption across departments. Limited visibility into real time usage patterns made it challenging to identify inefficiencies, benchmark performance, and establish accountability across operational units. The objective was to implement a technology driven framework enabling accurate monitoring, consumption transparency, and data based energy management.

Before implementation, energy monitoring was largely manual and reactive. The plant faced multiple operational limitations:

• There was no real time visibility into electricity consumption across departments
• Energy data consolidation was manual and time consuming.
• Energy cost per unit production was increasing without clear traceability.
• There were no automated alerts for abnormal consumption or demand spikes.
• KPI based monitoring and benchmarking were limited.

This lack of digital transparency made it difficult to identify inefficiencies, standby losses, and peak demand penalties.

The management team needed a smart, scalable solution aligned with Industry 4.0 and sustainability goals.

LUBI iFactory Factory Energy Management System

LUBI Electronics deployed its advanced iFactory FEMS platform, designed to enable intelligent, data driven energy management across industrial environments.

The solution included smart meter based real time data acquisition integrated across critical panels and zones. Energy data was captured, analyzed, and visualized through a centralized dashboard providing plant wide transparency. 

The architecture was designed in four strategic layers:

Layer One focused on smart meter data acquisition from all major loads and departments.

Layer Two enabled visualization through dynamic dashboards and trend analytics.

Layer Three introduced KPI benchmarking and performance tracking to monitor energy intensity and cost per unit production.

Layer Four leveraged AI based forecasting and optimization tools to identify savings opportunities and peak load management strategies.

Functional modules included real time demand monitoring, zone wise energy trend analysis, peak and low tariff optimization, abnormality detection alerts, and automated reporting with audit trails.