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Home Explore Connecting Members August 2020

Connecting Members August 2020

Published by siti_aishah, 2020-08-31 09:11:55

Description: Connecting Members August 2020


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AUGUST 2020 ISSUE 01 Industry Members 03 CURpPdates 09 ENqeuwipment 10 IPAroF-gPrPamme 12 MCaepmabbielirt'ises 13 HEvigehntlights 15 Trainings 16 Members Portal 17 AofRETvCeCnatslendar NEWSLETTER CONTENT IS STRICTLY FOR MEMBERS ONLY. PLEASE DO NOT DISTRIBUTE.


CRP UPDATES CYCLE 7 CORE RESEARCH PROJECTS (CRP) CRP TECHNOLOGY INDEX PROJECT TITLE PROJECT PROJECT THEME C20_01_ARTC TECHNICAL LEAD MANAGER Additive C20_02_ARTC 3D Printing of High Entropy Superalloys for Shashwat Shukla Ham Yean How C20_03_ARTC High Temperature Applications Muhammad Adri Ham Yean How Manufacturing Ham Yean How (AM) Media Selection for Abrasive Flow Maharjan Niroj Ham Yean How Machining of Internal Channel Ham Yean How Intelligent Coating Removal and Joshua Wong Verification Surface Preparation Joshua Wong Joshua Wong (IV) C20_04_ARTC Powder And Wire Laser Metal Deposition Chia Guo Yong Victor Quek Smart Victor Quek Automation C20_05_ARTC X-ray Inspection of Additively Bisma Mutiargo Victor Quek (SA) C20_06_ARTC Manufactured Components - Phase 2 Deepesh Smart C20_07_ARTC Zhou Yu Factory C20_08_ARTC Process Monitoring & Control Upadrashta Zhou Yu (SF) for Direct Laser Deposition (DLD) Wong Zheng Zheng Zhou Yu Applications - Phase 2 Zhang Jie Seal Integrity Sensor based on Capacitive Imaging Surface Defect Inspection using 3D Scanning Data C20_09_ARTC Mobile Manipulation - Phase 3 Lee Li Zhen C20_10_ARTC Optimised Traffic Management for AGV/AIV Alberto De San Bern- C20_11_ARTC Fleets Phase 2 abé Clemente C20_12_ARTC C20_13_ARTC Versatile Robot Grasping And Bai Fengjun C20_14_ARTC Manipulation Based On Cognitive Analytics Proof of Concept Digital Twin for Next Nimisha Agarwal Generation Supply Chain A Demonstrator of 5G Enabled Parts Lim Cheng Leong Delivery System Tool Wear Prediction using Transfer Machine Amir Bahador Learning CONNECTING MEMBERS - AUGUST 2020 03

CRP UPDATES CRP Technology Theme Additive Manufacturing MPoewtadleDr eapnodsWitiioren Laser CRP Index C20_04_ARTC ARTC Project Manager Ham Yean How, [email protected] ARTC Project Technical Lead Chia Guo Yong , [email protected] Project Background • While there is a common understanding of the general pros and cons between powder and lateral wire Laser Metal Deposition (LMD), there is a lack of understanding between the recent state-of-the-art coaxial wire feeding LMD systems and powder LMD systems. Therefore, such understanding needs to be re-established and the technologies reassessed. Objective IN718 cuboid (Powder) IN718 cuboid (Wire) • To review and evaluate the state-of-the-art coaxial wire LMD in comparison with existing powder LMD capabilities, and to consider potential use of powder and wire in sequence or in tandem. Benefits/PotentialIndustrialApplications • Comprehensive understanding of state-of-art coaxial wire LMD in relation to powder LMD for different materials and practical applications is achieved. • Database including “best practices” for various process applications using powder and/or coaxial wire LMD is established. • Potential solutions for“step-by-step”and hybrid powder and wire LMD. Technology Groups Involved • Advanced Remanufacturing (AR) • Data-driven Surface Enhancement (DSE) Current Status • (MS1) Technology review completed – cost of wire material found to be generally lower than powder counterparts, general cost of commercially available coaxial wire LMD systems costs are identified. • (MS2) Raw materials procured – IN718, Ti64 & H13 materials procured, coaxial wire LMD vendors secured. • (MS3) LMD experiments and evaluations (on-going) – IN718 thin walls, IN718 cuboids, Ti64 thin walls depositions completed. H13 depositions currently on-going. Metallurgical evaluations to follow. 04 CONNECTING MEMBERS - AUGUST 2020

