Automated Shelf Image Generation for Retail Planograms
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Solution Overview
Problem
Creating individual shelf images for different points of sale is time-consuming and does not adequately account for varying demands across locations, requiring laborious manual corrections and post-processing.
Innovation Solution
A data processing system method that allows users to interactively define blocks of items with specific attributes and create sequential placement rules, applying these rules to determine storage locations on shelves, taking into account assortment and shelf data for each point of sale, to generate accurate and efficient shelf images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If derivatives are generated from a master planogram using automated conversion, then productivity is improved, but manufacturing precision deteriorates due to inaccurate conversion results requiring manual corrections
Solution Approach 1:
The system automatically detects shelf characteristics and adjusts the master planogram to create location-specific derivatives without manual intervention. The computer program autonomously performs tasks that previously required manual correction, allowing the system to self-correct and self-optimize the shelf image generation process.
Solution Approach 2:
The system changes parameters such as shelf width, depth, height, and segment configuration to adapt the master planogram to specific outlet requirements. By dynamically adjusting these parameters based on detected shelf characteristics, the system generates accurate derivatives automatically, resolving the contradiction between speed and precision.
2Device complexity
If a single master planogram is used for multiple outlets, then device complexity is reduced, but adaptability deteriorates because site-specific features and varying demands are not accounted for
Solution Approach 1:
The system transforms the static master planogram into a dynamic adaptation process. The computer program automatically adjusts the planogram configuration based on detected shelf characteristics and location-specific demand patterns, enabling a single master template to dynamically generate location-specific derivatives without manual intervention.
Solution Approach 2:
The system segments the planogram creation process into a master template phase and an automated adaptation phase. The master planogram contains the base configuration, while the computer program segments and adjusts specific elements (article positions, quantities, arrangements) based on location-specific requirements, maintaining simplicity while achieving adaptability.
3Adaptability or versatility
If manual post-processing is performed to account for location-specific demand, then adaptability is improved, but loss of time increases due to laborious corrections
Solution Approach 1:
The system replaces the manual mechanical process of post-processing with an automated computer-based system. The computer program detects shelf characteristics, retrieves location-specific demand data, and automatically adjusts the planogram derivatives, substituting human labor with automated computational processes that achieve the same adaptability goals without time loss.
Solution Approach 2:
The system performs preliminary actions by pre-configuring the master planogram with adaptable parameters and pre-storing location-specific demand data. When generating derivatives, the system has already prepared all necessary information and rules, enabling automatic adaptation without requiring subsequent manual corrections or post-processing time.
Data Source
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AI summary
The invention relates to a method for operating at least one data processing unit according to at least one program for producing individual shelf images for a plurality of different sales outlets of a commercial enterprise, wherein ° the program accesses range data that define an individual range of different articles with associated attributes for each sales outlet, ° the program offers a user the opportunity to interactively define different blocks by means of input and output devices, said blocks each comprising one or more articles with at least one attribute that is specific to the respective block, ° after the definition of the blocks is completed by the user, the program accesses the blocks in a data memory, ° the program accesses shelf data with the individual data of at least one shelf of each sales outlet in a data memory, ° the program offers the user the opportunity to interactively produce a sequential series of positioning rules that relate to the positioning of different blocks in shelves, ° after the input is completed, the program accesses the sequential series of positioning rules in a data memory and ° for each sales outlet, the program successively applies the stored positioning rules according to the sequence thereof to the stored blocks with the articles from the range of the sales outlet and, taking the shelf data into account, determines the placing positions of the different articles in the shelf of the sales outlet and ° the program displays the placing positions of the different articles in a shelf image.