Knowledge-enabled Design of Cooperating Robots Assembly Cells

Papakostas, Nikolaos; Pintzos, George; Matsas, M.; Chryssolouris, George

doi:10.1016/j.procir.2014.10.092

Cited by 12 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Different alternatives regarding positioning and path planning are generated and evaluated based on a manually created initial solution. Papakostas et al (2014) extend the approach by including the selection of resources based on rules and previously used solutions. Pellegrinelli et al (2014) focus on the design of multi-robot cells specifically for spot welding applications.…”

Section: Positioning Of Robotsmentioning

confidence: 99%

Simulation-based layout optimization for multi-station assembly lines

et al. 2021

View full text Add to dashboard Cite

This article presents a novel approach for the automated 3D-layout planning of multi-station assembly lines. The planning method is based on a comprehensive model of the used production resources, including their geometry, kinematic properties, and general characteristics. Different resource types can be included in the planning system. A genetic algorithm generates and optimizes possible layouts for a line. The optimization aims to minimize the line’s area and the costs for assembling the line while simultaneously optimizing the resources’ positioning to perform their tasks. The line’s cycle time is considered as a boundary condition. For the evaluation of different layout alternatives, a multi-body simulation is performed. A parameter study is used to set the algorithm’s parameters. Afterward, the algorithm is applied to three increasingly complex examples to validate and evaluate its functionality. The approach is promising for industrial applications as it allows the integration of various resource types and individualization of the optimization function.

show abstract

Section: Positioning Of Robotsmentioning

confidence: 99%

Simulation-based layout optimization for multi-station assembly lines

et al. 2021

View full text Add to dashboard Cite

show abstract

“…1,19-25. The expert system is a usually pursued by researchers. [26][27][28] In the form of a rule-based model, it allows for the combined use of information pertaining to past engineering projects and capable of generating process design alternatives that take into consideration the performance requirements as well as the constraints and specifications of both robots and parts. Although a few systems support the decisionmaking process related to the manufacturing of products, similar systems, enabling the knowledge management and reuse of assembly processes, are still at infancy state or not used in practice in today's design offices and manufacturing environments.…”

Section: Patterned Layout Optimizationmentioning

confidence: 99%

Challenges and key technologies in robotic cell layout design and optimization

Zhang¹,

Fang²

2016

Proceedings of the Institution of Mechanical Engineers, Part C:

View full text Add to dashboard Cite

Automatic operation system with industrial robots has become more and more popular, especially with the urgent requirement from 3C (Communication, computer and consumer electronics) manufactory. A robot cell, which often involves one or more robots and accessory equipment, can be regarded as part of the larger theme of cellular manufacturing. The objective that most interests manufacturers is the investment return rate. It is largely determined by the productivity of robotic cell, and the leading time of robotic production system. Therefore, a fast and efficient method to design a robotic cell layout with the maximum throughput for a given task is undeniably a worthy research topic. This paper attempts to discuss the challenges and key technologies in the robotic cell layout optimal design. The proper selection of configuration for task, manual operation skill learning and translation, collaborative design tool-chain, optimization in cell layout and operation scheduling, optimal end-of-arm tooling design, and human-robot collaboration are included in this discussion with existing or on-going problem-solving key technologies.

show abstract

“…To decrease programming effort, improve ergonomics, and reduce hazards to the welder, remote welding applications are pursued [1][2][3][4][5][6][7][8][9]. The typical setup consists of a motion input device and a standard industrial robot with a welding torch attached.…”

Section: Introductionmentioning

confidence: 99%

Trajectory Extrapolation for Manual Robot Remote Welding

Ebel¹,

Maaß²,

Zuther³

et al. 2021

Robotics

View full text Add to dashboard Cite

This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve the welder from strain and fatigue. Depending on the sampled hand-motion data, an extrapolation of the given motion patterns is achieved by decomposing the input signals in a linear direction and a periodic motion component. An approach to efficiently determine the periodicity using a sampled autocorrelation function and the subsequent application of parameter identification using a spline function are presented in this paper. The proposed approach is able to resemble all practically relevant motion patterns and has been validated successfully on a remote welding system with limited input space and audio-visual feedback by an experienced welder.

show abstract

Knowledge-enabled Design of Cooperating Robots Assembly Cells

Cited by 12 publications

References 18 publications

Simulation-based layout optimization for multi-station assembly lines

Simulation-based layout optimization for multi-station assembly lines

Challenges and key technologies in robotic cell layout design and optimization

Trajectory Extrapolation for Manual Robot Remote Welding

Contact Info

Product

Resources

About