TIREBOT: A collaborative robot for the tire workshop

Levratti, Alessio; Riggio, Giuseppe; Fantuzzi, Cesare; Vuono, Antonio De; Secchi, Cristian

doi:10.1016/j.rcim.2018.11.001

Cited by 27 publications

(9 citation statements)

References 9 publications

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“…Also, the authors discuss the concept of collaborative robots or cobots, which assist employees in their work and benefit from a certain level of autonomy to react to the employee's actions (e.g. Fasth-Berglund et al 2016;Levratti et al 2019). Mayr et al (2018) also propose the use of autonomous robots to adjust production planning in real time.…”

Section: Just-in-timementioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

335

205

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Industry 4.0 is increasingly being promoted as the key to improving productivity, promoting economic growth and ensuring the sustainability of manufacturing companies. On the other hand, many companies have already partially or fully implemented principles and tools from the Lean management approach, which is also aimed at improving productivity. While the two approaches use very different strategies, they share some common principles. The objective of this article is to highlight the links between the principles and tools proposed by Industry 4.0 and those proposed by the Lean management approach, with a particular focus on how some of Industry 4.0's technologies are improving the implementation of Lean principles, depending on the technologies' capability levels. As such, this study aims to provide a characterisation of the impacts of Industry 4.0 technologies on Lean principles according to targeted capability levels. The results obtained show strong support for Industry 4.0 technologies for Just-in-time and Jidoka, but little or no support for waste reduction and People and Team work. There is, therefore, a clear need to pursue the deployment of Lean management while improving certain Lean principles using Industry 4.0 technologies.

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Section: Just-in-timementioning

confidence: 99%

Impacts of Industry 4.0 technologies on Lean principles

Rosin

Forget

Lamouri

et al. 2019

International Journal of Production Research

335

205

View full text Add to dashboard Cite

show abstract

“…Además, se muestra que el contagio emocional impacta positivamente en la asignación de tareas y la eficiencia del algoritmo propuesto es competitiva con los métodos más modernos. Los robots colaborativos actualmente se emplean ampliamente en la industria de manufactura, por ejemplo el diseño y control colaborativo de TIREBOT [18], un asistente robótico que ayuda a los operadores de talleres de neumáticos en el proceso de reemplazo de ruedas.…”

Section: Marco Teóricounclassified

Sistema de control cinemático guiado y colaborativo por percepción de las trayectorias de las extremidades superiores

Ibarra-Peñaranda

Duque-Suárez

Duque-Suarez

2021

Aibi revista investig. adm. ing.

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Este proyecto estudia la morfología del brazo humano con la finalidad de construir un robot capaz de imitar los movimientos del mismo, aprenderlos y repetirlos bajo una rutina de control cinemático, para esto fue necesario realizar un aprendizaje de trayectorias, las cuales se obtienen mediante visión artificial haciendo uso del Kinect; del cual se extraen las coordenadas espaciales de cada articulación, y posteriormente se procesan mediante un modelo matemático para obtener las posiciones articulares, calcular el modelo cinemático del robot, y desarrollar una rutina para el control cinemático que establece la relación entre las velocidades de las articulaciones. El sistema le permite al usuario poder iniciar un aprendizaje de sus movimientos, y posteriormente simular dicho aprendizaje en el robot virtual. Así como también activar el robot físico para que realice los movimientos aprendidos. Al comparar los resultados se determinó que la desviación estándar de las trayectorias con y sin control, no cambia en mayor medida; pero los puntos que se encuentran dentro de la desviación en la parte de control son más proporcionales, esto debido a que la estabilidad de las trayectorias mejora al aplicarle el control cinemático.

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“…Reducing the speed of the robot is not always the best solution, especially when the workspace conditions allow the robot to modify the pre-planned path. In [8] the authors exploit the concept of static and kinetostatic danger field on a mobile robot in order to prevent collision with human operators in a tire workshop. In [9] the concept of potential field around the whole robot body is used to generate collision-free trajectory.…”

Section: Introductionmentioning

confidence: 99%

A Safety-Aware Kinodynamic Architecture for Human-Robot Collaboration

Pupa

Arrfou

Andreoni

et al. 2021

IEEE Robot. Autom. Lett.

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The new paradigm of human-robot collaboration has led to the creation of shared work environments in which humans and robots work in close contact with each other. Consequently, the safety regulations have been updated addressing these new scenarios. The mere application of these regulations may lead to a very inefficient behavior of the robot. In order to preserve safety for the human operators and allow the robot to reach a desired configuration in a safe and efficient way, a two layers architecture for trajectory planning and scaling is proposed. The first layer calculates the nominal trajectory and continuously adapts it based on the human behavior. The second layer, which explicitly considers the safety regulations, scales the robot velocity and requests for a new trajectory if the robot speed drops. The proposed architecture is experimentally validated on a Pilz PRBT manipulator.

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TIREBOT: A collaborative robot for the tire workshop

Cited by 27 publications

References 9 publications

Impacts of Industry 4.0 technologies on Lean principles

Impacts of Industry 4.0 technologies on Lean principles

Sistema de control cinemático guiado y colaborativo por percepción de las trayectorias de las extremidades superiores

A Safety-Aware Kinodynamic Architecture for Human-Robot Collaboration

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