Autonomous Inspection in Manufacturing & Remanufacturing (AIMaReM)
Lead Research Organisation:
University of Strathclyde
Department Name: Electronic and Electrical Engineering
Abstract
High value manufacturing is an essential component of the UK economy, contributing strongly to our economic prosperity and engineering status around the world. The growth in high value manufacturing to support aerospace, nuclear and other high integrity engineering components, has placed huge pressure on the rapid delivery of reliable and high quality Non-Destructive Evaluation (NDE) to inspect these parts. Currently, much inspection of safety critical components (sometimes requiring 100% part inspection) is performed manually, leading to significant bottlenecks associated with the NDE. Existing robots typically follow pre-programmed paths making them unsuitable to handle, inspect and disassemble parts with a significant tolerance or variability. A new end-to-end approach is needed, embracing manufacture, transport through factory, parts alignment, parts tracking, and inspection (both surface form metrology and NDE) with the associated high volume data management feeding into the quality and assurance compliance processes.
Exactly the same process bottlenecks occur when we translate the problem to the regime of Remanufacturing, hence the integrated approach taken through this proposal. Remanufacturing has been identified as being central to the creation of economic growth in the UK and global markets. With supplies of resources and energy limited, the transition to a low carbon economy with strong emphasis on resource efficiency is key to the UK's Industrial Strategy. Remanufacturing can support this transition by achieving significant impact in all industrial sectors through preventing waste, improving resource management, generating sustainable economic growth, increasing productivity and enhancing competitiveness.
AIMaReM (Autonomous Inspection in Manufacturing& Remanufacturing) provides a unique combination of data collection, processing and visualisation tools combined with efficient robot path planning and obstacle avoidance, with a focus on manufacturing inspection (NDE and surface form metrology). The project will deliver an automated, systems integrated solution, that will be of direct benefit to the manufacturing sector to allow faster integrated inspection and parts handling, thus saving time, and reducing costs whilst enhancing quality and throughput.
Exactly the same process bottlenecks occur when we translate the problem to the regime of Remanufacturing, hence the integrated approach taken through this proposal. Remanufacturing has been identified as being central to the creation of economic growth in the UK and global markets. With supplies of resources and energy limited, the transition to a low carbon economy with strong emphasis on resource efficiency is key to the UK's Industrial Strategy. Remanufacturing can support this transition by achieving significant impact in all industrial sectors through preventing waste, improving resource management, generating sustainable economic growth, increasing productivity and enhancing competitiveness.
AIMaReM (Autonomous Inspection in Manufacturing& Remanufacturing) provides a unique combination of data collection, processing and visualisation tools combined with efficient robot path planning and obstacle avoidance, with a focus on manufacturing inspection (NDE and surface form metrology). The project will deliver an automated, systems integrated solution, that will be of direct benefit to the manufacturing sector to allow faster integrated inspection and parts handling, thus saving time, and reducing costs whilst enhancing quality and throughput.
Planned Impact
The impact of the AIMaReM project research will be quickly felt through uptake of new technologies and approaches by a range of industry. We identify specific application areas in the proposal including Aerospace Manufacturing (SPIRIT Aerosystems and RCNDE through industrial membership NDEvR, including Rolls Royce and TWI), Remanufacturing (Autocraft Drivetrains) and Nuclear Inspection (National Nuclear Laboratory). These areas represent key UK manufacturing and infrastructure assets. Aerospace and automotive manufacturing are at opposite ends of the spectrum, aerospace lifecycle typically being 50 years and high value, with automotive being lower cost, shorter lifecycle but with higher volumes. We have chosen to focus on Remanufacturing for the automotive sector to investigate the additional benefits to the environment and carbon commitments bythe introduction of the new technologies.
The underpinning research targets a number of areas that are still highly manual in operation, and as such provide barriers to throughput in the manufacturing sector (and hence increase cost). Our main focus (reflected in the partnerships), lies in high value aerospace manufacturing technology, where integration of quality and safety critical inspection procedures into the manufacturing cell is increasingly demanded from the manufacturers. Both surface form quality (for performance and assembly integrity) and internal defect compliance monitoring (through conventional NDE) are demanded by industry, and all the major UK aerospace manufacturers have a common desire to decrease inspection cycle time and improve throughput to cope with the projected demands for aerospace structures. Manual interpretation of data, with associated quality and coverage issues is not sufficient for parts demanding 100% inspection coverage. The drive is to full automation of the whole inspection process for large components (this includes transport through factory, alignment into automated process cells, delivery of surface form measurements, delivery of NDT measurements and handling the large data sets produced by these measurement techniques in real time). Although our initial motivation is therefore aerospace manufacturing, it is clear that the autonomous techniques developed translate directly into the automotive Remanufacturing environment. Here part transport, recognition and orientation are just as relevant as for aerospace, but with a lower emphasis on NDE. Real time adaptive robot path planning and obstacle avoidance must be seamlessly integrated into the measurement tasks - the ability for in process loop modification of path and measurement strategy is an essential characteristic for automating the inspection procedure. Building the requisite intelligence into the data compression, processing, display and archiving are all core priorities.
