Abstract
This article took the case of the adoption of a Machine Learning (ML) solution in a steel manufacturing process through a platform provided by a Canadian startup, Canvass Analytics. The content of the paper includes a study around the state of the art of AI/ML adoption in steel manufacturing industries to optimize processes. The work aimed to highlight the opportunities that bring new business models based on AI/ML to improve processes in traditional industries. Methodologically, bibliographic research in the Scopus database was performed to establish the conceptual framework and the state of the art in the steel industry, then the case was presented and analyzed, to finally evaluate the impact of the new business model on the operation of the steel mill. The results of the case highlighted the way the innovative business model, based on a No-Code/Low-Code solution, achieved results in less time than conventional approaches of analytics solutions, and the way it is possible to democratize artificial intelligence and machine learning in traditional industrial environments. This work was focused on opportunities that arise around new business models linked to AI. In addition, the study looked into the framework of the adoption of AI/ML in a traditional industrial environment toward a smart manufacturing approach. The contribution of this article was the proposal of an innovative methodology to put AI/ML in the hands of process operators. It aimed to show how it was possible to achieve better results in a less complex and time-consuming adoption process. The work also highlighted the need for an important quantity of data from the process to approach this kind of solution.
Highlights
This article tackles the opportunities that new business models [1] based on artificial intelligence (AI) can generate to transform traditional factories toward a smarter and more efficient environment, and how people on the shop floor can be empowered by the information these types of solutions produce
The use of machine learning (ML) methods employed alongside domain knowledge of blast furnace spe‐
Thefacilitated case addressed theknowledge adoption of new business model based on AI/ML
Summary
This article tackles the opportunities that new business models [1] based on artificial intelligence (AI) can generate to transform traditional factories toward a smarter and more efficient environment, and how people on the shop floor can be empowered by the information these types of solutions produce. The authors support the conceptual development with many cases from practice, and conclude that the innovative potential of the new business models can give rise to radical new operating models that could lead to firms of a kind not seen before. Another point to address, connected with the subject this article aimed to tackle, was raised by [3] regarding opportunities for the development of smart industries, and their expansion and evolution of production processes. The authors provided an interesting approach to industrial process optimization and smart manufacturing
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