András Pfeiffer

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The paper tackles the problem of managing uncertainties during the execution of predictive schedules in a dynamic environment. The dynamic environment in question is represented by a simulation model which constitutes a coherent part of a Digital Factory solution. The model is connected to an integrated production planner and job-shop scheduler system with(More)
The paper tackles the problem of managing the uncertainties during the execution of predictive schedules in a dynamic environment. The dynamic environment in question is represented by a simulation model – connected to a production scheduler system – with flexible modelling capabilities. The paper addresses the simulation module of the proposed architecture(More)
The paper gives a review of the literature related to the stability measures and describes a new concept with exhaustive simulation results. Predictive production schedules are calculated by a scheduler based on a genetic algorithm, hybridized with a modified Giffler&Thompson algorithm. By applying the proposed scheduler and executing the resulted schedules(More)
The paper presents an integrated production planner and job shop scheduler system with flexible modeling capabilities and powerful, scalable solution methods. The system generates close-to-optimal production and capacity plans on the medium term, and detailed production schedules on the short-term. However, the constraint-based, deterministic scheduling(More)
In the paper, a simulation-based technique is focused on that defines the boundaries and components of a reconfigurable assembly system according to historical order-streams. Fluctuating production volumes and “end-of-life-cycle” products require frequent revisions of the production structure applied, in order to gain production space and to level between(More)
Digital enterprise technologies combined with sophisticated optimization algorithms can significantly contribute to the efficiency of production. The paper introduces a novel approach for integrated production planning and control, with the description of the mathematical models and solution algorithms. The deterministic optimization algorithms are(More)