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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, t he constraint-based, deterministic scheduling… (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 sched-uler and executing the resulted… (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 introduces a discrete-event simulation-based decision supporting system aiming at automatically mirroring the current state of a large-scale material handling system of a production system in a digital model and supporting the analysis of diverse control settings and rules. The discrete-event digital model is built in an automated way and all the… (More)
The paper summarizes the main ideas and results for realizing agile manufacturing systems having active disturbance handling approach for real-time manufacturing control. The intelligent integration of information received from production-, quality and process monitoring systems is addressed as the enabler of the approach.
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)