Now showing 1 - 10 of 12
  • Publication
    Scheduling and Operator Control in Reconfigurable Assembly Systems
    ( 2017)
    Gyulai, D.
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    Kádár, B.
    ;
    Monostori, L.
    Pushed by the recent market trends, companies need to adapt to changeable demands, regarding both mix and volume, in order to keep their competitiveness. Modular and reconfigurable assembly systems offer an efficient solution to these changes, providing economies of scale and also economies of scope. In the previous works of the authors, novel methods were presented to solve strategic level system configuration, and tactical mid-term production planning problems related to modular, reconfigurable assembly systems. The paper relies on these results, and aims at extending the previously proposed planning hierarchy on the short-term, daily production scheduling. The objective is to minimize the total operator headcount, considering the production lot sizes calculated on a higher, planning level on a working shift basis. The analyzed scheduling problem requires novel models, as important constraints in the scheduling problem are the reconfigurations consuming time as well a s resources. In the paper, constraint programming and metaheuristics models are formulated and compared, resulting in production schedules that specify the production sequences, and the operator allocations. Conclusively, the operator controls can be also obtained from the results, specifying a work plan and tasks for a given operator within a working shift. The proposed methods are compared by using real industrial problem instances.
  • Publication
    Performance measurement in flow lines â Key to performance improvement
    ( 2016)
    Stricker, N.
    ;
    Pfeiffer, A.
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    Moser, E.
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    Kádár, B.
    ;
    Lanza, G.
    Key Performance Indicators (KPIs) are frequently used for measuring a production systemsâ performance. The selection of KPIs should lead to a set being as small as possible but taking into account all relevant aspects of the system. This paper provides an analytical approach to determine the set of relevant KPIs for specific production lines, allowing for a transparent and complete performance measurement. An LP was formulated for the proposed KPI model and a significant reduction of the number of KPIs used could be realized. The analytical model was tested in a real industrial application.
  • Publication
    Simulation-based production planning and execution control for reconfigurable assembly cells
    ( 2016)
    Gyulai, D.
    ;
    Pfeiffer, A.
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    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
    Simulation support in construction uncertainty management: A production modelling approach
    ( 2016)
    Pfeiffer, A.
    ;
    Kádár, B.
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    Bohács, G.
    ;
    Gáspár, D.
    The execution of construction projects such as a highway construction or the elevation of a new bridge is a complex, highly equipment-intensive process and are subject to many different uncertainties. This is very similar to the manufacturing execution level in production systems where predefined productions plans and schedules cannot be completely implemented due to unexpected internal and external changes and disturbances. Following this analogy, the paper proposes the application of a discrete-event simulation based method which was already applied in the decision-support for manufacturing control to develop the decision-support in the execution of a construction project where the effects of the deviation from the short-term schedule can be easily and quickly analyzed.
  • Publication
    Manufacturing lead time estimation with the combination of simulation and statistical learning methods
    ( 2016)
    Pfeiffer, A.
    ;
    Gyulai, D.
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    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
    Robust production planning and capacity control for flexible assembly lines
    ( 2015)
    Gyulai, D.
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    Kádár, B.
    ;
    Monosotori, L.
    The frequently changing order stream and high product variety require robust planning and control approaches, as well as a flexible system structure in order to fulfill the highest possible customer service level and to keep the production costs on a reasonable level. In the paper, a combined production planning and capacity control method for assembly lines is proposed aiming at balancing the workload of the human operators and decreasing the overall production costs on a given time horizon. Instead of using the idealistic cycle times and simple manufacturing control rules, the proposed planning and control methodology is based on adaptive calculations taken from continuously updated historical production data. The manufacturing execution-level data is applied for building regression models predicting the capacity requirements of the future production scenarios. Besides, the historical data is also used as direct input of discrete-event simulations, to determine the proper control policies of human operator allocations for the different scenarios mentioned above. In order to calculate reliable and feasible production plans, the regression models and control policies are integrated in a mathematical programming model that minimizes a cost function representing the total production costs.
  • Publication
    Supporting multi-level and robust production planning and execution
    ( 2015)
    Stricker, N.
    ;
    Pfeiffer, A.
    ;
    Moser, E.
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    Kádár, B.
    ;
    Lanza, G.
    ;
    Monostori, L.
    Operating current production systems influenced by the factors of increasing dynamics and volatility poses a need for robustness. Among different enablers for robustness the appropriate ones for specific production systems have to be identified and evaluated. In this cooperative paper multi-objective decision support models will be presented evaluating the best enablers for the levels of production network, plant and shop-floor. The suggested models for the stabilization of the production system's performance under volatile environment use analytical and simulation based approaches on the regarded levels.
  • Publication
    Capacity planning and resource allocation in assembly systems consisting of dedicated and reconfigurable lines
    ( 2014)
    Gyulai, D.
    ;
    Kádár, B.
    ;
    Monostori, L.
    Companies with diverse product portfolio often face capacity planning problems due to the diversity of the products and the fluctuation of the order stream. High volume products can be produced cost-efficiently in dedicated assembly lines, but the assembly of low-volume products in such lines involves high idle times and operation costs. Reconfigurable assembly lines offer reasonable solution for the problem; however, it is still complicated to identify the set of products which are worth to assemble in such a line instead of dedicated ones. In the paper a novel method is introduced that supports the long-term decision to relocate the assembly of a product with decreasing demand from a dedicated to a reconfigurable line, based on the calculated investment and operational costs. In order to handle the complex aspects of the planning problem a new approach is proposed that combines discrete-event simulation and machine learning techniques. The feasibility of the approach is demonstrated through the results of an industrial case study.
  • Publication
    Semantic virtual factory supporting interoperable modelling and evaluation of production systems
    ( 2013)
    Kádár, B.
    ;
    Terkaj, W.
    ;
    Sacco, M.
    Modelling, simulation and evaluation of manufacturing systems are relevant activities that may strongly impact on the competitiveness of production enterprises both during the design and the operational phases. This paper addresses the application of a semantic data model for virtual factories to support the design and the performance evaluation of manufacturing systems, while exploiting the interoperability between various Digital Enterprise Technology tools. The paper shows how a shared ontology-based framework can be used to generate consistent 3D virtual environments and discrete event simulation models, demonstrating this way how the proposed solution can provide an interoperable backbone for heterogeneous software tools.
  • Publication
    Execution data connected simulation for production operation planning and control
    ( 2012)
    Kádár, B.
    ;
    Pfeiffer, A.
    ;
    Monostori, L.
    Due to the large number of the resources, the frequent reengineering of manufacturing processes and the often changing product types, the maintenance of the simulation model and the provision of up-to-date input data are almost always difficult. The paper introduces new quantitative analysis method including processing time and batch calculation algorithms applied in the automatic building of discrete-event simulation systems. The simulation model and the mentioned algorithms are both directly interfaced with real execution databases and the overall solution supports the shop-floor managers in making control decisions. The applicability of the elaborated approach is illustrated by the results of experiments relying on real historical data.