Artificial Intelligence software;
What is DecoFinder What does it do?
DECOFINDER is an artificial intelligence (AI) based, practically convenient, digital chipboard appearance matching software.
Send scan
Let DecoFinder find it!
We Send It To You
WHAT IS DECOFINDER
Edgebands require to complement chipboard appearance. There is an ongoing difficulty in every phase of edgeband matching. Genuine chipboard samples must be shipped for an edge band to be designed. Then, edge band samples are returned. Occasionally, the transfers repeated a few times and cause delays in the production.
Matching the appearance is not straightforward. Therefore, mismatches are common. Edge band appearance must be in the correct color and texture as well as it must fit in all scales and angles. A master design that matches the chipboard requires some days, which costs valuable time and manpower. A mismatching edge band either requires another master design or, in case it is used, reduces the overall quality of the produced furniture.
Experienced and qualified experts are necessary to design a master sample. Expert must have wide knowledge of the producers inventory to initiate the process with a similar-looking edge band. It is not rare that a clone master is redesigned when the expert overlooks the inventory. Several molds, patterns, colors, techniques must be easily accessible during master making. Even in this case, the expert cast away considerable amount of raw materials, chemicals and most importantly time.
Conventional design approach consumes time and resources at each phase, might decrease the expected quality of the final product, directly or indirectly harms the environment.
“DECOFINDER is the solution”
DECOFINDER is an artificial intelligence (AI) based, practically convenient, digital chipboard appearance matching software. DECOFINDER AI engine knows the common shapes of the nature. Millions of natural visuals from daily life is wired into its AI engine. This is realized through a technique called “transfer learning”. Therefore, years of accumulated experience of AI on recognizing shapes could be reused in DECOFINDER. Additionally, thousands of chipboards and respective edge bands are included. “Siamese network” is employed, where twin AI engines handle respective surfaces of a chipboard and an edge band, to determine the similarities and differences.
Therefore, given a set of edge bands from the inventory, DECOFINDER could locate the best candidates in less than a second.
DECOFINDER is framed with a intuitive user interface.Users could include recent chipboards and edge bands, also include their own inventory to be matched.
DECOFINDER is a novel game changer with sevral contributions to efficiency of the business and resource savings.The most apaprent contribution is the dramatic decrease of initial production time.The edge band producers could propose a set of possible matches to their customers in minutes. Even though the proposals are not suitable, it provides a reference point to speed up negotiation.
DECOFINDER eliminates neverending, time consuming sample postings. All the time, packaging, transportation costs and pollution are recovered. In the best case scenario, DECOFINDER enables single delivery after production. The advantage is obvious, especially during freight crisis times.
DECOFINDER prevents the producer to duplicate an existing master. It seek for matches in a second in an inventory of ten thousand masters. Extensively reduces time to be spent in the inventory, as well as releases the dependency of experiences workers.
The near-miss proposals by DECOFINDER navigates the master making expert to a more suitable initial recipe. Therefore, even it could not match an existing edge band, it reduces the initial time of master making to hours instead of days. Eliminating duplicate production reduces archived resurces such as moulds, textures, color sets. Additionally, storehouse space is saved as duplicate products will not occur.Hopefully, as DECOFINDER becomes widespread, edge band appearance standardization could be possible.