Conflict-Receptive and Prognosis Scheduling in Deep Learning Systems

Abstract

In Manufacturing Industry, the main process involved are product design, prototype, product testing and then finally mass production is instantiated. So, most of the manufacturing industries and their production processes are static where the process is not flexible enough to handle sudden changes in production mechanism. In our case, consider the electronic manufacturing industry they undergo through the same phase where they are not capable of sudden changes in the production process, sudden changes in the sense where manufacturing company must analyze on demand products then try to satisfy the customer demand. In previous model static manufacturing process is handled by using FIFO algorithm which helps to schedule the process, in which the process arrives first will be executed first and it is a non-pre-emptive type of scheduling algorithm. The existing is not suitable to solve a dynamic manufacturing process where the scheduling should also be dynamic according to the priority. So, we proposed a Priority scheduling algorithm, and it is pre-emptive type, eventually based on scheduling, our proposed algorithm helps to schedule any process depending upon the priority. The proposed algorithm helps to schedule and also it dynamically change the process depending on the products priority, where one process may have to stop so the process of priority products can be initiated. By achieving the dynamic manufacturing process any business can be developed as they can satisfy the on-demand nature and their new product production process concurrently.