MV launched a pilot with the Capital Metropolitan Transportation to develop a predictive analytics solution that reduces unexpected maintenance events.
MV Transportation

MV launched a pilot with the Capital Metropolitan Transportation to develop a predictive analytics solution that reduces unexpected maintenance events.

MV Transportation

Transit agencies today are faced with the never-ending need to increase safety, efficiency, and reliability without sacrificing customer service. With the advent of advanced data analytics and artificial intelligence, it’s now possible to glean insights from historical and real-time data that not only improve operational performance but enhance the passenger experience.

MV Transportation is tapping into advanced analytics in partnership with Microsoft and Avanade to address several core parts of its business. MV is evaluating safety data to help drive process transformation; operational data, including overtime and on-time performance, to address pain points in hiring and retention; and maintenance data to develop predictive maintenance programs that reduce unplanned maintenance events. In each case, they are leveraging analytics to connect the dots between data and bring unique insights to life.

MV launched a pilot with the Capital Metropolitan Transportation Authority in Austin, Texas to develop a predictive analytics solution that reduces unexpected maintenance events by optimizing preventive maintenance for each vehicle based on utilization and environmental risk factors. The new program allows MV, which operates bus service for CapMetro, to customize maintenance to help prevent road calls for specific vehicles that are determined to be a higher risk, based on age and service miles, for example. The program takes these data points into account and identifies vehicle systems with the highest risk of failure to facilitate preventative maintenance actions.

MV will continually ingest data from CapMetro so that the system can learn and make new predictions. If the system detects a new pattern from analysis of work order history, it will suggest actions based on the data. With the maintenance department able to anticipate which vehicles are most likely to fail, service interruptions will drop, on-time performance and vehicle availability will improve, and passengers will ultimately enjoy a seamless ride.

MV’s analytics program moves away from static and historical reporting and allows for dynamic, real-time exploration and analysis of data. It changes the approach to preventative maintenance, delivering new data transparency, improving responsiveness, and opening the door for significant future savings. With the success of its pilot efforts, MV is expanding the availability of its analytics solutions to more of the customers the company serves with fixed-route, paratransit, and shuttle services and has also begun offering them as standalone professional services.

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