Finally we note that the autonomous approaches developed in the proposal will translate well into the arena of asset inspection. We have chosen to demonstrate this initially by focussing on collaboration with the National Nuclear Laboratory and Sellafield sites (both existing partners through EPSRC and Innovate UK funded projects). Demonstrating our range of robotic delivery and control platforms at the new Workington facilities is our strategy, and realistic due to numbers of the team having already deployed semi-autonomous inspection vehicles on site at Sellafield after proving through Workington.
Of course the academic team will pursue the conventional impact and dissemination activities through academic journal and conference publications. The proposed international collaborations will allow the research to have strong exposure in the EU robotics arena, leading to new knowledge exchange and joint research activities funded through the current Horizon 2020 framework.
The underpinning research targets a number of areas that are still highly manual in operation, and as such provide barriers to throughput in the manufacturing sector (and hence increase cost). Our main focus (reflected in the partnerships), lies in high value aerospace manufacturing technology, where integration of quality and safety critical inspection procedures into the manufacturing cell is increasingly demanded from the manufacturers. Both surface form quality (for performance and assembly integrity) and internal defect compliance monitoring (through conventional NDE) are demanded by industry, and all the major UK aerospace manufacturers have a common desire to decrease inspection cycle time and improve throughput to cope with the projected demands for aerospace structures. Manual interpretation of data, with associated quality and coverage issues is not sufficient for parts demanding 100% inspection coverage. The drive is to full automation of the whole inspection process for large components (this includes transport through factory, alignment into automated process cells, delivery of surface form measurements, delivery of NDT measurements and handling the large data sets produced by these measurement techniques in real time). Although our initial motivation is therefore aerospace manufacturing, it is clear that the autonomous techniques developed translate directly into the automotive Remanufacturing environment. Here part transport, recognition and orientation are just as relevant as for aerospace, but with a lower emphasis on NDE. Real time adaptive robot path planning and obstacle avoidance must be seamlessly integrated into the measurement tasks - the ability for in process loop modification of path and measurement strategy is an essential characteristic for automating the inspection procedure. Building the requisite intelligence into the data compression, processing, display and archiving are all core priorities.
Finally we note that the autonomous approaches developed in the proposal will translate well into the arena of asset inspection. We have chosen to demonstrate this initially by focussing on collaboration with the National Nuclear Laboratory and Sellafield sites (both existing partners through EPSRC and Innovate UK funded projects). Demonstrating our range of robotic delivery and control platforms at the new Workington facilities is our strategy, and realistic due to numbers of the team having already deployed semi-autonomous inspection vehicles on site at Sellafield after proving through Workington.
Of course the academic team will pursue the conventional impact and dissemination activities through academic journal and conference publications. The proposed international collaborations will allow the research to have strong exposure in the EU robotics arena, leading to new knowledge exchange and joint research activities funded through the current Horizon 2020 framework.