CRP Technology Theme CRP UPDATES Intelligent Verification Surface Defect Inspection CRP Index using 3D Scanning Data C20_08_ARTC ARTC Project Manager Joshua Wong, [email protected] ARTC ,[email protected] Zhang Jie Project Background • Typical optics setups used for acquiring surface defect sometimes face challenges such as certain defects which are hard to capture in 2D images unless specific lighting mechanisms are applied. Illumination needs to be carefully designed to highlight the defect while avoiding noise at the same time. This project will study the application of deep learning when depth is measured to enhance the visibility of the surface defects. Laser Objective • To develop deep learning capabilities for defect detection using 3D point cloud data. • To develop a testbed for 3D data acquisition. The capability developed will be customisable according to resolution and Field of view (FOV) requirement. Stage Benefits/ Potential Industrial Applications Sample • Surface defect detection for components with complex shapes and features without the need for illumination and optical filtering. • Immediate defect depth measurement after identification without using other sensors Scanning Platform ARTC Technology Groups Involved • Intelligent Product Verification Current Status • Consolidating 3D defect data through samples provided by members. • Developing algorithm for defect detection using commercial deep learning software. • Designing and fabricating prototype for demonstration. CONNECTING MEMBERS - AUGUST 2020 05

CRP UPDATES CRP Technology Theme Smart Automation Optimised Traffic CRP Index Management for AGV/AIV C20_10_ARTC Fleets - Phase 2 ARTC Project Manager Victor Quek Yen Sen, [email protected] ARTC Project Technical Lead Alberto De San Bernabe, [email protected] Project Background • Fulfilment Centers and Factories of the future will deploy fleets of heterogeneous robots. The coordination of the different fleets of robots requires a platform to manage their routing for efficient and safe navigation. • To address this issue, a traffic management module to enable smooth and effective implementation of different brands of mobile platforms in the shop-floor was developed in CRP6 Objective 2 Common Origin Map • Enhance fleet management by including features Graph for map standardisation and customisation. 4 3 1 Order • Evaluate the scalability of our current traffic Real Life AMR Request management solution. Communication Planner/Scheduler Module Simulated Module Module Benefits/ Potential Industrial 5 AMR Applications Communication Module • Warehouse/distribution center and goods-to- person automation. # Update from CRP6 to CRP7 Details • Manufacturing line with Autonomous Mobile 11 Graph Generator Automatic discretization of a map into a graph Robot (AMR) based material transfer between stations. 22 Map merger / Map customization Combine auto mapping with several AMRs. Definition of areas of reduce speed & time Technology Groups Involved restricted access • Advanced Robotics Application (ARA) 33 Order received/order completed feedback Feedback signals to planner that indicate the reception and the completion of an order. 44 Integration of new AGV model Integration of Fetch AGV. 55 Simplified (not graphical) simulator Fast test & evaluation of the planner, indicating estimation of real time execution of the orders, numbers of conflicts, etc. System Architecture Upgrades Current Status • Completed system architecture evaluation and upgrades, defining map merging and graph generating features for module development. • On-going development to integrate map merging feature for multi-robot mapping and map standardisation. • On-going development to integrate graph generator feature for automated creation of waypoints and their links over a new map. Map Merging Feature 06 CONNECTING MEMBERS -AUGUST 2020

CRP Technology Theme CRP UPDATES Smart Automation CRP Index Versatile Robot Grasping C20_11_ARTC and Manipulation based on Cognitive Analytics ARTC Project Manager Victor Quek Yen Sen, [email protected] Project Background ARTC Project Technical Lead • Most robots used for performing specialised tasks in controlled Bai Fengjun, [email protected] (pre-program, pre-defined) scenarios, such as manufacturing. Pre-programmed grasping solutions are typically designed for Grasping pose specific tasks such as customised for specific task with poor adaptability to object variations thus not easily expanding to Grasping results from Dexnet using a suction cup gripper various use cases. Traditional grasping systems lacks robustness in \"handling\" when placed in a dynamic environment. Point cloud Detected grasping Target grasping pose candidates Objective Grasping results from GPD on Point cloud data • To develop a robotic grasping approach that caters to a variety of novel objects using a deep learning approach. Grasping using visual pushing for grasping algorithm • Robotic grasping motion planning with obstacle avoidance. • Multi-sensor integration and sensor fusion to improve the success rate of grasping. Benefits/ Potential Industrial Applications • Versatile robot grasping with a deep learning approach is robust enough to detect and estimate grasping positions to novel objects of various dimensions. This is required for flexible operations with high mix-low volume parts. • Pick and place various objects with gripper grasping. Technology Groups Involved. • Advanced Robotic Applications (ARA) Current Status • Literature review has been done for grasp detection approach and available software packages. • Working on simulation to train the model for grasp detection. • Setting up the robotic system and vision system, and optimising parameters to evaluate grasping performance. CONNECTING MEMBERS - AUGUST 2020 07

