Predictive Print Job Tracking System
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Solution Overview
Problem
Existing SLA tracking systems in presentation systems require customers to explicitly list each print job and its receipt time, making it time-consuming and labor-intensive to manage high-volume print shops, where new lists need to be generated daily.
Innovation Solution
A predictive scheduling system that identifies categories of print jobs and stores rules for their frequency, allowing the system to generate schedules without a specific customer list, and alerts operators if expected jobs are not received, thereby automating SLA tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing SLA tracking systems require customers to explicitly list each print job and its receipt time, then tracking accuracy is improved, but implementation complexity and time consumption increase significantly
Solution Approach 1:
The system automatically generates the list of expected print jobs using stored rules about job categories and frequency patterns, eliminating the need for customers to manually create and maintain job lists. The presentation system serves itself by autonomously determining what jobs should be received and when, based on historical data and predefined rules.
Solution Approach 2:
The system pre-stores rules regarding print job categories and their expected frequency in the presentation system before tracking begins. This preliminary configuration allows the system to automatically generate expected job lists without requiring daily manual intervention, resolving the contradiction between accurate tracking and implementation complexity.
2Measurement precision
If manual list generation is required for each day's print jobs, then tracking precision is maintained, but productivity decreases due to substantial time and effort required
Solution Approach 1:
The presentation system automatically generates daily lists of expected print jobs by querying stored rules and category definitions, eliminating the need for operators to manually create these lists each day. This self-service approach maintains precise tracking while dramatically improving implementation efficiency.
Solution Approach 2:
The system continuously automatically generates and updates the expected job lists based on stored rules, ensuring tracking precision is maintained without requiring intermittent manual intervention. This continuous automated operation resolves the contradiction between precision and productivity.
3Ease of operation
If predictive schedules are generated automatically without customer lists, then ease of operation is improved, but reliance on accurate rule analysis increases system complexity
Solution Approach 1:
The system performs preliminary analysis and stores simplified rules about print job categories and frequency patterns in advance. This pre-processing of complexity allows the system to generate predictive schedules easily during operation, resolving the contradiction between ease of operation and underlying system complexity.
Data Source
AI summary
Systems and methods are provided for predictively tracking expected print jobs. The system comprises a memory that identifies categories of print jobs, and that stores rules that indicate how often print jobs will be received at a presentation system. The system also comprises a control unit operable to identify a rule for a category of print jobs, to analyze the rule to generate a predicted schedule of print jobs expected for receipt at the presentation system, and to determine whether expected print jobs have been received at the presentation system in accordance with the schedule. The control unit is further operable to generate an alert if an expected print job has not been received at the presentation system in accordance with the schedule.