Fleet Supply Awareness for Printer Maintenance Scheduling
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Solution Overview
Problem
Maintaining fleets of printer devices is inefficient due to complex scheduling of service calls, leading to increased maintenance costs and productivity losses, as traditional methods only allow for individual printer device supply status queries without collective awareness.
Innovation Solution
Implementing a 'collective awareness' system where printer devices within a fleet can access and share supply status information, enabling a predictive usage model to determine remaining supplies and schedule servicing across multiple devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional individual printer supply status queries are used, then each printer can be monitored independently, but fleet maintenance becomes complex and inefficient requiring trained remote agents and complex scheduling
Solution Approach 1:
The patent merges individual printer supply status monitoring into a collective fleet-wide view. The system combines supply level data from multiple printers into a unified representation, allowing a single service call to address multiple devices simultaneously. This eliminates the need for separate monitoring and scheduling for each printer, reducing operational complexity while maintaining comprehensive supply awareness across the entire fleet.
2Reliability
If trained remote agents service multiple customers, then service capability is maintained, but scheduling complexity and maintenance costs increase
Solution Approach 1:
The system performs preliminary actions by continuously monitoring supply levels and predicting when printers will run out of supplies. It proactively schedules service calls before actual supply depletion occurs, allowing service agents to plan routes and times in advance. This predictive approach enables better scheduling efficiency, as agents can group multiple printers into single service calls based on predicted needs rather than reacting to individual failures or depletions.
3Reliability
If individual printer servicing is performed, then supply issues are addressed, but productivity losses and downtime increase due to frequent service calls
Solution Approach 1:
The system schedules service calls in advance based on predicted supply depletion, rather than responding to actual supply issues after they occur. This allows printers to be serviced proactively during off-peak times, minimizing interruptions to worker productivity. By planning service calls before supply runs out, the system ensures continuous operation while reducing the frequency of service interruptions.
Solution Approach 2:
Multiple printer servicing operations are merged into single service calls, where agents service multiple printers during one visit. This consolidation reduces the total number of service calls required, thereby minimizing disruptions to worker productivity while ensuring all printers receive timely supply replenishment.
4Productivity
If collective awareness of supplies is implemented, then fleet management efficiency improves, but system complexity increases
Solution Approach 1:
The system implements a universal supply monitoring framework that serves multiple functions simultaneously: it tracks supply levels across the entire fleet, predicts future supply depletion, optimizes service scheduling, and provides consolidated reporting. This multi-functional approach consolidates what would otherwise require separate systems into a single integrated platform, managing the added complexity through unified data structures and centralized processing logic.
Data Source
AI summary
In one example, collective awareness of supplies includes several operations. A remaining level for each supply in a printer device within a fleet of printer devices is measured. A predicted usage model for each supply from a history of supply usage for printed pages over time in the printer device and other printer devices of the fleet of printer devices is calculated. A system intervention event based on the predicted usage model and remaining level for each supply in the printer device is determined. The system intervention event is communicated to a responsible party.