Scheduling, as a decision-making process, plays a crucial role in manufacturing. Most production systems work in dynamic environments, where disrupting events may result in non-optimality or infeasibilities of the previously defined production schedules. The advent of Cyber Physical Systems (CPS) has brought to higher connectivity and integration of the physical world with the digital world, leading to a higher level of self-awareness and to a new boost in the research interests in reactive scheduling. This work aims at proposing a dynamic scheduling framework based on the tolerance scheduling principle; rescheduling is only triggered in the presence of major disrupting events, accepting a tolerance interval, in order to reduce its frequency. Tolerances for process parameters are defined on the previously selected schedule in order to provide an automated decision-making for triggering the reactive scheduling.

Tolerance Scheduling for CPS

Ragazzini L.;Negri E.;Fumagalli L.;MacChi M.;
2020

Abstract

Scheduling, as a decision-making process, plays a crucial role in manufacturing. Most production systems work in dynamic environments, where disrupting events may result in non-optimality or infeasibilities of the previously defined production schedules. The advent of Cyber Physical Systems (CPS) has brought to higher connectivity and integration of the physical world with the digital world, leading to a higher level of self-awareness and to a new boost in the research interests in reactive scheduling. This work aims at proposing a dynamic scheduling framework based on the tolerance scheduling principle; rescheduling is only triggered in the presence of major disrupting events, accepting a tolerance interval, in order to reduce its frequency. Tolerances for process parameters are defined on the previously selected schedule in order to provide an automated decision-making for triggering the reactive scheduling.
Proceedings - 2020 IEEE Conference on Industrial Cyberphysical Systems, ICPS 2020
978-1-7281-6389-5
CPS
genetic algorithm
reactive scheduling
simulation
tolerance scheduling
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1157321
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