Utilizing edge computing for monitoring plant productivity in print industry

Automated monitoring of a whole production plant, equipped with a variety of different machines is a challenging task. Particular industries are introducing their own XML based schemas to ease the integration process. Print industry attempts to accomplish this with Job Description Format (JDF). However, a number of older print industry machines is rarely ready for such an integration. For integrating a real production plant, here is proposed a novel approach in utilizing a concept from Internet of Things (IoT) called edge computing, to enhance and integrate various printing and finishing equipment status in a unified manner. Edge computing assumes that a lot of processing is on a remote node and that the data is eventually aggregated to another location. For edge nodes small board computers (SBC) with wireless connectivity were used to collect data from machine sensors and store it locally. The data collected on the edge indicates status and operational speed over time of a machine and could be used for various analysis later. Edge node stores all data to a local database that could be accessed remotely or the node could be converted to a JDF compliant producer. The data from edges is then collected to establish a plant wide monitoring system that is a part of management information system. The concept presented here was successfully implemented in a real production environment.