Vision guided robotic inspection for parts in manufacturing and remanufacturing industry

Khan, Aamir; Mineo, Carmelo; Dobie, Gordon; MacLeod, Charles N.; Pierce, S. Gareth

doi:10.1007/s13243-020-00091-x

Cited by 31 publications

(18 citation statements)

References 32 publications

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“…Research reported in [52] investigated creation of an automation cell for an aircraft fan-blade repair with the integration of a 6-DoF industrial robot with an end-effector grinder and a computer vision system. Another study reported the use of vision-guided robotic technology for ultrasonic inspection of components in returned products [53].…”

Section: Sensors and Machine Vision For Inspectionmentioning

confidence: 99%

A Review of Circular Economy Research for Electric Motors and the Role of Industry 4.0 Technologies

et al. 2021

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The market for electric motors is experiencing a step-growth due to their adoption across a range of industrial sectors. This increased demand also highlights the importance of end-of-life management of electric motors and a requirement for appropriate strategies for the high value materials embedded in them. This paper aims to offer a holistic view on the circular economy research for electric motors and the role of Industry 4.0 technologies by presenting the state-of-the-art available in literature and comparing it with the industrial perspective. The literature review revealed the absence of a methodology for selecting the best end-of-life scenario for industrial electric motors. Recycling, which is an end-of-product-life strategy, was found to be the key focus area of research. Reuse, which is a better strategy in terms of waste hierarchy, was the least researched area due to lack of information about the condition and availability of returned products. In order to capture the current landscape within the UK for the repair, remanufacture and recycling of electrical machines, a structured survey of UK based companies was conducted. The survey revealed that nearly half of the companies do not undertake any repair strategies for electrical machine components; however, there was an aspiration from the respondents to migrate their companies towards more sustainable activities. The industry survey and the review of existing literature led to the identification of research trends, challenges and recommendations for future research.

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Section: Sensors and Machine Vision For Inspectionmentioning

confidence: 99%

A Review of Circular Economy Research for Electric Motors and the Role of Industry 4.0 Technologies

et al. 2021

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“…Previous works have obtained good automated 3D reconstructions of parts by moving a robot-manipulated 3D scanner around a given component through a predefined path, along which multiple views of the scene are collected. In [26], the authors proposed using a robot arm to move a non-contact passive 3D scanning system, following spiral paths lying on paraboloid primitives and stopping at regular intervals with the camera pointing at the centre of the paraboloid, to collect photogrammetric views of relatively small industrial parts. Although this may be an acceptable scanning path for some objects, it can cause some portions of the part to not be scanned at all, some other areas to not be scanned to a satisfactory or acceptable extent and/or, on the contrary, some remaining areas to be over-sampled.…”

Section: Related Workmentioning

confidence: 99%

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Mineo

Cerniglia

Ricotta

et al. 2021

Int J Adv Manuf Technol

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Many industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

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“…The merged point clouds create the complete 3D model. This whole process, going from the single range map to the whole model, is usually known as the 3D scanning pipeline [24,25]. Complete 3D reconstruction of a scene is typically achieved by establishing a relative motion between the scanning system and the object to reconstruct, while data is captured by the system.…”

Section: Related Workmentioning

confidence: 99%

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Mineo

Cerniglia²,

Ricotta³

et al. 2021

Preprint

Self Cite

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Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are unavoidable differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. This could be avoided by measuring the real-geometry and the position of the specimen, which creates the paradox of having to plan robot paths for surface mapping purposes, before the originally intended robot task can be approached. Previous works have demonstrated the use of robotically manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized to the part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

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Vision guided robotic inspection for parts in manufacturing and remanufacturing industry

Cited by 31 publications

References 32 publications

A Review of Circular Economy Research for Electric Motors and the Role of Industry 4.0 Technologies

A Review of Circular Economy Research for Electric Motors and the Role of Industry 4.0 Technologies

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

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