Programme - Cranfield University
Transcript of Programme - Cranfield University
ProgrammeThere will be a brief introduction at 09:00 and a closing presentation at 15:15 in the auditorium for all to attend.
Room: LR2 Open presentation
Start Finish Project Title
09:15 10:00 MAN6 Environmental impact analysis and life cycle analysis for siting of concentrating solar power plants
10:00 10:45 MAN2 Digitalised Solutions of Organisational Learning Capability
11:15 12:00 MAN4 Digital Twin representation of a modified mobile asset in the aerospace and land vehicle context
12:00 12:45 MAN5 Supply Chain Optimisation for Land Vehicles within Babcock International
13:30 14:15 MAN1 Linear actuator monitoring for enhanced productivity in vehicle assembly line
14:15 15:00 MAT9 Ultra-precision laser finishing
Room: LR3 Open presentation
Start Finish Project Title
09:15 10:00 MAN 7 Factory flow simulation and lean improvements
10:00 10:45 MAN10 Developing sustainable supply chains for UK manufacturing growth
11:15 12:00 MAN11 Shop floor simulation for continuous improvement in a pharmaceutical company
12:00 12:45 MAN12 Reconfigurable microfactories for future vaccines manufacturing
13:30 14:15 MAN8 Augmented reality to improve data usage and increase pilot plant capacity
14:15 15:00 MAN9 Developing the next generation of training at network rail
Room: LR5 Open presentation
Start Finish Project Title
09:15 10:00 MAN13 Industrial System Pen-Testing
10:00 10:45 MAN14 Towards Digital Aircraft Engineer and Paperless MRO
11:15 12:00 MAT1 Surface Integrity and Performance of Laser Peened Nickel-based Superalloy
12:00 12:45 MAT2 Quantifying Sintering Behaviour of Thermal Barrier Coatings at High Temperatures
13:30 14:15 MAT3 Photoluminescence thin films for improvement of solar photovoltaic performance
14:15 15:00 MAT4 Portable thermal conductivity testing rig for composites
Room: LR6 Open Presentations
Start Finish Project Title
09:15 10:00 MAT6 Radio Frequency Piezo Electric Tuning Element
10:00 10:45 MAT7 Wire plus arc additive manufacture (WAAM) of 15-5 PH stainless steel using Plasma arc process
11:15 12:00 MAT5 Development of graphene enhanced hydrogen pipelines
12:00 12:45 MAT10 Augmented Reality Equipped Composites Assembly
Room: LR6 Closed Presentations
Start Finish Project Title
13:30 14:15 MAN3 Demonstrating the benefit of Predictive Maintenance
14:15 15:00 MAT8 3D printing of latex gloves
Vijayragul VijayanAcademic background
2018 - 2019
2014 - 2018
Aerospace Manufacturing MSc, Cranfield UniversityB.E. Mechanical Engineering, Kumaraguru College of Technology, India
David Maqueda GomezAcademic background2018 - 2019
2012 - 2016
Engineering and Management of Manufacturing Systems MSc, Cranfield University Industrial Technologies Engineering, Antonio de Nebrija, Spain
Previous experience2017 - 2018 Deputy Project Manager, Escuela Tecnica
Superior de Ingenieros Industriales - UPM
2016 Researcher, Oficina Espanola de Cambio Climatico - Ministerio de Agricultura, Alimentacion y Medio Ambiente
Suxue Huang Academic background
2018 - 2019
2010 - 2014
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor of Engineering, Xiamen University, China
Previous experience2014 - 2018 Tooling designer, COMAC
Yu Xia Academic background
2018 - 2019
2014 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield University Bachelor of Engineering, Wuhan University of Technology, China
Previous experience2017 Manufacturing and Technology copywriter of
Automotive Team, Ogilvy & Mather Advertising Beijing
Eduardo Muñoz GalindoAcademic background
2018 - 2019
2012 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Polytechnic University of Madrid, Spain
Yuanfei ZhuAcademic background
2018 - 2019
2012 - 2016
Aerospace Manufacturing MSc, Cranfield University Bachelor of Science, Beijing Institute of Technology, China
Previous experience2016 - 2016
2016 - 2017
Exchange Researcher, Delft University of TechnologyEU Seller Support Associate, Amazon China
Quentin Le Corre Academic background2018 - 2019
2016 - 2019
Management and Information Systems MSc
Master degree in software engineering, ISEP, France
Previous experience2017 Full-stack developer, Hoolders
Xiaoyu Zhou Academic background
2018 - 2019
2007 - 2011
Aerospace Manufacturing MSc, Cranfield UniversityBachelor, Human University of Science and Technology, China
Previous experience2014 - 20192013 - 2014
Engineer, Aero Engine Corporation of ChinaEngineer, BYD Auto
(left to right) Quentin Le Corre, Eduardo Muñoz Galindo, Suxue Huang, David Maqueda Gomez, Xiaoyu Zhou, Yu Xia, Vijayragul Vijayan, Yuanfei Zhu.
