  Industrial Artificial Intelligence (Industrial AI) is an emerging concept
which refers to the application of artificial intelligence to industry.
Industrial AI promises more efficient future industrial control systems.
However, manufacturers and solution partners need to understand how to
implement and integrate an AI model into the existing industrial control
system. A well-trained machine learning (ML) model provides many benefits and
opportunities for industrial control optimization; however, an inferior
Industrial AI design and integration limits the capability of ML models. To
better understand how to develop and integrate trained ML models into the
traditional industrial control system, test the deployed AI control system, and
ultimately outperform traditional systems, manufacturers and their AI solution
partners need to address a number of challenges. Six top challenges, which were
real problems we ran into when deploying Industrial AI, are explored in the
paper. The Petuum Optimum system is used as an example to showcase the
challenges in making and testing AI models, and more importantly, how to
address such challenges in an Industrial AI system.
