• CASE STUDY IoT Pumps

    Freestyle Drink Machine Field Service Network

  • "This project was a big success for Coca-Cola."

    Senior Director Reliability, Coca-Cola

  • Field Service Case Study: IoT Pumps

    Freestyle Drink Machine

  • Challenge

    Excessive Failures

    Coca-Cola has a large fleet of 40,000 Freestyle drink machines at restaurants and movie theaters throughout the US. They are connected to the internet, and every night they upload to their cloud the day’s activity and machine status data for various systems. Each machine has over 10 digitally controlled electronic pumps that dispense flavor ingredients according to customer selection. Pump health data is based solely on machine codes, a symbolic representation of pump behaviors covering a wide range of operating conditions from normal to not-normal.

     

    The Freestyle fleet was experiencing excessive pump failures, which resulted in a degraded customer experience because certain flavors not being available. Service calls for pump replacement were going up. Technicians on-site were unable to diagnose whether it was a pump failure or come other condition. They were replacing many more pumps than necessary.

     

    The Freestyle team engaged DecisionIQ to determine if these machine codes could be used to create diagnostics that would enable on-site field technicians to determine if a pump needed replacement.

     

    Solution

    Diagnostics Analysis & Report

    Using these machine codes, the DecisionIQ platform was able to provide failure diagnostics to the field technicians. It also found a larger problem: a production lot of pumps that had a defective seal, randomly distributed through out the fleet. A defective seal presents the kind of variability in performance difficult to isolate.

    Performance Result

    Significant Gaines

    The DecisionIQ platform to isolate the problem to the random distribution of a defective production lot of pumps. Proactive replacement of these pumps would solve much of the customer service problem and eliminated the need for on-site diagnostics.

    • Fleet size | 40,000+
    • Pumps in fleet  | 500,000+
    • Defective Production Identified  | 3000+
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