Dr Cristobal Ruiz Carcel E: [email protected]: +44 (0)1234 75 5566
Team members
Supervisor
www.cranfield.ac.uk2019
0102030405060708090100
0
1
10
100
1,000
10,000
Pitting Health Condition & Maintenance Cost
SUM OF REPAIR COSTS (k £)
SUM OF PRODUCTION COSTS (k £)
SUM OF LABOUR COSTS (k £)
Health Condition
The Simulink model can mimic the kinematicand electronic behavior of rig. The figurebelow shows its position difference with rigas well as theoretical value.
Prof. Andrew Starr [email protected] Engineering Services Institute, SATM, Building 90Dr. Cristóbal Ruiz Cárcel [email protected] of Aerospace, Transport and Manufacturing, Building 90
Project SponsorJaguar Land Rover Limited
Linear actuator monitoring for enhanced productivity in vehicle assembly line
Jaguar Land Rover is aiming to implement Condition BasedMaintenance (CBM) to increase productivity, by monitoring therack-and-pinion linear actuator on marriage station, a machinefor joining car body and powertrain. Monitored data can beprocessed to indicate failure modes and degradation stages,which are vital for subsequent maintenance decision.
• Conduct Failure Mode Effect & Criticality Analysis (FMECA)• Rig Testing with selected failures seeded in• Digital Twin Simulation by building Simulink model• Cost Benefit Analysis in different degradation stages• Develop CBM detection algorithm & sensor selection
Background Objectives
System Modelling
Methodology
· Position· Loads· Time· Voltage· Failures
Cost AnalysisRig Testing
· Current · Velocity · Torque· Voltage · Position · Force
Conclusions
Stepper Motor
Rack & Pinion
Algorithm
CBM
Estimate system behavior of given conditions for different degradation
stages by digital twin simulation
Real-time signal acquisition andprocessing from
sensors implemented on machine
Cost estimation according to current
and subsequent health conditions to guide
maintenance
Condition Acquisition
Maintenance Scheduling
Cost Estimation
Cost Breakdown
Repair Costs
Production Losses
Labour Costs
The rig was tested under 116 conditions and537 sets of data including Current,Displacement, Acoustic and Vibration werecollected and analyzed.The Figure below shows the difference ofrack displacement of teeth breakage stage 6.
Rig Testing System Modelling Cost Analysis
Displacement Comparison
Jump Teeth
Position Result Conformity
Results
• On average, changing from correctivemaintenance to CBM can half themaintenance cost.
• Production loss is the majority of costwhen failure happens while it can beminimized if maintenance is scheduledin advance.
• According to test, vibration could detectfailures since early-stage. Displacementcan only detect late stages.
• Model simulation has good conformityof a less than 10mm’s absolute errorwith rig result in terms of displacement.
• Model simulation indicates thatexcessive load would cause severe dropdown during extension.
