adidas has been granted a patent for a method of estimating a physical property associated with a region of a sports article. The method involves determining structural features within the region, assigning feature values to each structural feature, mapping these values to a physical property using a machine learning algorithm, and using the mapping to estimate the physical property for the region. The physical property in this case is the printability of the structural feature. GlobalData’s report on adidas gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Smarter leaders trust GlobalData
According to GlobalData’s company profile on adidas, footwear 3D Printing was a key innovation area identified from patents. adidas's grant share as of September 2023 was 70%. Grant share is based on the ratio of number of grants to total number of patents.
Estimating printability of structural features in a sports article
A recently granted patent (Publication Number: US11763144B2) describes a method for estimating a physical property associated with a region of a sports article, such as a shoe. The method involves determining structural features within the region and assigning feature values to each structural feature based on the distribution of material within the region. These feature values are then mapped to a physical property using a machine learning algorithm trained on a limited number of samples. The physical property in this case is the printability of the structural feature. The mapping is used to estimate the physical property for the entire region.
The patent claims also include various additional features and variations of the method. For example, the region can be divided into sub-regions, which can be voxels or pixels that further subdivide the region. Each sub-region is associated with a feature value based on the amount of material present. The mapping can be based on different machine learning algorithms, including artificial neural networks such as convolutional neural networks. The association between feature values and physical property values can be obtained using a finite element method.
The patent also covers the application of the method to specific parts of a sports article, such as the midsole or upper of a shoe. In these cases, the region of interest is subdivided into voxels or pixels, and at least one structural feature is associated with each voxel or pixel. The physical property can include elasticity, stiffness, and shearing resistance of the structural feature.
Furthermore, the patent describes a method of manufacturing a part of a sports article using the estimated physical property. The method involves optimizing the physical property based on the estimate and considering structural constraints for the part. The manufacturing process can include additive manufacturing or placing patches on a blank.
Overall, this granted patent presents a method for estimating physical properties of structural features in sports articles, particularly shoes, using machine learning algorithms and considering material distributions within the regions of interest. The method has potential applications in optimizing the design and manufacturing of sports articles based on desired physical properties.
To know more about GlobalData’s detailed insights on adidas, buy the report here.
Data Insights
From
The gold standard of business intelligence.
Blending expert knowledge with cutting-edge technology, GlobalData’s unrivalled proprietary data will enable you to decode what’s happening in your market. You can make better informed decisions and gain a future-proof advantage over your competitors.
GlobalData, the leading provider of industry intelligence, provided the underlying data, research, and analysis used to produce this article.
GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
