Real-time cloud-based stochastic scheduling incorporating mobile clients and a sensor network
Cameron McOnie · SUNScholar (Stellenbosch University) · 2016
ENGLISH ABSTRACT: Scheduling within manufacturing environments is often complicated due to the complex, dynamic and stochastic characteristics such environments exhibit. These characteristics pose problems for off-line scheduling techniques as schedules, initially determined to be acceptable, may degrade or even become infeasible as the state of the system changes. On-line techniques attempt to address this challenge by performing scheduling concurrently with the manufacturing system. By reacting to system disturbances in real-time, on-line schedulers are capable of producing better schedules, or schedule control laws, when compared to off-line techniques. This study proposes a software architecture for a simulation-based reactive scheduling system. The architecture addresses what the main components of a reactive scheduler are and how they are related. Furthermore, it describes each of the components from multiple viewpoints, i.e., logical, process, development, and deployment|predominantly using the unified modelling language. The design decisions used to arrive at architecture qualities such as scalability, modularity, and interoperability are also discussed. Particular attention is given to defining a service contract between the back-end of a reactive scheduling system and data capture and decision support devices located on the shop floor. The proposed architecture is applied through the construction of a simulationbased reactive scheduling system, capable of reacting to real-time disturbances. The base of the system is a simulation model of a pressure gauge assembly operation. Interaction with the simulation model is done through a scheduling application server. The system also comprises of a sensor network prototype, used as means of tracking the movement of work-in-process through the assembly operation; and a mobile client, used to communicate decision support data back to the shop floor. The scheduling application server is deployed to the cloud and is exposed as a Web service for shop floor devices to consume. An experiment that compares the effect of rescheduling using dispatching rules on the system over time is performed. It is shown that as the system state progresses, the recommended dispatching rule may change, and therefore, by embedding the associated control law into the shop floor, would result in an improvement of the manufacturing objective. This experiment illustrates the value of reactive scheduling in the presence of real-time events.