DegradationStages
0 1 2 3 4 5 6
1. Teeth Breakage
2. Spalling
3. Sand Contamination
4. Lack of Lubrication
FailureModes
HealthyCondition
At 5 different speed (only for healthy condition) and 5or 4 different loads (for all conditions)
Error never exceeds 10mm
cost k£ Health %
Failure Detected
Ideal Time for Maintenance(Min Yearly Cost)
Minimized due to maintenance scheduled in advance
Schedule Maintenance
Mr. Quentin Le Corre, Miss Suxue Huang, Mr. David Maqueda Gómez, Mr. Eduardo Muñoz Galindo, Mr. Vijayragul Vijayan, Mr. Yu Xia, Mrs. Xiaoyu Zhou, Mr. Yuanfei Zhu
Thibault MastromicheleAcademic background
2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield UniversityBachelor in Engineer, Institut SupErieur d’Electronique de Paris, France
Previous experience2018 Assistant Manager in IT, Henkel
Elisa PtakAcademic background2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield UniversityBachelor of Engineering, ISEP, Paris
Previous experience2018 Assistant Project Management IS, Henkel
Agnieszka Oginska Academic background2018 - 2019
Manufacturing Technology and Management MSc, Cranfield University
Pablo JolyAcademic background
2018 - 2019
2013 - 2017
Management and Information Systems MSc, Cranfield UniversityBEng in Industrial Technology Engineering, Polytechnic University of Catalonia (UPC-ETSEIB), Spain
Previous experience2016 2013 - 2016
R&D Engineer Intern, BC Nonwovens S.L.President, Club Faro Barcelona
Queen Great Academic background
2018 - 2019
2016 - 2018
Management and Information Systems MSc, Cranfield University
Business and Management with applied computing, University of Buckingham, UK.
Previous experience2018 2014 - 2016
Part time Business analyst, Victorian Renovations General Manager, HLBC
Chloe Gros Academic background2018 – 2019
2016 – 2019
Management and Information Systems MSc, Cranfield University
Engineering in Business Intelligence, ISEP,
Previous experience2018 Business Intelligence Intern at Natixis
(left to right) Queen Olajumoke Great, Chloe Gros, Pablo Joly, Thibault Mastromichele, Agnieszka Oginska, Elisa Ptak.
Dr Ahmed Al-shaab E: [email protected]: +44 (0) 1234 750111 x5622
Supervisor
Team members
www.cranfield.ac.uk2019
Supervisor : Dr. Ahmed [email protected] : Mohamed Khalil [email protected]
United Arab Emirates
Office 4, Al Muhairi BuildingAl Bada, DubaiP.O Box: 36023Tel: +971 4 2369096Fax: +971 4 2369096E-mail: [email protected]
Digitalised Solutions of Organisational Learning CapabilityMrs. Queen Great, Miss Chloé Gros, Miss Elisa Ptak, Miss Agnieszka Oginska,Mr. Thibault Mastromichele, Mr. Pablo Joly
Literature review Questionnaire & field study Data analysis OLC Framework Expert judgment
OLC Definition : Example of field study analysis :
• Synthesise the best practices of the organisational learningmodel and capability through literature review & field study.
• Develop a conceptual OLC framework based on digitaltechnologies.
• Facilitate employees’ learning through digitalised solutions.
Public service organisations provide different learning programsto their employees in order to enhance their skills and capabilitiesto provide better services. Digitalised solutions are enablingtechnologies that this research believes it would help inenhancing employees performances if they are incorporated.
Law enforcement & security Education Local authorities & social care Healthcare
Enhancing performance in public organisations could not be achieved without a formal initiative of OLC. The impactof learning can be enhanced significantly by employing digitalised solutions of the learning programs.
OLC is the facilitation of a process to ensure that theorganisation is learning from its operations and theexperiences of different projects and initiatives. Thislearning process is influenced by certain factors that aredirectly related to the performance of both employees andservice provision.
BACKGROUND AIM & OBJECTIVES
E- Learning digitalisedsolution example:
3,23 3,23 3,04 3,21 3,332,63
3,31
4,19
3,22 2,95
0,000,501,001,502,002,503,003,504,004,505,00
Which of the following challenges do you face in implementing digital technology in your learning processes?
