Visualizing Electricity Usage to Support Energy Monitoring and Decision-making: A Study of an Automotive Manufacturing Plant

Abstract

Aims: This study aims to examine current electricity monitoring practices in an automotive manufacturing plant and to demonstrate how electricity usage data can be visualized using Microsoft Power BI to support better energy-related decision-making. Study Design:  This research adopted a qualitative case study design supported by quantitative electricity consumption data. Place and Duration of Study: The study was conducted at an automotive manufacturing plant, using electricity consumption data collected over a one-year period. Methodology: A qualitative approach was employed using multiple data sources. Data were collected through semi-structured interviews, direct observations, document analysis, and quantitative electricity usage records. Methodological rigor was ensured through data triangulation across multiple data sources. Based on the integrated data, an interactive Power BI dashboard was developed to visualize electricity consumption. Results: The developed dashboard included total electricity consumption, monthly usage trends, electricity usage per unit of production, plant-level comparisons, and electricity supply sources. The developed Power BI dashboard improved the visibility of electricity consumption patterns and facilitated the identification of inefficiencies and usage trends, supporting more structured energy monitoring and enhanced management understanding of electricity usage across different production areas. Conclusion: This study demonstrates that data visualization using Power BI can support data-driven decision-making and sustainability efforts in automotive manufacturing. The findings highlight the practical value of interactive dashboards in strengthening electricity monitoring practices in electricity-intensive manufacturing environments.