IoT Enabled Production Scheduling
DOI:
https://doi.org/10.37591/joprm.v8i3.1479Keywords:
Scheduling, cycle time, priority level, idle time, artificial neural network (ANN)Abstract
In the world of high competition between various firms; it is important that firms plan their production in advance. This will help them maximize the use of available resource and facilities. Production scheduling discusses the process of assigning an order to machines considering the total time available, required time, type of order and to arrange these orders in such way that machine idle time is minimized. By legitimate planning, firms will be able to reduce the overall cost of a product. Many approaches such as demand estimation and mathematical model for scheduling are built in recent times for reducing downtime. In this paper an ANN model is created which predicts the machine on which it should be performed based on quantity, size, the time required and type. Also, an algorithm for arranging these orders in an appropriate way, considering cycle time, priority level so that downtime can be minimized and weekly schedule for each machine can be identified at the beginning of the week.
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