IMPORTANCE
72%
14%
14%
WHAT IS YOUR ORGANISATION’S APPROACH TO USING DIGITAL LEARNING METHODS FOR
EMPLOYEES?Optional (15) Compulsory (3) Both (3)
ConceptualOrganisational Learning Capability Framework :
RESEARCH METHODOLOGY
CONCLUSION
Nicolas Lienhard Academic background
2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield UniversityDiplome D’ingenieur, ISEP, France
Previous experience2018 2017
Data scientist, AXA Global DirectProject Manager, MyCompanyFiles
Robin Kubler Academic background2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield UniversityEngineer’s degree, ISEP, France
Previous experience2018 Innovation Consultant, Capgemini
Abdullah Almutairi Academic background
2018 - 2019
2012 - 2016
Aerospace Manufacturing MSc, Cranfield UniversityBachelor’s of Engineering Technology, (Mechanical) College of Technology, Saudi Arabia
Previous experience2010 - 2018 Maintenance Planner, Saudi Electricity
Company
Clara Moussu Academic background2018 - 2019
2016 - 2019
Manufacturing Technology and Management MSc, Cranfield UniversityGeneral engineering, IMT Mines Ales, France
Previous experience2017
2018
Internship as laboratory worker, Koppers Performance ChemicalsInternship as assistant engineer, Jaguar Land Rover
Ashish Chathoth MeethalAcademic background
2018 - 2019
2012 - 2016
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor of Engineering (Mechanical), Savitribai Phule Pune University (Formerly University of Pune), India
Previous experience2016 - 2018 Jr. Engineer, Swan Mechanical Services Pvt.
Ltd.
Wei-Yu Lin Academic background2018 - 2019
2014 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering Management, Yuan Ze University, Taiwan (R.O.C.)
Dr Isidro Durazo Cardenas E: [email protected]: +44 (0)1234 75 5564
Supervisor
Team members
(left to right) Abdullah Almutairi, Ashish Chathoth Meethal, Robin Kubler, Nicolas Lienhard, Wei-Yu Lin, Clara Moussu.
Yousra Mkhinini Academic background
2018 - 2019
2017 - Current
Aerospace Manufacturing MSc, Cranfield UniversityBachelor of Engineering, IMT Mines Albi, France
Previous experience2018 Logistics Internship, Safran
Merwan AghaAcademic background
2018 - 2019
2016 - 2019
Aerospace Manufacturing MSc, Cranfield UniversityMechanical Engineering and Interactive Design, Polytech Montpellier, France
Previous experience2018
2017
Intern in Logistics Continuous Improvement, Daher AerospaceCommercial Employee, E. Leclerc
Jose de la PuenteAcademic background
2018 - 2019
2012 - 2016
Management and Information Systems MSc, Cranfield UniversityBEng in Industrial Technology Engineering, Polytechnic University of Catalonia, Spain
Previous experience2017 - 2018
2016 - 2017
Strategy and Operations Consultant, Deloitte Consulting
Project Management Office, Ricoh, Spain
Dominik Bulka Academic background
2018 - 2019
2014 - 2019
Manufacturing Technology and Management MSc, Cranfield UniversityAutomation and Robotics, Silesian University of Technology, Poland
2015 - 2016 Trainee Program at SAT, Production Department, Poland.
Marion LangloisAcademic background
2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield UniversityDigital engineer Specialised in embedded systems, Institut Superieur d’Electronique de Paris (ISEP), France
Previous experience2017 Internship - RAMS engineer, Safran Electronic
and Defense
Dr John ErkoyuncuE: [email protected]: +44 (0)1234 75 4717
Supervisor
(left to right) Merwan Agha, Dominik Bulka, Jose De La Puente, Marion Langlois, Yousra M’khinini.
Team members
www.cranfield.ac.uk2019
• Develop a scalable & flexible framework forthe design & development of a digital twin.
• Build a functional digital twin prototype for asystem integrated onto a modified mobileasset.
Babcock put technology at the core of theiractivities continually looking for innovations. Thusthey are focusing on developing digital twintechnology to extend their competencies in systemdesign, integration and support.
Digital Twin Representation of a Modified Mobile Asset in Aerospace Maintenance
Merwan Agha
Dominik Bulka
Marion Langlois
Yousra M’khinini
Jose de la Puente
MOTIVATION
Develop a framework tobuild a digital twin &demonstrate the impacts &benefits by applying it.
AIM OBJECTIVES
“A digital twin is an integrated multi-physics, multi-scale, probabilistic simulation of a complex product & uses the best availablephysical models, sensor updates, etc., to mirror the life of its corresponding twin.” (NASA, 2012)
WHAT IS A DIGITAL TWIN?