CRP UPDATES Proof of Concept CRP Technology Theme Digital Twin for Smart Factory Next Generation Supply CRP Index C20_12_ARTC ARTC Project Manager Zhou Yu, [email protected] ARTC Project Technical Lead Nimisha Agarwal, [email protected] Project Background • The current supply chain processes rely on: 1. Manual business model implementation 2. Experience 3. Communication between vendors and transporters which takes a long time, with reduced efficiency • Digitalisation of supply chain processes using the Digital Twin (DT) technology provides the visibility needed to facilitate improved decision making capabilities. Objective • To design and implement a proof of concept (POC) Digital Twin Application for the use-case of Hyper-personalisation (HPL) at ARTC which can demonstrate Digital Twin capabilities: (1) end-to-end visibility of supply chain, (2) decision-making capabilities to help in optimisation, and (3) disruption management capabilities. • To provide the methodology for the implementation of DT, for wider adoption at manufacturing firms to adapt to different supply chain models. Benefits/ Potential Industrial Applications • The proof of concept Digital Twin opens possibilities for the adoption of digitisation for supply chain. • It offers methodologies to use the Digital Twin as per each company’s requirements and can adapt to different supply chains and softwares. • To use Digital Twin capabilities to investigate specific supply chain modules such as production scheduling, inventory assignment, etc.. Technology Groups Involved KPI dashboard • Smart Manufacturing Group (SMG) Current Status • Configuration of software modules for seamless data integration and connectivity; pending configuration of some of the softwares. • Developing the UI design for a Digital Twin application with automated waypoint creation and linkage over a new map. 08 CONNECTING MEMBERS - AUGUST 2020

NEW EQUIPMENT Fetch Mobile Manipulator Description The Fetch Mobile Manipulator consists of a differential drive mobile base, an arm with 7 degrees of freedom and 6kg payload, a pan and tilt head, a torso lift actuator, and a standalone mobile robot platform. The mobile base contains a 2D scanning laser range finder with a 220 degree field of view for navigation. With the pan and tilt of the head together with its adjustable torso, the 3D short range depth camera allows for additional optical support for object detection and directional navigation. Technical Data Department Size: 508mm wide, 559mm diameter, 1096mm (min) - 1491mm (max) height Advanced Robotics Application Payload:  7 kg (collaborative robot) Weight: 113.3kg  Owner Max. speed of mobile base: 1m/s  Installed software: Ubuntu Linux LTS, ROS Melodic 18.04 Kendrick Chin Applications Location • Machine tending ARTC Level 5 (AGV Arena) • Shelf picking KUKA KMR iiwa Department Description Advanced Robotics Application The KUKA KMR iiwa is a mobile manipulator which features a 14-kg collaborative robot mounted atop an Autonomous Intelligent Vehicle Owner (AIV) for increased mobility and flexibility in performing robotic applications. It comes with in-built safety sensors to detect obstacles Lee Li Zhen reliably and keep within regulated speeds. The system also comes with a fleet management system to monitor other KUKA vehicles in the Location workshop. ARTC Level 5 (AGV Arena) Technical Data Size: 1080x630x700 mm (Mobile base only) Payload: 7kg (collaborative robot) ,170kg (mobile base) Weight: 420kg Max. speed of mobile base: 2 – 3.6 km/h (Depending on direction) Positioning accuracy: ±0.1mm (collaborative robot)±5mm(mobile base) Applications • Machine tending • Depalletising CONNECTING MEMBERS - AUGUST 2020 09

