Custom Fragrance Creation System with Variable Potency Scent Normalization
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Solution Overview
Problem
Current fragrance creation methods are subjective, random, and lack the ability to account for time-changing aspects of scents, leading to poorly structured fragrances and limited customer customization options, such as gender specificity, concentration adjustment, and occasion-based fragrances.
Innovation Solution
A system utilizing a 'Perfumer's Organ' with variable and normal strength scent liquids, grouped by family and volatility, allowing customers to select and adjust scents, with a CPU-driven process to determine optimal scent ratios using pre-stored data and compatibility coefficients, ensuring a repeatable and objective custom fragrance creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If customers allow free selection of scents without guidance, then customization freedom is improved, but fragrance structure quality deteriorates
Solution Approach 1:
The system provides real-time feedback to customers by displaying the fragrance composition as they select scents, allowing them to see the evolving formula and adjust their choices. This feedback mechanism guides customers toward balanced selections while maintaining customization freedom.
Solution Approach 2:
The system changes the parameters of scent selection by organizing scents according to volatility categories (top, middle, base notes) and providing guided selection criteria. This structured parameter organization ensures balanced fragrance structure while still allowing customer customization within defined frameworks.
2Productivity
If scents are selected without considering volatility categories, then selection speed is improved, but fragrance performance deteriorates
Solution Approach 1:
The system segments scents into distinct volatility categories (top notes, middle notes, base notes) and presents them in organized groups. This segmentation allows customers to quickly navigate and select from structured categories while ensuring that the final fragrance includes appropriate proportions of each volatility level for optimal performance.
3Device complexity
If fixed blotter groups are used for scent sampling, then device simplicity is improved, but customization capability deteriorates
Solution Approach 1:
The system transitions from static fixed blotter groups to a dynamic virtual blotter interface where scents can be selectively combined in unlimited configurations. The digital system adapts to customer preferences and provides personalized fragrance formulas, enabling extensive customization without physical reconfiguration.
4Ease of operation
If subjective personality tests are used for fragrance selection, then ease of operation is improved, but selection accuracy deteriorates
Solution Approach 1:
The system replaces subjective mechanical personality tests with an automated computer-based fragrance composition system. The computer calculates optimal scent combinations based on stored fragrance data and customer selections, providing precise, objective fragrance matching that maintains ease of use through automated processing.
Data Source
AI summary
A system for creating custom fragrances is described that allows a customer to interact with an employee and a Perfumer's Organ to interactively select several scents for base, middle and top notes. They can then iteratively adjust the scents chosen. In one embodiment, the scents selected by a customer are provided to a computing device having a prestored table which separates the scents into variable potency scents having variable perceived strengths and normal potency scents having standard, equal perceived strengths. The table indicates the amount of each variable potency scent to use to normalize the strengths. The remaining normal potency scents are then added with an equal amount. In an alternative embodiment, predetermined mixtures are provided to the computing device and used as ‘training data’ to adjust the coefficients of a generalized formula to create a prediction equation fit to the training data. The computing device receives the selected scents, the type of product to be made and the container size and uses the prediction equation to identify the amounts of each of the selected scents. In another optional embodiment, a filling device can automatically meter the scent liquids, a filling material, and provide them into the selected container. The filling device is driven by the computing device and determines the amounts of the selected scents and creates the custom fragrance according to one of the methods above.