SUPERVISOR:
Dr. John Ahmet Erkoyuncu
RESULTS ANALYSIS
Log.txtLog.txtLog.txt
PHYSICAL ASSET
Log.txtLog.txtLog.txt
Log
Wi-Fi
PROTOTYPE
Legend
Digital World
Connection
Physical World
CameraMain
ComputerEthernetSwitch
Client Mission Computer Monitor
Internet
DIGITAL TWIN
“We are extremely impressed that the prototype could be adaptedand implemented on the actual system we were integrating onto amobile asset.”J. Sibon, Head of Research and Partnerships,S. Wedell, Technical Support Manager
QUOTE FROM BABCOCK
39
24
05
10152025303540
Scenario1 – Ethernet cable disconnection
Without
With
Literature review• Current practices & benefits• Future trends
Framework• What does a digital twin look like?• How is a digital twin built?
Requirements• Aim• Scope
Verification & Validation• Experiments & results analysis• Identification of benefits
Creation of the digital twin prototype• Development of the database• Development of the communication
Discussion• Feedback• Further works
METHODOLOGY
Babcock testers• Upgrade the panel to show
the source of the failure.• Find a way to make the
database more robust.
Cranfield testers• Display only the information
linked to the current situation.• Display a progress bar of the
data transmission status.
PANEL
30
16
45
35
7
2
Connected
Connected
Connected
16/04/19
VALIDATON FEEDBACKS
(in sec)
39% Reduction of time in scenario 1
89% User-friendliness of the digital twin 85% Data relevancy of
the digital twin
81% Reduction of time in scenario 2
96
18
0102030405060708090
100
Scenario 2 – CPU % usage too high
Without
With
(in sec)
Adrien Baily Academic background
2018 - 2019
2014 - 2017
Aerospace Manufacturing MSc, Cranfield UniversityBachelor’s degree in engineering sciences, Ecole Nationale supérieure des Mines de Nancy, France
Previous experience2018 Intern, Sonaca Group
Elodie Thai Thien Nghia Academic background
2018 - 2019
2014 - 2019
Aerospace Manufacturing MSc, Cranfield UniversityEngineer degree, ECAM-EPMI, France
Previous experience2017 - 2018 Engineer assistant, Thales
Pierre-Ly Pinault Academic background
2018 - 2019
2014 - 2018
Management and Information Systems MSc, Cranfield UniversityEngineering Master Degree, I.S.E.P, France
Previous experience2018 Intern Product Manager, PayinTech
David Bodin Academic background
2018 - 2019
2014 - 2018
Management and Information Systems MSc, Cranfield UniversityEngineering Master Degree, I.S.E.P., France
Previous experience2018 Project Manager, Atexo
Victor Penella BrossaAcademic background
2018 - 2019
2013 - 2017
Management and Information Systems MSc, Cranfield UniversityIndustrial Engineering, Universitat Politecnica de Catalunya (UPC), Spain
Previous experience2017
2016 - 2017
Supply Chain Intern, Auto1 Group
Operations & Quality Intern, Integra2
Dr John ErkoyuncuE: [email protected]: +44 (0)1234 75 4717
Supervisor
(left to right) Adrien Bailly, David Bodin, Victor Penella Brossa, Pierre-Ly Pinault, Elodie Thai Thien Nghia.
Team members
Supply Chain Optimisation Framework for a Service Provider
Mr Adrien Bailly Mr David Bodin Miss Elodie Thai Thien NghiaMr Victor Penella Mr Pierre-ly Pinault
www.cranfield.ac.uk
[email protected] [email protected]
Aim & Background Objectives
To provide an implementation framework for the optimisation of the supply chain to an asset management service provided by Babcock International. This framework guides the sponsor to find the best trade-off between maximising assets availability and minimising supply chain costs.
