Virtual Planogram Automation for Packaging Dimension Changes
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Solution Overview
Problem
Existing planogram generation systems are inflexible and require significant time and human effort to adapt to unexpected changes in product dimensions, leading to delays and costs due to unusable planograms.
Innovation Solution
An automated planogram generation system using computer vision to detect changes in product dimensions and generate new planogram options, allowing for agile and data-driven adaptations with minimal human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If planograms are generated infrequently with significant time and human supervision, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The system pre-generates multiple alternative planogram options in advance, storing them for future use. When product dimension changes occur, the system can quickly retrieve and adapt pre-generated plans rather than creating new ones from scratch, thus maintaining accuracy while improving response speed
Solution Approach 2:
The system automatically adjusts planogram parameters (product positions, shelf allocations, display configurations) in response to detected dimension changes. By dynamically modifying existing planograms based on updated product parameters, the system maintains high accuracy without requiring complete regeneration, thereby improving productivity
2Reliability
If planograms are made inflexible to maintain stability, then reliability is improved, but adaptability deteriorates
Solution Approach 1:
The system implements dynamic planograms that can automatically adjust to changing conditions. Multiple alternative plans are generated and stored, allowing the system to switch between different configurations based on current product dimensions and retail environment requirements, thus achieving both stability through proven designs and adaptability through flexible selection
Solution Approach 2:
The system modifies specific parameters of existing planograms (such as product positions, shelf assignments, and display orientations) in response to dimension changes while maintaining the overall structure and design principles of the original plans. This approach preserves reliability by keeping proven planogram frameworks while achieving adaptability through parameter adjustments
3Manufacturing precision
If manual correction is used for dimension changes, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system automatically detects product dimension changes and self-corrects planograms by selecting appropriate alternative plans or adjusting parameters without human intervention. This automated self-service approach maintains the precision of manual correction while eliminating the time loss associated with human review and modification processes
4Productivity
If automated generation is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system creates multiple copies of planogram templates and product dimension data that can be quickly replicated and adapted. By using template-based generation and storing alternative plan versions, the system achieves high productivity through automated copying and adaptation rather than complex real-time calculations, thus reducing the effective complexity of the automated system
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables quick and efficient adjustment of planograms to changing product packaging dimensions, enhancing profitability and product placement while reducing manual effort and delays.
Implementation Method 1
An automated planogram generation system using computer vision to detect changes in product dimensions
Data Source
AI summary
A system and method are disclosed for virtual planogram automation comprising receiving, by a planogram planner comprising a server, image data from imaging devices of products prior to the display of the products in a product display area at a retail entity, detecting changes in a product based on the received image data, performing simulated annealing to generate new planogram options by generating a planogram option in response to received image data and one or more received KPI's, incrementing the planogram option according to neighboring states of the planogram parameters, calculating an objective function measuring optimality of the incremented planogram option, repeating the generating, incrementing and calculating steps until a stopping criterion is met according to the objective function, and determining a final planogram based on the stopping criterion being met.