In this research, Industrial Artificial Intelligence (IAI) is discussed as the most promising technology for enabling and realization of the next industrial revolution. The key enablers for this transformative technology along with their significant advantages are discussed. In addition, this research explains “Lighthouse Factories” as an emerging status applying to the top manufacturers that have implemented IAI in their manufacturing ecosystem and gained significant financial benefits. It is believed that this research will work as a guideline and roadmap for researchers and industries towards the real world implementation of IAI. // Please use this for citation: "Jay Lee, Jaskaran Singh, Moslem Azamfar. Industrial AI: Is It Manufacturing’s Guiding Light? Manufacturing leadership Journal. 2019:26–36. doi:10.7945/tt9s-gz25."
Cyber-Physical Production Systems (CPPSs) are complex manufacturing systems which aim to integrate and synchronize machine world and manufacturing facility to the cyber computational space. However, having intensive interconnectivity and a computational platform is crucial for real-world implementation of CPPSs. In this paper, the potential impacts of blockchain technology in development and realization of real-world CPPSs are discussed. A unified three-level blockchain architecture is proposed as a guideline for researchers and industries to clearly identify the potentials of blockchain and adapt, develop, and incorporate this technology with their manufacturing developments towards Industry 4.0.
Produced almost entirely at Experimental Television Center (ETC), the video uses a simple animation of a rotating rectangle (produced in Deluxe Paint on the Amiga Computer) as a stencil into which are keyed various versions of a processed live image of the river outside the window at ETC. This was my second attempt at a multi channel piece. The four programs have been shown in grid’s of twelve and sixteen monitors. While relatively simple in structure and shown only three times, this remains a personal favorite.