Organisations
- University of Strathclyde (Lead Research Organisation)
- University of Sheffield (Collaboration)
- SPIRIT Aerosystems (Collaboration)
- Association for Robots in Architecture (Collaboration)
- University West (Collaboration)
- National Nuclear Laboratory (Collaboration)
- Autocraft Drivetrain Solutions Ltd (Collaboration)
- UNIVERSITY OF STRATHCLYDE (Collaboration)
- KUKA Robotics (Collaboration)
Publications
Antoniadou I
(2017)
An Illustration of New Methods in Machine Condition Monitoring, Part II: Adaptive outlier detection
in Journal of Physics: Conference Series
Charalampos Loukas N
(2022)
A sensor enabled robotic strategy for automated Defect-Free Multi-Pass High-Integrity welding
in Materials & Design
Cooper I
(2017)
Introducing a novel mesh following technique for approximation-free robotic tool path trajectories
in Journal of Computational Design and Engineering
Davì S
(2020)
Correction of B-scan distortion for optimum ultrasonic imaging of backwalls with complex geometries
in Insight - Non-Destructive Testing and Condition Monitoring
Fei Z
(2020)
Deep convolution network based emotion analysis towards mental health care
in Neurocomputing
Foster E
(2022)
Automated Real-Time Eddy Current Array Inspection of Nuclear Assets
in Sensors
Fuentes R
(2021)
Equation discovery for nonlinear dynamical systems: A Bayesian viewpoint
in Mechanical Systems and Signal Processing
Fuentes R
(2019)
A probabilistic compressive sensing framework with applications to ultrasound signal processing
in Mechanical Systems and Signal Processing
Description | We have developed a new high speed ultrasonic inspection process for aerospace components. We have developed new data processing tools to cope with high throughput data acquisition. We have developed a new probablistic method for data gathering that links into the automated aquisition |
Exploitation Route | In aerospace manufacture, automotive remanufacture, nuclear plant inspection |
Sectors | Aerospace Defence and Marine Construction Education Energy |
URL | http://aimarem.eee.strath.ac.uk/ |
Description | At a series of public exhibitions The team are translating research findings to new project directly funded by Industry (Spirit AeroSystems). |
Sector | Aerospace, Defence and Marine,Education,Energy |
Impact Types | Societal |
Description | ABC of ARC |
Amount | £224,000 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2018 |
End | 03/2020 |
Description | Alpha Glovebox Decomissioning Feasibility Study |
Amount | £30,736 (GBP) |
Funding ID | 104068 |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 01/2018 |
End | 12/2018 |
Description | Automated delivery of non-contact NDE sensors |
Amount | £114,541 (GBP) |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2018 |
End | 03/2020 |
Description | GKN DAITAS |
Amount | £31,543 (GBP) |
Organisation | GKN |
Department | GKN Aerospace |
Sector | Private |
Country | United Kingdom |
Start | 08/2017 |
End | 10/2020 |
Description | GKN PhD |
Amount | £87,000 (GBP) |
Organisation | GKN |
Department | GKN Aerospace |
Sector | Private |
Country | United Kingdom |
Start | 09/2017 |
End | 10/2020 |
Description | KTP Glenalmond |
Amount | £230,300 (GBP) |
Organisation | Knowledge Transfer Partnerships |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 09/2017 |
End | 09/2020 |
Description | New Wire Additive Manufacturing (NEWAM) |
Amount | £5,886,209 (GBP) |
Funding ID | EP/R027218/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2018 |
End | 06/2024 |
Description | OAAM - Open Architecture Additive Manufacture |
Amount | £320,619 (GBP) |
Funding ID | 113164 |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 09/2017 |
End | 11/2020 |
Description | RoboWAAM, Robotically Delivered Wire Arc Additive Manufacture |
Amount | £1,436,000 (GBP) |
Funding ID | 103273 |
Organisation | Innovate UK |
Sector | Public |
Country | United Kingdom |
Start | 03/2017 |
End | 03/2019 |
Description | SPIRIT PhDs |
Amount | £140,000 (GBP) |
Organisation | SPIRIT Aerosystems |
Sector | Private |
Country | United States |
Start | 11/2017 |
End | 11/2020 |
Description | Spirit AeroSystems Royal Academy of Engineering Research Chair "In-process Non-destructive Testing for Composites" |
Amount | £600,000 (GBP) |
Funding ID | RCSRF19201032 |
Organisation | Royal Academy of Engineering |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2020 |
End | 02/2025 |
Description | Wing of Tomorrow |
Amount | £837,094 (GBP) |
Organisation | SPIRIT Aerosystems |
Sector | Private |
Country | United States |
Start | 06/2017 |
End | 06/2019 |
Description | AMRC/Factory 2050 |
Organisation | University of Sheffield |
Department | Advanced Manufacturing Research Centre (AMRC) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Joint workpackage |
Collaborator Contribution | Joint workpackage |
Impact | Inpsection |
Start Year | 2016 |
Description | Aachen Robots in architecture |
Organisation | Association for Robots in Architecture |
Country | Austria |
Sector | Charity/Non Profit |
PI Contribution | Robotic programming |
Collaborator Contribution | Robotic programming |
Impact | New programming for robotics |
Start Year | 2016 |
Description | Autocraft |
Organisation | Autocraft Drivetrain Solutions Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | remanufacture |
Collaborator Contribution | remanufacture |
Impact | remanufacture |
Start Year | 2016 |
Description | KUKA |
Organisation | KUKA Robotics |
Country | Germany |
Sector | Private |
PI Contribution | Robotics |
Collaborator Contribution | Robotics |
Impact | robotics |
Start Year | 2016 |
Description | NNL |
Organisation | National Nuclear Laboratory |
Country | United Kingdom |
Sector | Public |
PI Contribution | Consultancy work evaluating electromagnetic and ulrasonic inspection of AGR fuel pins |
Collaborator Contribution | Technology and procedures for inspection |
Impact | Technical findings, new inspection techniques and capabilities |
