The ‘K-AI Manufacturing Data Analysis Competition (Data)’, held for the second time this year following last year, was ready to suggest ways to improve the added value of companies by discovering ways to use manufacturing data (data) in real business sites . .
This K-AI manufacturing data (data) analysis competition is registered on the ‘KAMP’ website (portal) (www.kamp-AI.kr), a platform for using manufacturing data (data) for small enterprise companies and medium. Based on the standard model (model) of melting tank manufacturing field data (data), ideas (ideas) that can improve the working environment of food processing companies were recruited.
This year’s competition was supported by a total of 153 groups (teams) of different participants (teams) from companies, universities, and graduate schools across the country through a competition last October, and based on analysis (data) manufacturing (data), defect prediction and quality Different ideas (ideas) were presented, such as forecasting, process quality control, and operation optimization measures.
In particular, the 8 groups (teams) that reached the final round after going through a written evaluation performed presentations and Q&A through their virtual alter egos (avatars) in the evaluation center prepared in the expanded virtual world space (Metaverse) Applicability and scalability of the analysis model (model) have been comprehensively evaluated.
Through this evaluation in the extended virtual world space (metaverse), it was possible to confirm the purpose of the competition, which is to present innovative methods through the convergence of various new technologies.
Joe (team) from ‘DataIntelligenceLAB (Chung-Ang University)’, which received the Minister’s Award for Small and Medium Enterprises and Start-Ups (Grand Prize), predicts the time that faults will occur with a fault detection algorithm based on semi-supervised learning that can be expanded to different scenarios (scenarios) Guidelines (guidelines) and operation optimization scripts (scenarios) were drawn up to enable a pre-emptive response.
This was highly evaluated by the judges as the analysis model (model) was varied, and the validity of the analysis process and the excellence of the result interpretation were recognised.
In addition, in this ‘2nd Artificial Intelligence (Data) Manufacturing Data Analysis K-Competition’, an innovation business model (business) (model) was carried out by promoting the servitization of products based on manufacturing data (data) together with the ‘Competition Servitization based on manufacturing data (data)’.
The aim of the ‘Service Competition’ is to analyze and use manufacturing data (data) not only to solve problems and increase productivity in manufacturing companies, but also to increase sales and profits of companies by expanding new business models (models). in the sense that it shows the possibility of continuing, and a total of four groups (teams) who presented excellent models (models) were awarded.
The Minister of Small and Medium Businesses and Startups Award (Grand Prize) was awarded to IT Space Co., Ltd., which proposed a predictive maintenance intelligent factory (smart factory) using human voice and machine-specific sound waves (waves).
Lim Jung-wook, head of the Startup Enterprise Innovation Office at the Ministry of Small and Medium Enterprises and Startups, said, “A new model (model) that can be expanded through various artificial intelligence analysis models (models) and data (data) that is relevant to manufacturing companies in the competition and contest using manufacturing data (data). ),” he said.
In addition, he said, “The Ministry of Small and Medium Businesses and Startups will continue to expand the base (infrastructure) for the analysis and use of various data (data).”
He added, “I would like to ask for a lot of interest in the innovation of small and medium-sized manufacturing companies, such as related industries, companies, and universities, and the analysis and use of data (data).
