In the domain of Railways, India is having second largest railway network in the world. This study focus on a data driven framework for the temporal and spatial analysis of operational disruptions in Indian Railways, mainly focus on Alarm Chain Pulling (ACP) incidents. We have categorized 20,000 ACP events into “On Station” and “Out of Station” occurrences. The analysis highlights key aspect of temporal patterns, identified high risk zones and train numbers then compared the frequency of ACP incidents between goods and passenger trains. The framework demonstrates how the data analytics in enhancing railway safety operational efficiency and cost effectiveness. By using modern and interactive analytical tool, Power BI dashboard offers a comprehensive view of ACP trends, optimizing targeted maintenance strategies and improved decision making for the huge railway network. Our proposed analysis framework offers a valuable insight as well as propose a way to achieve minimum operational disruptions and optimize resource allocation across the Indian Railways network resulting in improving transportation services significantly, which helps in achieving accessible transportation.

Delays,Data model,Spatial, Railways,Resource allocation,Rail transportation