Actual industrial robotic systems offer performance to effectively cope with the requirements in manufacturing dealing with flexibility and quality. Especially in machining application, their known limits in accuracy do not allow extending their field of application to high-accuracy machining, actually covered by state-of-the-art CNC machine tools. Consequently, industrial robots are currently limited to applications with low geometrical accuracies and soft materials. This thesis present an integrated approach to develop a robotic modular workcell with enhanced accuracy for machining, through the full integration of different theoretical models, state-of-the-art technological solutions and manufacturing strategies. In order to compensate for robot errors, several experiments under different conditions that represent a typical set of industrial applications and allow a qualified evaluation are performed. Based on this analysis a modular approach to overcome these obstacles, applied both during program generation (offline) and execution (online), is proposed. Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high dynamic compensation mechanism on piezo-actuator basis. To evaluate the method effectiveness, an experimental campaign has been designed and realized in order to discuss the dimensional and geometrical quality obtained for an automotive part in comparison with quality and costs offered by a standard 5-axis CNC machine tool.
Le prestazioni offerte dai moderni sistemi robotizzati permettono di soddisfare i principali requisiti di flessibilità e qualità nell’ambito delle lavorazioni meccaniche. L’utilizzo di tali sistemi è però limitato da problemi legati all’accuratezza dei robot industriali che non consente l’utilizzo degli stessi nel campo delle lavorazioni ad alta precisione, coperto dalle tradizionali macchine a controllo numerico. Ciò restringe l’applicazione di tali sistemi per applicazioni che richiedono ampi campi di variabilità dimensionale e geometrica. Il presente lavoro di tesi presenta un approccio integrato per lo sviluppo di una cella modulare robotizzata di lavorazione che integra soluzioni tecnologiche allo stato dell’arte, con lo scopo di aumentare l’accuratezza finale sulla parte in lavorazione. La parte iniziale della ricerca ha riguardato l’analisi degli errori attraverso l’esecuzione di vari esperimenti di lavorazione robotizzata. Successivamente è stato sviluppato un approccio progettuale che permette di realizzare una cella modulare attraverso l’integrazione di diverse tecnologie abilitanti che intervengono prima dell’esecuzione del ciclo di lavoro (modalità offline) e in tempo reale (modalità online). La compensazione predittiva offline degli errori del robot è realizzata attraverso il modello cinematico e dinamico del Robot. La compensazione online avviene attraverso un sistema di tracking ottico che permette di misurare la posizione reale del TCP del robot. A questo si aggiunge un sistema di compensazione ad elevata dinamica basato su sensori piezoelettrici. Una successiva campagna sperimentale è stata realizzata al fine di analizzare l’accuratezza dimensionale e geometrica in componenti industriali, prendendo come esempio un componente automotive. Al fine di valutare l’efficacia del metodo proposto, i risultati ottenuti sono stati infine comparati con quelli ottenibili con una componente lavorato con una macchina a controllo numerico standard.
Progettazione Integrata di Sistemi Robotizzati Modulari per l’aumento di Accuratezza nelle Lavorazioni Meccaniche
ANSALONI, Matteo
2014
Abstract
Actual industrial robotic systems offer performance to effectively cope with the requirements in manufacturing dealing with flexibility and quality. Especially in machining application, their known limits in accuracy do not allow extending their field of application to high-accuracy machining, actually covered by state-of-the-art CNC machine tools. Consequently, industrial robots are currently limited to applications with low geometrical accuracies and soft materials. This thesis present an integrated approach to develop a robotic modular workcell with enhanced accuracy for machining, through the full integration of different theoretical models, state-of-the-art technological solutions and manufacturing strategies. In order to compensate for robot errors, several experiments under different conditions that represent a typical set of industrial applications and allow a qualified evaluation are performed. Based on this analysis a modular approach to overcome these obstacles, applied both during program generation (offline) and execution (online), is proposed. Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high dynamic compensation mechanism on piezo-actuator basis. To evaluate the method effectiveness, an experimental campaign has been designed and realized in order to discuss the dimensional and geometrical quality obtained for an automotive part in comparison with quality and costs offered by a standard 5-axis CNC machine tool.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/214697
URN:NBN:IT:UNIMORE-214697