Data-Driven Continuous Improvement Process For Railway Construction Projects

Abstract

Delays And Cost Overruns Are Frequent In Infrastructure Construction Projects. Deviations Are Often Identified Late, And Their Causes Cannot Be Traced Back. Traditionally, Decisions Are Made By Experience And Not With The Support Of Data Directly Coming From The Site. Moreover, Schedules Are Often Static And Thus Not Able To Reflect The Real Conditions On-Site. Emerging Technologies Like Building Information Modeling (BIM), Mobile Cloud Computing As Well As Advanced Sensors Can Help To Overcome The Previously Mentioned Issues. In The Paper, We Propose A Framework For A Digital Platform To Gather Production Data In Real-Time And To Identify Early On Bottlenecks That Could Potentially Lead To Delays And Deviations. The Proposed Platform Should Support Collecting, Analyzing, And Structuring Production Data In Real-Time. With A Demonstration Case We Show The Three Main Functionalities Of The Platform: 1) Retrospective Analysis, 2) Live Analysis And 3) Predictive Analysis. In Future Research, The Platform Will Be Implemented And Validated Within Railway Construction Projects Of The Company Rhomberg Sersa Rail Group AG.