ndustrial Internet of Things (IIoT) Based Job Shop Scheduler Monitoring System

Abstract

The manufacturing industry has now started the 4th revolution; also referred to as Industry 4.0, powered by the Industrial Internet of Things (IIoT) technology. In this context factories are now being transformed into smart industries by automation of the Shop Floors. Automation comprises of scheduling and monitoring cycles. To implement the true essence of Industry 4.0, a number of different techniques have been applied to schedule the shop floor tasks, while a gap persists in monitoring the job shop scheduler. The aim is to present an optimized IIoT based Job Shop Scheduler Monitoring System that tracks the tasks being performed by the machines, thus completing the closed loop feedback path, enabling automatic detection of completion time of a job and based on that, dynamic rescheduling. The task being performed by the machines on the shop floor are monitored in real time making current profiles via industrial current sensors network. These current profiles are compared with all the current profiles already stored in the database providing a vivid picture of the lead or lag in the tasks being performed, judged by the current variations. This novel automation improves the efficiency of the whole shop floor and ultimately resulting in the optimal management of the resources and time at enterprise level. The monitoring system was tested in an actual shop floor setting and results verify the practicability in improving performance of the shop floor.