Automated Image Nesting Algorithm for Printing Sheet Layout Optimization
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Solution Overview
Problem
Conventional methods for printing multiple images on a single sheet are inefficient, leading to significant waste of paper and processing time due to poorly positioned print jobs, especially on high-value paper stocks.
Innovation Solution
An automated method that determines the width and length of each image object from metadata to optimize positioning, creating columns and rows based on the largest and second-largest dimensions, allowing for maximum utilization of the page space and minimizing waste by positioning images in a column-by-column and row-by-row process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If conventional approaches are used to print multiple print jobs onto one sheet, then the printing capability is provided, but paper space is wasted due to inefficient positioning
Solution Approach 1:
The system performs preliminary layout calculations and positioning optimizations before the actual printing process. By pre-determining the optimal positions of multiple print jobs on a sheet using algorithms that consider sheet dimensions, job dimensions, and nesting possibilities, the system maximizes space utilization and minimizes waste before printing begins.
Solution Approach 2:
The invention transitions from traditional one-dimensional or simple grid-based layout approaches to two-dimensional optimized nesting arrangements. By utilizing both horizontal and vertical dimensions effectively through sophisticated positioning algorithms, the system can fit more print jobs on a single sheet, thereby reducing paper waste while maintaining high productivity.
2Loss of substance
If multiple images are printed on one sheet, then paper saving is achieved, but processing time increases due to inefficient positioning
Solution Approach 1:
The system replaces manual or trial-and-error positioning methods with automated computer-based algorithms. The processor executes optimization routines that quickly calculate optimal layouts, eliminating time-consuming manual adjustments and enabling efficient processing of multiple images per sheet without increasing overall processing time.
Solution Approach 2:
The invention dynamically adjusts positioning parameters such as image orientation, spacing, and arrangement patterns based on the specific characteristics of the images and sheet dimensions. By optimizing these parameters through automated calculations, the system achieves efficient space utilization without requiring additional processing time for manual parameter tuning.
3Loss of substance
If print jobs are positioned to maximize space utilization, then paper waste is reduced, but the complexity of positioning increases
Solution Approach 1:
The system employs a universal positioning algorithm that can handle various image sizes, orientations, and sheet formats through a single integrated solution. This multi-functional approach eliminates the need for multiple specialized positioning methods, reducing the apparent complexity while achieving optimal space utilization across different printing scenarios.
Solution Approach 2:
The automated positioning system performs self-optimization by automatically calculating and adjusting layouts without requiring complex manual configuration. The algorithm independently handles the complexity of space optimization, allowing users to benefit from reduced paper waste without needing to understand or manage the underlying positioning complexity.
Data Source
AI summary
A system and method provide efficiency in the placement of image objects onto a page space. Print jobs become more efficient in use of page space to minimize the amount of blank space left by maximizing the number of images per space available according to a process of defining columns and rows for each column. A column may be defined by the available image object with the largest width. Subsequent columns may be defined by the next objects with the next largest widths that fit within available page space. Once columns are defined, each column may define rows based on the image objects that maximize page space for each row. The process may reiterate for each column until no more image objects are available or the remaining available empty page space can no longer fit an object.