Conduct literature review to identify best practices in Supply Chain Management
Identify suitable use cases to optimise the existing supply chain
Establish the appropriate parameters against which the optimisation should be run
Create a through life optimisation framework
DEF
INE
MEA
SUR
EC
ON
TRO
LA
NA
LYSE
IM
PRO
VE
Demand management Procurement Supply Logistics
Accurate demand forecastForecast suppliers lead
timeBuy less (Minimum Order
Quantity)
Select adequate suppliersMaximise value for money
Maximise operations efficiency
Maximise assets availability
Decrease inventory costsIncrease inventory visibility
Increase demand forecastReduce downtime costs
Improve Just-In-Time
Decrease materials costsImprove supplier selection
Better value for money
Decrease service costIncrease asset uptime
Increase resilience
Reduce inventory levelDecrease inventory cost
Improve prediction
Document the new process:- Create a user guide & trainings
- Communicate the changes- Align changes to the company’s
standards
Validate the new process:- Continuously measure the solution
validity- Create a process monitoring plan:
(Agree on Frequency/procedure/manager)
Evaluate continuous improvement updates:
- Consider process transfer opportunities- Implement a permanent control plan/
updating system
Service Provider Supply Chain Optimisation Framework
Analytic Hierarchy Process;Decision-Making Trial and Evaluation Laboratory;
Preference Ranking Organisation Method for Enrichment of Evaluation;
Mathematical methods:Mixed Integer Programming;Linear Programming;Non Linear Programming;
Simulation methods:Discrete Event Simulation;
Agent Based Simulation;System Dynamics;
Service Provider
Storage
Maintenance & Repair
Suppliers
Customers
Through Life element
Solution / System engineering element
Demand Management element
Procurement / Macro Planning
Service Desk
Service Desk
Spare part request
Request for Service/MaintenanceCapability
requirementsPlanned maintenance
BOM/ fleet type
Customer specification
Vendor inventorySatellite storage facility
Safety stocks
Assets
Spares
Decommissions
Planned MROIn-house
Sub-contract
System provisions
Economic optimisation
Short-term hire
Contingency planning
Failure rateObsolescence
Logistics
Off the shelf
StoresInventory capacityStorage Systems
ConsumablesWorkshop equip.
Utilisation requirements
Unplanned MRO
Commissions Unplanned maintenance
Reactive maintenance
Repair/Replace/RefitBreakdown/Recovery
Availability requirements
SERVICE SUPPLY CHAIN MAPPING
Review
Monitor
Documentation
Plan
Implement
Tools
Structure
Decide
Method
Evaluate
Feature
KPI
Architecture
Illustrate
Profile
Supervisors: Dr John Ahmet Erkoyuncu Dr Maryam Farsi
2019
Contract constraints
Warranty
Economic KPI’s
Operational KPI’s Service KPI’s
Xiwen Zhang Academic background
2018 - 2019
2011 - 2013
Management and Information Systems MSc, Cranfield UniversityMaster of Applied Statistics, Xi’An JiaoTong University, China
Previous experience2013 - 2018 Engineer, AVIC
Sijing LiAcademic background
2018 - 2019
2005 - 2009
Engineering and Management of Manufacturing Systems MSc, Cranfield University
Bachelor of Arts, Northwestern Polytechnical University, China
Previous experience2009 - Current Engineer, Aviation Industry Corporation of
China,Ltd
Najib Usman ShehuAcademic background
2018 - 2019
2011 - 2014
Manufacturing Technology and Management MSc, Cranfield UniversityIndustrial Chemistry, Bayero University, Kano, Nigeria
Previous experience2018 Part-time teaching, School of Basic and
Remedial Studies, Ahmadu Bello University, Funtua
Zhili Yang Academic background
2018 - 2019
2012 - 2016
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor, Hunan University, China
Previous experience2016 - 2018 Overseas Account Manager, FiberHome
Technologies International Co.ltd.
Leo ComperatAcademic background
2018 - 2019
2016 - 2019
Manufacturing Technology and Management MSc, Cranfield UniversityMechanical Engineering, UTC - Universite de Technologie de Compiegne, France
Previous experience2017 - 2018
2016
Process assistant engineer, Ewabi
Test engineer assistant, Valeo
Dr Heather Almond E: [email protected]: +44 (0)1234 75 2020
Supervisor
(left to right) Leo Comperat, Sijing Li, Najib Shehu Usman, Zhili Yang, Xiwen Zhang.
