Cognitive Agent for the Quality Management in Flexographic Printing on Packages

Abstract

The aim of the chapter is to develop an approach for improving quality management in flexographic printing on packages using cognitive agent. A hybrid agents' architecture based on the learning intelligent distribution agent architecture (LIDA) and hierarchical temporal memory has been developed. Such approach has not been developed before; therefore, it is the main contribution of this chapter. The first part of the chapter presents the introduction to the research problem and background. Next, research methodology and the LIDA cognitive agents have been described. The main part of chapter presents the cognitive agent's architecture and functionality related to quality management in flexographic printing. The last part presents discussion, future works, and major conclusions.

Lessons Learned from Developing an Industry 4.0 Mobile Process Management System Supported by Artificial Intelligence

“…• building the awareness of employees that their actions, directly related to production processes, have a significant impact on their safety; • building the employees' awareness that their activities, directly connected with production processes, have a significant impact on environment health and safety (EHS) (Thibaud et al, 2018), physical infrastructure, the manufactured products quality, as well as labour costs (direct and indirect), customer relations, and finally, on company revenue. The scope of the project falls into the smart factory domain, thus following the modern trend of automation and data exchange in manufacturing technologies, including cyber-physical systems (Lee, 2008), cloud (O'Donovan, Gallagher, Leahy, andO'Sullivan, 2019) and cognitive computing (Janus et al, 2021), and the Internet of Things (Bytniewski, Matouk, Rot, Hernes, and Kozina, 2020).…”