About the Client

American coin and dollar counting machine manufacturer and distributor serving to 1500+ Banks across North America.

The Challenge

Client was managing Field service for all the Banks based on reactive and scheduled maintenance data. Despite of having 800+ field technicians, client was not able to give Smart Field service to their customers.

• Most of the inspections and maintenance are still done with pen and paper, putting an undue burden on field technicians to organize and ensure the accuracy of their handwritten results.
• Audit locations are selected randomly, without considering efficient travel routes, impacting the field technician’s productivity and effectiveness.
• With around 1500+ sites for various technicians and without data driven prioritization/scheduling, critical maintenance is not addressed in time.

What We Did

• Clustering
• Classification
• Machine Learning
• Enterprise App Development

• Data Acquisition
• Data Cleansing
• Predictive Analysis
• Statistical Modelling
• Clustering
• Classification
• Machine Learning
• Enterprise App Development

The Solution

With predictive analytics and ML based statistical modelling technique, client managed to offer premium SLA with predictive and prescriptive maintenance.

• Failure Prediction – Predict time of the next machine failure. This will ensure there are fewer emergency calls.
• Inventory Acquisition Prediction – Predict part(s) that will fail or wear out. The field technician will come over to the call site with the correct spare parts.
• Service Time Prediction – Predict the time it will take for a technician to complete the call.
• Smart Allocation – Suggest the most competent technicians for a given service call.

Results & Outcomes

DXFactor developed Smart Filed Service Management with Predictive Maintenance based on historical and real-time data to achieve Zero down time of Machines for all the Banks.