Start Year | 2014 |
Description | SEARCH |
Organisation | University of Strathclyde |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | New technology transfer to industry and academic partners |
Collaborator Contribution | New applications e.g. in pharmaceutical manufacture, welding & joining, cladding |
Impact | New project partnerships with end users - technology demonstrators |
Start Year | 2021 |
Description | SPIRIT |
Organisation | SPIRIT Aerosystems |
Country | United States |
Sector | Private |
PI Contribution | Partnership on ATI Innovate UK VIEWS program on new technology |
Collaborator Contribution | Developing integrated robotic NDT and metrology cell |
Impact | New inspection capabilities |
Start Year | 2013 |
Description | University West |
Organisation | University West |
Department | University College West |
Country | Sweden |
Sector | Academic/University |
PI Contribution | Collaborative robotics and production engineering |
Collaborator Contribution | Collaborative robotics and production engineering |
Impact | Collaborative robotics and production engineering |
Start Year | 2016 |
Title | Data for: "Novel algorithms for 3D surface point cloud boundary detection and edge reconstruction" |
Description | The dataset contains the source MATLAB version of the figures included in the paper, which is available through the link: https://doi.org/10.1016/j.jcde.2018.02.001. Moreover, the dataset contains two examples of boundary points detection (BPD). The examples show the use of the compiled version of the published BPD algorithm, which is described in the paper. The two examples show that all boundary points are correctly detected for the point clouds of a fan blade curved surface and the point cloud of half Stanford bunny. The prerequisites to run the compiled version of the BPD algorithm (boundaryPoints.exe) are: - 64-bit Windows operating system; - MATLAB Compiler Runtime (MCR) R2016a (9.0.1); It is possible to download the MCR installer for MATLAB R2016a from the MathWorks Web site, by navigating to: http://www.mathworks.com/products/compiler/mcr/index.html You will need administrator rights to run the MCR installer. For more information about the MCR and the MCR installer, see Distribution to End Users in the MATLAB Compiler documentation in the MathWorks Documentation Center. |
Type Of Technology | Software |
Year Produced | 2019 |
Title | Interfacing Toolbox for Robotic Arms |
Description | Robots are increasingly present in industry. Achieving effective integration and the full potential of robotic systems presents significant challenges. Robots, sensors and end-effector tools are often not necessarily designed to be put together and form a system. This manual introduces a C++ language-based toolbox, designed to facilitate the integration of industrial robotic arms with server computers, sensors and actuators. The toolbox, named as Interfacing Toolbox for Robotic Arms (ITRA), contains fundamental functionalities for robust connectivity, real-time control in Cartesian and joint space and auxiliary functions to set or get key functional variables. It is designed to run on a remote computer connected with one or multiple robot controllers. All embedded functions can be used through high-level programming language platforms (e.g. MATLAB®, LabVIEW®), providing the opportunity to speed-up robust integration of robotic systems. Emerging applications aim to use robot arms in changing environments with movable obstacles or where the shape of the surroundings is changing. In such situations, the robots need to adapt their tasks/behaviors. ITRA contains functions designed to enable real-time adaptive robot behavior, maximizing the robot promptness and respecting constraints (maximum accelerations and velocities). The toolbox is compatible with all KUKA robotic arms, based on the fourth generation of KUKA controllers and equipped with the Robot Sensor Interface (RSI) software add-on. The current version of the DLL is available for Windows 32bit and 64bit platforms. |
Type Of Technology | Software |
Year Produced | 2019 |
Description | 9th China-Scotland Signal and Image Processing Research Academy Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Novel data visualisation approaches for ultrasonic inspection of complex geometries - 9th China-Scotland Signal and Image Processing Research Academy Workshop |
Year(s) Of Engagement Activity | 2018 |
Description | Advanced Engineering show |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Advanced Engineering Show Birmongham Nov 2016 |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |
Description | BEIS event |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | ERIC the robot |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |
Description | Explorathon - European Night of Science |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Public/other audiences |
Results and Impact | ERIC the robot demonstrator |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |
Description | Jaguar Land Rover Skills Show - Hired by KUKA Robotics UK |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Annual show for KUKA/ JLR |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |
Description | RWTH Aachen University |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Given a seminar on Robotic Non-Destructive Testing, Product and Process Integrity |
Year(s) Of Engagement Activity | 2017 |
Description | Scottish Airshow 2016 - Lead Sponsor Spirt AeroSystems Stand |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Public/other audiences |
Results and Impact | ERIC the robot demonstrator |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |
Description | Scottish Manufacturing Advisory Service Annual Conference |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Industry/Business |
Results and Impact | ERIC the robot |
Year(s) Of Engagement Activity | 2016 |
URL | http://eric.eee.strath.ac.uk/ |