Predictive Methodology for Dimensional Path Precision in Robotic Machining Operations

Iglesias, I.; Ares, E.; González-Gaya, Cristina; Morales, Francisco J.; Rosales, Virginia

doi:10.1109/access.2018.2868549

Cited by 8 publications

(8 citation statements)

References 10 publications

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“…PREMET, the predictive methodology developed by I. Iglesias et al [34], has been validated and can be applied in any six degrees of freedom industrial robot to calculate the path deviations of the machining tool, and it is used in this factorial procedure to predict the simulated path deviation.…”

Section: Phase 2: Methodology Applied For Determination Of the Simulamentioning

confidence: 99%

“…[31][32][33]. Among the most notable advances, we must highlight the machining tool path deviation predictive methodology (PREMET) developed by I. Iglesias et al [34] in which the robot's structural dynamics are reduced to the cutting Tool's Center Point (TCP) to evaluate and compare the deviations between different robot structural configurations in order to select the lowest deviation of the cutting path. PREMET has been applied for the case of the grooving operation in soft materials and the errors obtained are smaller than 12%.…”

Section: Introductionmentioning

confidence: 99%

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A New Approach to the Consideration and Analysis of Critical Factors in Robotic Machining

et al. 2020

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The relative low stiffness of industrial robots is a major limitation on the development of flexible and reconfigurable systems in applications in which process forces and vibration lead into significant tool path deviations with respect to the programmed path as in the case of robotic machining. This paper presents a novel factorial procedure that allows for the preliminary study of the main conditions in robotic machining operations and it determines the critical factors that are affecting the machining path of any robotic cell in order to obtain the process conditions with lower path deviations. In this procedure the most influential robotic machining constraints were identified and classified, the factorial design of experiments was used to enable the execution of the experimental tests and the machining tool path deviation predictive methodology (PREMET) was used to determine the cutting tool path deviation between the programmed and the experimental path as a function of the process variables. Experimental trials have been carried out in order to determine the main factors that affect the robotic machining and influence the main constraints of the process, showing a reduction greater than a 36% of the cutting tool path deviation in groove milling of aluminum. The critical factors identified in order of importance are: hardness of the material, location of the workpiece, orientation of milling head relative to working direction and cutting conditions. This procedure can be extended to future factorial studies to improve the precision of robotic machining (in operations such as face milling, contouring, pocketing) and to establish design criteria for machining robotic cells.

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Section: Phase 2: Methodology Applied For Determination Of the Simulamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Approach to the Consideration and Analysis of Critical Factors in Robotic Machining

et al. 2020

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“…Robotic grinding is an efficient and intelligent machining method for complex components. A robotic grinding cell can be seen in Figure 2 'C' [21]. Researchers in robotic grinding have been concentrating on two extremes, one end has investigated small-scale complex surfaces and the other has targeted efficient grinding of large-scale components [22].…”

Section: Robotic Grindingmentioning

confidence: 99%

Robotic Machining: Status, Challenges and Future Trends

Kiefer,

Luo,

Reimer

et al. 2023

2023 28th International Conference on Automation and Computing (ICAC)

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Robotic machining is considered a viable replacement for large, fixed single-process machines like computer numerical control (CNC) machining and drilling units. Robotic machining is attracting intensive research interests in recent years due to its high efficiency, flexibility, and low cost. However, its industrial adoption is still extremely limited. This paper systematically reviewed the status of major robotic machining processes, including milling, drilling, polishing, and finishing. The key focus was to identify the challenges of robotics machining that derive from low stiffness, poor positional accuracy, and current approaches to over these challenges. The paper concluded with future research trends and the potential of robotic machining.

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“…Furthermore, robots can allow new machining strategies for highly complex parts since they have more degrees of freedom than conventional machine tools. However, one of the substantial limitations that hinder the widespread adoption of industrial robots is their low stiffness, mainly in machining with high material removal rates [1]- [4]. In this context, a significant amount of research on robotic machining has been done over the past decades, and a review of some of those works was presented in [3].…”

Section: Introductionmentioning

confidence: 99%

STEP-NC Architectures for Industrial Robotic Machining: Review, Implementation and Validation

et al. 2020

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In the manufacturing sector, industrial robots are being increasingly improved to execute machining tasks as they exhibit significant advantages in terms of flexibility, cost-effectiveness, affordability, and larger work-space when compared to traditional computer numeric control (CNC) machines. However, programming this kind of equipment for robotic machining is complex, due to closed architecture controller and proprietary programming languages limitations. For that reason, this work aims at contributing to the adoption of the STEP-NC standard (STandard for the Exchange of Product model data-Numerical Control (ISO 10303-238 and ISO 14649)), generating programs for robotic machining operations. The STEP-NC data model enables the integration of information from design, process planning, simulation, manufacturing, and even inspection in a single platform, which could create new alternatives for industrial robotic machining programming. In this context, several previous studies are described in this manuscript aiming to highlight the contribution of this work, in addition to the analysis, implementation, and validation of six different STEP-NC architectures describing the advantages that each architecture provides for achieving robotic machining capabilities. Each introduced architecture can successfully generate a STEP-NC robotic machining program, either as ISO 10303-238 or ISO 14649, which are validated in a simulation environment with both a virtual robot model and a real industrial robot equipped with a LinuxCNC controller. This approach can be implemented in different industrial robots.

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Predictive Methodology for Dimensional Path Precision in Robotic Machining Operations

Cited by 8 publications

References 10 publications

A New Approach to the Consideration and Analysis of Critical Factors in Robotic Machining

A New Approach to the Consideration and Analysis of Critical Factors in Robotic Machining

Robotic Machining: Status, Challenges and Future Trends

STEP-NC Architectures for Industrial Robotic Machining: Review, Implementation and Validation

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