NEW IAF-PP PROGRAMME Advanced Post-Processing and Non-Destructive Evaluation for Additive Manufacturing A*STAR and NTU recently secured a funding under the Industry Alignment Fund to develop advanced post-processing and non-destructive evaluation (NDE) solutions targeted at additively manufactured (AM) components. The 30-month programme running till December 2022 is a collaboration of more than 40 researchers from four A*STAR Institutes (ARTC, IHPC, IMRE, SIMTech) and NTU led by Principal Investigator Dr. Andy Malcolm from ARTC. Objectives Calling for Industry Participation and Collaboration Post-processing and non-destructive evaluation of AM components pose several challenges that are not typically The team encourages active participation from members encountered for components manufactured by traditional of the ARTC consortium to help steer the programme. means, such as: Specific problem statements and feedback are welcome. While initial development is generic in nature, • Complex geometry, including internal channels resources have been earmarked in the latter stages • Poor initial surface roughness, that is also non- of this programme to tailor the outcome to specific uniform and anisotropic industry needs. In addition, there are options to develop • Complex thermal profiles during fabrication, leading customised solutions for your company through direct to complex material properties projects or through licensed developed technologies. • High component values, rendering destructive testing unfeasible For further enquiries, please contact   Dr. Andy Malcolm, [email protected] To address these challenges, expertise across the Singapore research ecosystem is being leveraged to develop and deliver a suite of novel and enhanced solutions that span surface enhancement, surface finishing and non-destructive evaluation. 10 CONNECTING MEMBERS - AUGUST 2020

NEW IAF-PP PROGRAMME WORK Surface Enhancement of AM Components by Laser- assisted Robotic Hammer Peening 1PACKAGE The main objective is to develop a cost-effective laser-assisted robotic hammer peening as a hybrid process which overcomes the limitations of conventional hammer peening. Using an ultra-fast laser, surface is heated up in-situ during robotic hammer peening in order to augment the process capability, specifically to achieve deeper and more stable compressive residual stress. Improved formulation for coating layer will also be developed by SIMTech. Potential applications are in both large area treatment and also localized repair. WORK Internal and External Finishing of AM Components 2PACKAGE In this Work Package, abrasive flow machining (AFM) and robotic stream finishing (RSF) are developed for internal and external finishing of AM components respectively. Modeling and simulation capabilities will also be developed to support complex process planning and control for AFM and RSF. Finally, a new electropolishing method, with a novel electrode for polishing of complex internal geometry, will also be developed as an alternative to AFM. WORK Non-destruction Evaluation of AM Components 3PACKAGE Non-destructive Evaluation (NDE) techniques are developed to address the requirement from the other Work Packages. Electromagnetic and ultrasonic techniques will be developed to quantify residual stress and characterise near-surface microstructural change. X-ray CT algorithms will be developed to accurately measure the surface roughness, internal dimension and near-surface defects, while ultrasonic techniques will be investigated for online monitoring of surface finishing process with the potential to be integrated as a system with closed-loop feedback. For further enquiries, please contact 11 Dr. Andy Malcolm, [email protected] CONNECTING MEMBERS - AUGUST 2020

MEMBERS' CAPABILITIES Reverse Engineering with Hexagon VISI 2020 Reverse Engineering (RE) is a viable method to reconstruct 3D CAD models of existing physical parts. The 3D scan data, in point cloud format, is transformed to produce a boundary-representation CAD model using commercially available RE software. Recovery of such a 3D CAD model provides information for legacy parts or CADs that are unavailable. The ARTC Intelligent Product Verification (IPV) team undertook a study of several offerings, one being the VISI Reverse 2020 CAD/CAM software, by our member Hexagon Manufacturing Intelligence. A representative aerofoil was scanned with a structured light-based 3D scanner. The steps to convert a 3D point cloud to a 3D CAD model are shown below. Through reduced dependency on manual input from the operator, the time taken for RE was 30% shorter compared to standard commercial RE softwares based on the specific part used. Overall, the RE process is systematic and user-friendly and the team plans to apply VISI reverse in relevant projects moving forward. Differentiating Features of VISI reverse • User-interface with step by step functions with guide • Direct Modelling enabling user to quickly create and modify any geometry. For further enquiries, please contact Ms. Angeline Chang, [email protected] 12 CONNECTING MEMBERS - AUGUST 2020

EVENT HIGHLIGHTS VISIT BY SECOND MINISTER FOR TRADE AND INDUSTRY 11TH AUGUST 2020 President of Roll-Royce South East Asia, Pacific and South Korea, Dr Bicky Bhangu, presented the robot-assisted casing bolting capability jointly developed with ARTC. Second Minister for Trade and Industry, Dr Tan See Leng with A*STAR Chairman, Ms Chan Lai Fung, CEO A*STAR, Mr Frederick Chew and industrial partners. Mr Tan Ser Hean of Abrasive Engineering explained the collaboration with ARTC in digital shot peening. Second Minister for Trade and Industry Visit to ARTC – On the 11th of August, ARTC had the honour of hosting Second Minister for Trade and Industry Dr Tan See Leng. The visit serves as his introduction to A*STAR and ARTC was selected to be the research institute to host the Second Minister. A*STAR Chairman Ms Chan Lai Fung and CEO A*STAR Mr Frederick Chew, alongside ACE SERC Prof Alfred Huan, ACE Enterprise Prof Tan Sze Wee, ARTC co-chair Mr Peter Tan and ARTC CEO Dr David Low. A tour of our workshop was conducted where ARTC and 2 of its Industry Partners (Rolls-Royce & Abrasive Engineering) presented on the industrial solutions co-developed with ARTC, such as digital enabled shot peening and automated bolting for fan case. ARTC's efforts in COVID-19 solutions such as the BRAVE System in collaboration with KA Industrial Engineering, and the Mask Manufacturing Project with Ramatex, were also showcased. CONNECTING MEMBERS - AUGUST 2020 13

