Intelligent Factory Process Monitoring and Scheduling in Industry 4.0
Lead Research Organisation:
University of Nottingham
Department Name: Faculty of Engineering
Abstract
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Publications
Tochev E
(2018)
A Comparison of Centralised and Decentralised Scheduling Methods Using a Simple Benchmark System
in IFAC-PapersOnLine
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509309/1 | 30/09/2015 | 29/03/2021 | |||
| 1788239 | Studentship | EP/N509309/1 | 30/09/2016 | 03/02/2021 | Emil Tochev |
| Description | I have developed an algorithm for production scheduling in factories with multiple product types. This is based on an existing algorithm that I used in a conference paper which compared different scheduling methods.The algorithm is meant to be easy to understand and implement, and is the basis of a journal paper currently being written. Three variants are presented, to provide schedules for single, serial and parallel machines. To aid understanding, the single machine variant is tutorialised. I have also designed a test bench to simulate a factory machine. This has been used to assess a change point detection algorithm, which can be used to monitor machine health with a minimum amount of setup. I have formulated a second, live change point detection algorithm based on existing literature. It can detect change points in live data and has been tested on the test bench mentioned above. |
| Exploitation Route | The algorithm has been tested against a simple representation of a factory, and has performed better than an approximation of the current factory scheduling system. There is also scope to improve the algorithm by making it more efficient. It can also be expanded to function for a greater variety of machine setups. The change point detection algorithm is intended to be generic enough to be applicable across a range of machines in a factory. The live change point detection algorithm can be used to detect machine faults shortly after they occur. |
| Sectors | Manufacturing including Industrial Biotechology |