This presentation was made at the 2019 NAFEMS World Congress in Quebec Canada
This paper presents the growing importance of data in the engineering process of designing a sports product. It describes how the international sports company Decathlon developed an augmented engineering methodology to efficiently improve the engineering process.
Decathlon’s goal is to make the pleasure and benefits of sport accessible to all. As a consequence, our objective is to know our customers’ needs and to design the most adapted product for everyone. Such an adapted product offers the right level of performance, cost, quality and development time.
Companies involved in sports design and manufacturing require fast innovations to remain competitive in the sports business. To achieve this, Decathlon is using simulation extensively to deliver continuous performance improvements, ensure safety and reliability and minimise engineering and manufacturing costs.
Simulation is working well but our goal is to make product design easier, faster and really smart. So we have decided to implement in-house design tools that are able to quickly generate regular design. These tools are based on design rules developed by our team trough R&D studies, using the correlation between use feelings and technical performance of a product. This knowledge uses data mining to enable a link between a product technical database and a use test database. It comprises a full range of numerical tools, from traditional finite element analysis to internal specific simulation tools. As a result, predictive models of subjective use feelings are established and linked to the technical behaviour of the product.
Once we have developed knowledge of the design rules, we implement it in our tools. To support our in-house design tools, we set up a web platform to host and share engineering knowledge and a design interface (internally called ‘Design Application Store’). It is worldwide easily accessible and user-friendly, which is enabling our development team to be autonomous in optimising the product, making product design easier and accelerating bringing it to market. It also capitalises on product knowledge. These smart-engineering tools generate regular design quickly, so teams can focus on innovation.
As it has full interoperability with other tools of our company, we connect it with internal and external data. On a specific product, we are able to collect and enrich design data with a wide range of data: we are able to aggregate engineering data (simulation results, laboratory results, material database), production data (costs, quality, environmental impact), but also retail data (product reviews, selling price, product return) and so on. This data aggregation lets us improve the design experience by qualifying the good design regarding multiple complex parameters.
We are now developing a 3D automatic product configurator for every piece of sports equipment, usable by each designer (product engineer, product manager, R&D engineer, user). These have the rudiments of the co-design, customisation, automatic improvement and auto-adaptation of products.
Design has historically always involved a compromise among cost, performance and quality. Now it is possible to take into account a growing number of new parameters. Augmented engineering makes it possible to intelligently trade between these huge numbers of different objectives to deliver a product that better meets Decathlon customers’ needs at a lower cost.
|Date||18th June 2019|