Browsing by Author "Snyman, Stephan"

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    Design and development of a real-time scheduling system in a sensorised job shop using cloud-based simulation with mobile device access
    (Stellenbosch : Stellenbosch University, 2019-12) Snyman, Stephan; Bekker, James F.; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: Traditional scheduling approaches used in manufacturing systems address scheduling problems before production commences, which poses possible problems when the system is interrupted by unexpected events. Managers must then react in a timely fashion, by developing a new or revised schedule to mitigate the effects of the interruptions on the productivity of the system. This can be done by a real-time scheduling system, which is used in conjunction with the actual manufacturing system. Technological advances, including cloud-based computing, the omnipresence of mobile devices, and the improved capabilities of sensor networks, have opened up the opportunity to design a real-time scheduling system, as well as create software architectures to support such a system. The purpose of this research project is therefore to develop a prototype of a real-time simulation scheduling system, which will serve as a decision support tool for real-time rescheduling of machine steps in a job shop. The prototype incorporates a cloud-based information system for the storage of data and a cloud-based simulation scheduler that generates schedules. It also includes web pages for logging data changes and selecting a new schedule and sensors that keep track of the movement of jobs through the job shop. The preliminary test results of the developed simulation scheduler suggest that metaheuristics should be considered to generate schedules, due to the metaheuristics outperforming the common dispatching rules. The model was then expanded from the single-objective to the multi-objective domain, which is a better representation of the real-world job shop environment. Several metaheuristics were adapted to solve the bi-objective job shop scheduling problem, after which comparison tests were conducted. The tests revealed that the NSGAII performed best of all the metaheuristics and it was selected for further implementation. The final phase of this research project was to implement a newly developed ranking and selection procedure for discrete stochastic simulation problems, called MMY. The MMY procedure finds the minimum number of simulation replications for each solution, while guaranteeing that the probability of correct selection of the best solutions exceeds a desired value. In this study, MMY finds the best simulated schedules while the probability of correct selection is guaranteed.
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    Real-time scheduling in a sensorised factory using cloud-based simulation with mobile device access
    (Southern African Institute for Industrial Engineering, 2017) Snyman, Stephan; Bekker, James
    ENGLISH ABSTRACT: Scheduling is a challenge that persists in the operational phase of the manufacturing life-cycle. The challenge can be attributed to the complex, dynamic, and stochastic nature of a manufacturing system. Computer simulation is often used to assist with scheduling, as it can sufficiently mimic complex, discrete, dynamic, stochastic processes. We propose an architecture of a real-time simulation scheduling system that incorporates the use of a sensorised-network of a job-shop, mobile devices, and cloud computing with simulation and scheduling methods. A simulation model is also created to describe the environment and operations of a job-shop.
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    A real-time scheduling system for a sensorised job shop using cloud-based simulation with mobile device access
    (South African Institute for Industrial Engineering, 2018) Snyman, Stephan; Bekker, James; Botha, John-Pieter
    Scheduling is a challenge that continues to trouble management of the operational phase of the manufacturing life cycle and can be attributed to the complex, dynamic and stochastic nature of a manufacturing system. Computer simulation is often used to assist with scheduling, as it can sufficiently mimic complex, discrete, dynamic, stochastic processes. We propose and develop a prototype real-time simulation scheduling system for a sensorised factory, which is to serve as a decision support tool for real-time rescheduling of machine steps in a job shop.