Tekniker explains the application of AI-PROFICIENT technologies to improve Continental tyre manufacturing at a tech event dedicated on Augmented Analytics, on October 26th!
We are happy to announce that our project partner Tekniker will be part of the conference ‘Augmented Analytics: AI, Machine Learning and NLP as a service’ which will be held in San Sebastian, Spain, on October 26th!
In specific, during the session 11.35-12.00, Mrs. Susana Ferreiro, Senior Data Scientist at Tekniker, will elaborate on the AI technologies currently applied at AI-PROFICIENT’s Use Case CONTI-2.
A few words about Use Case CONTI-2
CONTI-2 is a Use Case that takes place in the Continental production line related with the extrusion process, which is not continuous. The need to produce different types of recipes, as well as other scheduled or unplanned repairs and replacements, all lead to successive interruptions and restart of the production line, which are unavoidable, even though they have a negative influence on the quality of the tyre tread. As a consequence of the production stoppage, it is necessary to bring the production line back to the optimal production performance condition, for which adjustments (manual control of set points) are carried out. Until this production-ready point is reached, the tyre tread that is being produced tends to be of low quality and is sent back to the extruders, since it is not useful. The duration of the set-up process determines the amount of rework that is created and brought back to the extruders (a.k.a. reintroduction) in order to not waste the raw materials.
The scope of this Use Case is to create an outcome allowing for a homogeneous assessment of the optimal set of parameters in ‘real time’, which will support a simple decision-making protocol, a clear feedback and finally a higher tread quality. To this direction, AI technologies have been widely adopted and used, to achieve the desired results in an automatic manner independent of the operators’ level of experience or of the recipe complexity. Thus, the Use Case makes combined use of prediction & optimization algorithms, together with advanced HMI mechanisms to interact with humans in order to self-adapt and improve algorithms whose performance make AI technologies as ‘enablers’ for the development of a solution.