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Emerging technologies – especially IIoT and analytics – have opened an opportunity for near-zero unplanned downtime while improving asset longevity and costs. Bill Larson, Director, Process Improvement, CSX Transportation, presented “On Track Work Equipment EAM Wireless Sensor – PM Integration” at the Forum by ARC Advisory Group earlier this year. As a major railroad, CSX provides rail-based freight transportation and services in North America, including intermodal containers. CSX Transportation encompasses about 21,000 route miles of track in 23 states, the District of Columbia, and the Canadian provinces of Ontario and Quebec. Some two-thirds of Americans live within CSX’s service areas.
Rethinking Asset Management
The combination of aging infrastructure and industry dynamics for safety, regulations, growth, and competition exerts pressure for railroad operators to rethink how to manage their geographically dispersed assets. New technologies combined with innovation provide opportunities to lower maintenance costs while improving KPIs like uptime and mean time between failures (MTBF). At CSX, this realization drove a transformation to intelligent, interconnected, instrumented, and – ultimately -- optimized assets.
Mr. Larson’s presentation focused on CSX’s “Work Equipment” class of assets for upgrading its railway track. In total, Work Equipment includes 3,500 individual machines. This includes complex tamper machines to restore the track surface following replacement of ties and/or track.
Predictive Maintenance
The project’s objective involved improving equipment reliability (uptime and MTBF) and utilization (extend time between rebuild cycles) with lower maintenance costs. An initial study proved that the OEM’s current recommendation to change the oil and filter in the tamper every month was too conservative. Based on an initial study, the oil and filter replacement time was extended from 30 days to 45 days, saving $1.3 million in filters and labor alone. Further analysis showed that, with predictive maintenance, the change cycle could be extended to 60 days and save an additional $1 million annually in filters and labor.
The CSX PdM application performs analytics that identify a problem before it can lead to a failure. Integration with the IBM Maximo EAM system automatically generates maintenance work orders. The maintenance planner approves and schedules these work orders in Maximo, and then sends them to the technicians in the field. Completion is fed back into Maximo.
Benefits
With this business process automation, data quality improved and management learned to trust the data. Also, PdM mitigated risk. Approval was given to go with a 60-day cycle for changing filters in the tamper machine. Extending the preventive maintenance (PM) cycle without impacting reliability saved a total of $2.3 million annually, plus productivity improvements.
A video recording of Mr. Larson’s Forum presentation is available here.
Rethinking Asset Management
The combination of aging infrastructure and industry dynamics for safety, regulations, growth, and competition exerts pressure for railroad operators to rethink how to manage their geographically dispersed assets. New technologies combined with innovation provide opportunities to lower maintenance costs while improving KPIs like uptime and mean time between failures (MTBF). At CSX, this realization drove a transformation to intelligent, interconnected, instrumented, and – ultimately -- optimized assets. Mr. Larson’s presentation focused on CSX’s “Work Equipment” class of assets for upgrading its railway track. In total, Work Equipment includes 3,500 individual machines. This includes complex tamper machines to restore the track surface following replacement of ties and/or track.
Predictive Maintenance
The project’s objective involved improving equipment reliability (uptime and MTBF) and utilization (extend time between rebuild cycles) with lower maintenance costs. An initial study proved that the OEM’s current recommendation to change the oil and filter in the tamper every month was too conservative. Based on an initial study, the oil and filter replacement time was extended from 30 days to 45 days, saving $1.3 million in filters and labor alone. Further analysis showed that, with predictive maintenance, the change cycle could be extended to 60 days and save an additional $1 million annually in filters and labor.
PdM required communications for gathering data on runtime and other operating statistics. At about this time, new regulations for commercial driver electronic logbooks drove an investment in communications. An evaluation determined that this new infrastructure could be leveraged for the communications needed to support PdM.
The CSX PdM application performs analytics that identify a problem before it can lead to a failure. Integration with the IBM Maximo EAM system automatically generates maintenance work orders. The maintenance planner approves and schedules these work orders in Maximo, and then sends them to the technicians in the field. Completion is fed back into Maximo.
Benefits
With this business process automation, data quality improved and management learned to trust the data. Also, PdM mitigated risk. Approval was given to go with a 60-day cycle for changing filters in the tamper machine. Extending the preventive maintenance (PM) cycle without impacting reliability saved a total of $2.3 million annually, plus productivity improvements.
A video recording of Mr. Larson’s Forum presentation is available here.