EVENT HIGHLIGHTS VISIT BY INFOCOMM MEDIA DEVELOPMENT AUTHORITY 14TH AUGUST 2020 Discussion on the automation of diagnostic testing with IMDA CEO, Model Factory Programme Manager Mr Murali Das presenting the Mr. Lew. Manufacturing Intelligence Control Room (MICR). CEO IMDA Mr Lew Chuen Hong with CEO A*STAR, Dr Frederick Chew, ACE Enterprise, Prof Tan Sze Wee, CEO ARTC Dr David Low and IMDA management. CEO of Infocomm Media Development Authority (IMDA) Visit to ARTC – ARTC hosted the new CEO of IMDA, Mr Lew Chuen Hong on the 14th of August. The visit centred around ARTC’s Public-Private Partnership (PPP) Model from Development to Demonstration and Deployment (3Ds) via W.O.G (whole of government) support. Moving forward, ARTC and IMDA will continue to work together on Industry 4.0 technologies, specifically in the area of 5G in Advanced Manufacturing together with ARTC members. 14 CONNECTING MEMBERS - AUGUST 2020

TRAINING ADVANCED SMART MACHINING TECHNOLOGY TRAINING *course co-organised with SIMTech 6TH OCTOBER 2020 - 17TH NOVEMBER 2020 Computer Numerical Control (CNC) machining is utilised in industrial sectors such as aerospace, marine, oil & gas, automotive, MedTech, precision engineering (PE), and lastly moulds and dyes. However, it has certain constraints on customised production speed in a high-mix-low-volume business demand. Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing Industry 4.0 technologies. To remain competitive and profitable, plants and machines will have to be smarter: better connected, more efficient, more flexible, and be safer. ABOUT THE PROGRAMME This programme will equip managers, engineers and operators in precision engineering companies with the skills to understand and use advanced smart machining technologies to fulfill the relevant industrial requirements. The fundamentals and state-of-the-art on the latest developments in smart machining technology are covered through lectures and lab demonstrations. With the guidance of course mentors during practice sessions, participants will work on a specific relevant project of their own choice to address practical problems in their workplace. The knowledge gained during this course benefits both the participants who stand to upgrade their individual expertise and their companies with the opportunity to improve their productivity and competitiveness. Kindly visit the following website for further details regarding this workshop: or contact Dr. Bertil Brandin at [email protected] About the Trainers Dr Liu Kui is a Senior Scientist with A*STAR SIMTech and an adjunct Associate Professor at the National University of Singapore (NUS). He received his BSc and MSc degrees from the Nanjing University of Aeronautics and Astronautics, China, and his PhD degree in Mechanical Engineering from NUS in 2002 Mr Matthew King is the Deputy Group Manager of the Advanced Remanufacturing Group and Senior Technical Lead for the Machining Technologies Team at the ARTC, managing a team of experienced engineers and scientists developing solutions in a variety of areas that include Adaptive Machining, Intelligent Machining and Lean Manufacturing. Matthew obtained his Bachelors CONNECTING MEMBERS - AUGUST 2020 15

TRAINING ARTC MEMBERS PORTAL COVID-19 has brought about a new normal and ARTC is looking for new ways of connecting with members. The Members Portal is one of such initiatives to provide them with a platform to refer to for information at their convenience. The portal contains components such as trainings and webinars whereby members get an overview of training courses that take place, between ARTC & SIMTech in collaboration with other organisations. These courses allow members to upskill and upgrade the technical capabilities of their staff. Members can also access CRP information on the portal. Another important feature of the Members Portal is the inclusion of our latest technology development and flagship programmes. We’d love to listen to your feedback on the Members Portal, and what you would like to see added to our current database in the Members Portal. Reach out to your ARTC Business Development Account Managers for more information and visit the Members Portal at 16 CONNECTING MEMBERS - AUGUST 2020


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