Csaba Kardos

Process planning and offline programming for robotic remote laser welding systems

The paper introduces a complete offline programming toolbox for remote laser welding (RLW) which provides a semi-automated method for computing close-to-optimal robot programs. A workflow is proposed for the complete planning process, and new models and algorithms are presented for solving the optimisation problems related to each step of the workflow: the sequencing of the welding tasks, path planning, workpiece placement, calculation of inverse kinematics and the robot trajectory, as well as for generating the robot program code. The paper summarises the results of an industrial case study on the assembly of a car door using RLW technology, which illustrates the feasibility and the efficiency of the proposed approach.

Applying model-reconstruction by exploring MES and PLC data for simulation support of production systems

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 data necessary for the model are taken from a manufacturing execution system (MES) and additionally directly from programmable logic controllers (PLC). Main focus is given to present the results of the PLC program code processing method (code mapping) generating a structured dataset, as well as the model-reconstruction method for the simulation software. The easy-of-use support tool is intended to be used both in planning and operation phases of an automotive manufacturing company, thus the capabilities of model reconstruction and simulation are tested on real-world data.

Automatic simulation model generation supported by data stored in low level controllers

Abstract One of the most widespread techniques to evaluate various aspects of a manufacturing system is discrete-event simulation (DES). However, building a simulation model of a manufacturing system is a difficult task and needs great resource expenditures. Automated data collection and model buildup can drastically reduce the time of the design phase as well as support model reusability. Since most of the manufacturing systems are controlled by low level controllers (e.g., PLCs, CNCs) they store structure and control logic of the system to be modeled by a DES system. The paper introduces an ongoing research of PLC program processing method for automatic simulation model generation of a conveyor system of a leading automotive factory. Results of the validation process and simulation experiments are also described through a case study.