Titre : |
Automated grading with Al and traceability |
Type de document : |
texte imprimé |
Auteurs : |
Neil Martin, Personne interviewée |
Année de publication : |
2021 |
Article en page(s) : |
p. 20-21 |
Langues : |
Anglais (eng) |
Catégories : |
Automatisation Cuirs et peaux Cuirs et peaux -- Défauts Détection de défauts (Ingénierie) Etalonnage Qualité -- Contrôle Traçabilité
|
Index. décimale : |
675 Technologie du cuir et de la fourrure |
Résumé : |
Mindhive is a tech company in New Zealand that discovered the power of AI in detecting defects in leather hides seven years ago. Its Model V Grading is flow quickly growing in popularity among tanneries as well as shoe and automotive manufacturers. Industry requests have since led to the company also developing a robust traceability solution that is deployable in tanneries of any size. This enables tanners to achieve a key sustainability goal. But Leathertracer, as the solution is called, has another significant advantage. Mindhive's CEO Neil Martin explains its impact. |
Note de contenu : |
- Many tanneries have played with various approaches to achieve traceability. Some use a documented system; others are experimenting with tattooed ID's. What makes Mindhive's Leathertracer unique ?
- What about your other solution, Model V Grading: artificial intelligence to detect defects? How can you guarantee this solution could do as good a job as a 'master grader' with 30+ years' experience ?
- Ok, but artificial intelligence is a very new, expensive technology. How can tanners deploy this as a commercially advantageous business case for their tannery ?
- And what is the benefit of deploying both solutions together ?
- What were the responses and uptake of these solutions to date ? |
En ligne : |
https://drive.google.com/file/d/1JE0HkhbbJuzklQWupDzzCR_c9Dc787RA/view?usp=drive [...] |
Format de la ressource électronique : |
Pdf |
Permalink : |
https://e-campus.itech.fr/pmb/opac_css/index.php?lvl=notice_display&id=36189 |
in INTERNATIONAL LEATHER MAKER (ILM) > N° 49 (09-10/2021) . - p. 20-21