Description and modelling of robot-manipulator FANUC M-430iA/4FH

Nikolov, Emil; Nikolova, Nina G.; Georgiev, Metody

doi:10.1088/1757-899x/878/1/012006

Cited by 10 publications

(3 citation statements)

References 3 publications

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“…The results show that it was not possible to attain an angle above 25 • with the current settings at 700 • C . This is due to a pronounced bend rate decay, which is a result of geometrical distortion of the sample [13] and material hardening [14]. Furthermore, the results show that the fastest bend development occurs with a peak temperature of 1300 • C. This is due to the elevated formability and higher gradients at higher temperatures.…”

Section: Bend Anglementioning

confidence: 83%

A Laser Forming Study on Time and Energy Efficiency

Nikolov,

Thomsen,

Kristiansen

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Laser forming is a relatively slow process utilizing temperature differences in the material to cause plastic deformation. The process requires dwell time between laser passes to cool down the material, which results in a slow production rate. Not fully cooling the workpiece has been shown to give a higher bend rate per unit of time. This, coupled with the cooling rate at higher temperatures being more pronounced permits examining the efficiency of laser forming while working in different temperature ranges. The presented work experimentally explores different temperature ranges for AISI 304 from 20 to 1300°C using a thermal camera. Therefore, for each temperature range, the workpiece is heated and cooled to a achieve a constant peak temperature. The purpose is to compare the bend rate per unit of time with different temperature ranges and to examine overall time efficiency. Finally, since different power levels are utilized for each temperature range, the total energy used to achieve each bend will also be investigated. The results show that the increased formability and rate of cooling at higher temperatures increase efficiency in terms of total time. While efficiency in terms of the equipment is higher when allowing the workpiece to fully cool.

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Section: Bend Anglementioning

confidence: 83%

A Laser Forming Study on Time and Energy Efficiency

Nikolov,

Thomsen,

Kristiansen

2023

IOP Conf. Ser.: Mater. Sci. Eng.

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“…M-430iA Robots: The M-430i A is a 2 to 4 kg payload handling robot designed specifically for food or pharmaceutical applications Table 2. On top of that, it has a chemical-resistant surface and a fast, continuous treatment rate 60 .…”

Section: Fig 9: M430i Robotmentioning

confidence: 99%

Untitled

2023

IJPSR

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The rapid development of artificial intelligence (AI) has far-reaching consequences for the global economy. Computers are helping with human input, decisionmaking, and data provision in medicine more than ever before. AI, algorithms, robotics, and big data are all used in today's healthcare sector and the medical profession to derive inferences for monitoring large-scale medical trends and detecting and measuring individual risks and chances based on data-driven estimations. Healthcare is a knowledge-intensive industry that relies heavily on data and analytics to advance treatments and procedures. There has been a significant expansion in the types of medical data gathered in recent years. This includes clinical, genetic, behavioural and environmental information. Large volumes of data from various sources are generated daily by healthcare providers, biomedical researchers, and patients. Technology advancements, such as AI, allow for the analysis of human thought processes. The pharmaceutical business saw significant transformation as a result of the application of machine learning, AI, and automation processes. Various types of analysis have contributed to a general decline in death rates. The use of AI techniques aids in diagnosing the most serious illnesses. To properly diagnose and treat a patient, it is essential to first identify any potential genetic disputes. Technological advancements have made it easier for pharmaceutical companies to detect dosage mistakes. Machine learning relies on monetary analysis, regular spectral analysis and the feature attraction process. The creation of an intelligent computer program is crucial for modelling mechanical systems. In this review, we have glanced at how technology plays a part in the pharmaceutical industry and at the potential outcomes that robotics and AI could have. INTRODUCTION:Robotic systems with artificial intelligence (AI) can learn, make decisions, and solve problems in a manner comparable to that of a person, but they are not yet QUICK RESPONSE CODE

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“…Besides, in Hanerde, 13 a large gantry-type glass sorting manipulator was designed, which can absorb glass and stack through the pneumatic suction cup. Also, the series structure of palletizing manipulators designed by FANUC and ABB were discussed in Nikolov et al 14 and Rajkumar et al 15 to further promote the application of palletizing manipulator in industrial production.…”

Section: Introductionmentioning

confidence: 99%

Multi-link mechanism-inspired palletizing manipulator: Design, optimization and experimental results

Chen

Huang

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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The precision of trajectory tracking and stable operation with sorting merchandise are the main challenges for palletizing manipulators in different working conditions, especially in sorting glass-substrate. To ensure the adaptability of the manipulator under different working conditions, including operational efficiency, motion space, and control accuracy, the structural optimization and the motion control methods of the manipulator should be considered. In this paper, the structure optimization and tracking control of the manipulator for sorting glass substrates are studied. Firstly, considering the optimization factors including stroke speed ratio k, transmission angle [Formula: see text] and the sum of link-rod lengths l of the crank rocker mechanism, a structural optimization method based on genetic algorithm is applied to enhance the flexible maneuverability. Furthermore, a feedforward-feedback iterative learning control (ILC) algorithm is adopted to the high accuracy of position tracking. Finally, experimental results verify the feasibility of structural optimization and tracking control, which can be effective applied in practical engineering.

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Description and modelling of robot-manipulator FANUC M-430iA/4FH

Cited by 10 publications

References 3 publications

A Laser Forming Study on Time and Energy Efficiency

A Laser Forming Study on Time and Energy Efficiency

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Multi-link mechanism-inspired palletizing manipulator: Design, optimization and experimental results

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