Case Study: Downer Group achieves predictive maintenance and higher train reliability with IBM Instana and IBM

Downer and IBM keep passengers moving safely, reliably and comfortably with updated, sustainable asset management

Downer Group, a leading provider of integrated urban and rail services in Australia, faced the challenge of managing long-term maintenance for hundreds of passenger trains. They needed to shift from a reactive maintenance model to a predictive one to improve reliability, support sustainability goals, and manage their fleet more efficiently. To address this, they partnered with vendor IBM and leveraged the IBM Maximo Application Suite as the core of their TrainDNA asset management platform.

The solution implemented by IBM involved creating the TrainDNA platform, which uses IBM Maximo and IBM MQ to process over 30 million data messages per hour from the trains for predictive maintenance. This allowed Downer to predict failures and optimize maintenance schedules. The results were significant, including a 51% increase in fleet reliability and the ability to double maintenance capacity at one facility with a 20% efficiency gain. IBM's technology provided the foundational data and analytics that enabled these improvements.

Downer Group

Adam Williams

Head of Growth for Rail and Transit Systems