A professional digital tool to process, analyse, visualise and communicate
laboratory washing results with a consumer-centric approach
It shows what consumers would see when evaluating washing results in diverse visual scenarios, where garments are washed, stored or used—validated and verified. Transform lab data to new consumer's perception data.
It includes perceptual thresholds to represent how consumers discriminate satisfaction in cleanliness, whiteness and colour-care.
It works for different regional consumers around the world, different laundry experiences, different cultures.
It combines cutting-edge concepts in fluorescent spectroscopy, colour appearance models, colour reproduction and WebXR technologies. It is the most advanced scientifically-based digital tool in the detergency field.
In blending with VR-Clicks (the digital tool to collect consumer responses), they offer the most modern and advanced approach to represent the interaction between consumers with products and products' performance in relevant visual scenarios.
Since November 2021, the application has included the Stain Removal Index in Virtual Realities (SRI-VR), the most advanced representation of cleanliness perception considering garment irregularities/textures in virtual visual scenarios.
Since January 2023, the application includes interactive spectral radiance factors and interactive uniform colour spaces in order to sustain the fundamentals of cleanliness, whiteness and colour-care indexes.
Is this for my team or me?
What input data do I need from my detergency laboratory?
Interested to experiment a demo? Contact Us!
Interested to get a free trial with your lab data? Contact Us!
Frequently Asked Questions (FAQs):
What is new?
The new Stain Removal Index in
Virtual Realities (SRI-VR) is
the unique feature of
Laundry-VR. It combines
cleanliness lab readings with
dinginess levels for the first
time in the industry. Now
shadows, creases, bottoms,
seams, and redeposition of body
and other soils are considered
to quantify cleanliness
How is it calculated? Four (4) different consumer-relevant garments are rendered, each with a different stain location and dinginess level. The remanent stained area and its proximal field are characterised by the appropriate RGB values, which are transformed to colorimetric attributes and then the SRI is calculated. See the below graphs.Main implications:
Graph 01. Mud stain on socks:
Graph02. Collar stain on shirt:
Graph 03. Armpit stain on T-shirt:
A screenshot of the new outputs in Laundry-VR:
Contact us to see a demo or to experiment with your lab readings.
terms and definitions