Faunhofer Project Center for Production Management and Informatics PMI

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  • Publication
    Robust production planning and control for multi-stage systems with flexible final assembly lines
    ( 2017)
    Gyulai, D.
    ;
    Pfeiffer, A.
    ;
    Monostori, L.
    Production planning of final assembly systems is a challenging task, as the often fluctuating order volumes require flexible solutions. Besides, the calculated plans need to be robust against the process-level disturbances and stochastic nature of some parameters like manual processing times or machine availability. In the paper, a simulation-based optimisation method is proposed that utilises lower level shop floor data to calculate robust production plans for final assembly lines of a flexible, multi-stage production system. In order to minimise the idle times when executing the plans, the capacity control that specifies the proper operatorâtask assignments is also determined. The analysed multi-stage system is operated with a pull strategy, which means that the production at the final assembly lines generates demands for the preceding stages providing the assembled components.
  • Publication
    Manufacturing lead time estimation with the combination of simulation and statistical learning methods
    ( 2016)
    Pfeiffer, A.
    ;
    Gyulai, D.
    ;
    Kádár, B.
    ;
    Monostori, L.
    In the paper, a novel method is introduced for selecting tuning parameters improving accuracy and robustness for multi-model based prediction of manufacturing lead times. Prediction is made by setting up models using statistical learning methods (multivariate regression); trained, validated and tested on log data gathered by manufacturing execution systems (MES). Relevant features, i.e.; the predictors most contributing to the response, are selected from a wider range of system parameters. The proposed method is tested on data provided by a discrete event simulation model (as a part of a simulation-based prediction framework) of a small-sized flow-shop system. Accordingly, log data are generated by simulation experiments, substituting the function of a MES system, while considering several different system settings (e.g.; job arrival rate, test rejection rate).
  • Publication
    Simulation-based production planning and execution control for reconfigurable assembly cells
    ( 2016)
    Gyulai, D.
    ;
    Pfeiffer, A.
    ;
    Kádár, B.
    ;
    Monostori, L.
    In order to meet the continuously changing market conditions and achieve economy of scale, a current trend in the automotive industry is the application of modular reconfigurable assembly systems. Although they offer efficient solution to meet the customers needs, the management of these systems is often a challenging issue, as the continuous advance in the assembly technology introduces new requirements in production planning and control activities. In the paper, a novel approach is introduced that enables the faster introduction of modular assembly cells in the daily production by offering a flexible platform for evaluating the system performance considering dynamic logistics and production environment. The method is aimed at evaluating different modular cell configurations with discrete-event simulation, applying automated model building and centralized simulation model control. Besides, the simulation is linked with the production and capacity planning model of the system in order to implement a cyclic workflow to plan the production and evaluate the system performance in a proactive way, before releasing the plan to the production. The method and the implemented workflow are evaluated within a real case study from the automotive industry.
  • Publication
    Milkrun vehicle routing approach for shop-floor logistics
    ( 2013)
    Gyulai, D.
    ;
    Pfeiffer, A.
    ;
    Sobottka, T.
    ;
    Váncza, J.
    In large-scale shop floors and manufacturing environment, different transportation systems are applied in order to satisfy the material requirements of the systems. The limited capacity of vehicles and time consumption of the logistics processes require effective vehicle routing approaches so as to support production without glitches. The paper gives an overview of the appropriate models and the most efficient solver algorithms of the vehicle routing problem (VRP), introduces a novel approach that uses a novel initial solution generation heuristics, and presents a local search method to solve the VRP. In order to demonstrate the capabilities of the solution proposed, the implemented software concentrates on the main industrial requirements like quick response, effective layout definition and order handling. A specific layout representation scheme is proposed which ensures interoperability between different factory-, and shop-floor planning software products.