Data State Manager for Synchronized Printing
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Solution Overview
Problem
Digital press environments lack the capability to support distributed production environments effectively, failing to scale, synchronize, and reproduce complex data structures and production intents in a dynamic and consistent manner.
Innovation Solution
A data state manager system that slices, distributes, and synchronizes data streams across multiple printing devices based on metadata and device capabilities, includes modules for error detection and recovery, auditing, and reconstitution of production intents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital presses are used to print a variety of products with different substrates, then product versatility is improved, but system complexity increases
Solution Approach 1:
The system employs a universal data structure format (XML-based) that can represent multiple production intents including variable data printing, traditional printing, personalization, and finishing operations. This single data structure serves multiple functions across different printing scenarios, reducing the need for separate specialized systems for each product type while maintaining versatility.
Solution Approach 2:
The patent introduces a digital front end (DFE) as an intermediary component that translates various customer print jobs into a standardized submission format and queues them to digital presses. This mediator handles the complexity of converting diverse input formats and requirements into a unified processing framework, isolating the presses from direct complexity while maintaining adaptability.
2Productivity
If data streams are distributed across multiple printing devices, then productivity is improved, but synchronization difficulty increases
Solution Approach 1:
The patent segments the data stream into multiple independent data streams that can be processed simultaneously by different printing devices. Each data stream maintains its own state information, allowing parallel processing while reducing synchronization overhead. The segmentation enables load distribution across multiple devices, improving productivity without requiring complex inter-device coordination.
Solution Approach 2:
The system implements feedback mechanisms where the DFE continuously monitors the state of multiple digital presses and adjusts data stream distribution dynamically. This feedback loop enables automatic load balancing and synchronization by routing jobs to available presses and tracking their completion status, managing distributed production complexity through continuous state awareness and adaptive resource allocation.
3Adaptability or versatility
If production intents are sliced and distributed dynamically, then adaptability is improved, but data management complexity increases
Solution Approach 1:
The patent implements dynamic slicing of production intents based on real-time press availability, job characteristics, and production requirements. The system can adjust how data streams are divided and assigned to different presses during operation, rather than using fixed predetermined assignments. This dynamic approach allows the system to adapt to changing conditions while maintaining manageable data flow through automated decision-making algorithms in the DFE.
Data Source
AI summary
A data state manager may include a production intent module to define a production intent, a capability module to identify a number of capabilities of a plurality of media printing devices to which the data state manager is coupled, and a data stream module to, through a plurality of communication links to the media printing devices, stream a plurality of data streams to the plurality of media printing devices in a synchronized manner based on a number of characteristics of the streamed data and the identified capabilities of the media printing devices, with the data streams defining the production intent.