Team members
Ryan D’SouzaAcademic background
2018 - 2019
2010 - 2015
Aerospace Manufacturing MSc, Cranfield UniversityBachelor of Mechanical Engineering, University College Dublin, Republic of Ireland
Previous experience2016 - 2018
2015
Manufacturing Engineer, Ohshima Ireland Ltd
Mechanical Design Engineering Intern, Ken-naMetal India Ltd
Zhiyue WanAcademic background
2018 - 2019
2011 - 2015
Aerospace Manufacturing MSc, Cranfield UniversityBSc, Nanjing University of Aeronautics and Astronautics, China
Previous experience2017 - 2018 Supply Chain Management Specialist, Damco
Pedro Manuel Calheiros da RochaAcademic background
2018 - 2019
2014 - 2019
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering and Management, University of Minho, Portugal
Previous experience2016 - 2018 Customer Service, Lidl & Cia
Asuncion Lopez ContrerasAcademic background
2018 - 2019
2012 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield University Industrial Engineering, Universidad Politecnica de Madrid, Spain
Peng Luo Academic background
2018 - 2019
2014 - 2020
Aerospace Manufacturing MSc, Cranfield University
Bachelor, XiangTan University, China
Previous experience
2014 - Current Engineer, AECC
Angelo BorreggineAcademic background
2018 - 2019
2014 - 2017
Management and Information Systems MSc, Cranfield UniversityBSc Management Engineer, Polytechnic of Bari, Italy
Previous experience2014 - 2017 Support for tender office employees, Pastore
S.r.l.
Rong Hu Academic background
2018 - 2019
2008 - 2012
Aerospace Manufacturing MSc, Cranfield UniversityBachelor, USTB, China
Previous experience2012 - 2018 Fixture Designer, AECC
(left to right) Asunción López, Angelo Borreggine, Pedro Manuel Calheiros Da Rocha, Peng Luo, Ryan D’souza, Alan Robic, Rong Hu, Zhiyue Wan.
Dr Konstantinos SalonitisE: [email protected]: +44 (0)1234 75 8347
Team members
Alan Robic Academic background
2018 - 2019
2016 - 2019
Management and Information Systems MSc, Cranfield UniversityTelecom & IoT Architect, ISEP Paris, France
Previous experience2018 System & Network Engineer, Beijaflore Paris
Supervisor
www.cranfield.ac.uk2019
Welding
Coke
LimestoneSteel Scrap
Cupola Melting Desulphurisation Electric Furnace
Mg
Metal Treatment
PatternPreparation Box Filling Squeezing Box Closing Pouring
Shakeout & Runner Removal
Shot-blastingFettlingDip coatingDispatch Assembly
Melting
Moulding
Finishing
3D WITNESS Model
Fabrication & welding
Fettling & paint-line
Assembly
Shakeout & shot-blasting
Dr. Konstantinos Salonitis // [email protected]
Dr. Emanuele Pagone // [email protected]
Prof. Mark Jolly // [email protected]
Factory Flow Simulation & Lean Improvements, Saint GobainMr. Alan Robic Mr. Angelo Borreggine Ms. Asunción López Contreras
Mr. Rong Hu Mr. Ryan D’Souza Mr. Pedro Calheiros da Rocha
Mr. Zhiyue Wan Mr. Peng Luo
PROJECT AIMS
• Reduce Work in Process (WIP) in the finishing area at the PAM Holwell foundry.
• Improve line balancing between moulding and finishing areas
• Investigate and research technology improvements in the finishing area of the foundry
OBJECTIVES• Create a virtual model of the facility, using
WITNESS simulation software
• Recommend Lean Improvements that aim to reduce WIP and improve day to day operations
• Based on research, recommend technological improvements to be used at the facility
Website : https://www.saint-gobain-pam.co.uk/
METHODOLOGY
- Project primarily focuses on the finishing area of the Holwell Foundry
- Finishing area consists of automated and manual operations
- Complete understanding into production practices, using value stream & process maps
- 77 Time measurements provided distribution for manual finishing processes
- Routing studies provided verification into travel time across the floor
- Pareto Analysis carried out on product range highlighted top 20% of product that made up 80% of volume processed
- Conceptual model created to verify understanding into production decisions
- Simulation model built in the following Work centre - based modules:
1: Problem Definition
2: Data Collection
3: Model Development
Holwell foundry process routes
o Mouldingo Shot-blast & Shakeouto Fettlingo Weldingo Paintingo Assembly
- Simulations show imbalance between manual and automated work-centres
- WITNESS provided a means to experiment with different layouts, moulding strategies & labour configurations to provide recommendations to improve balance between moulding & finishing areas
Results & Conclusions
Flavien TourtetAcademic background
2018 - 2019
2014 - 2018
Manufacturing Technology and Management MSc, Cranfield UniversityMechanical and Industrial Engineering, Arts et Metiers, France
Previous experience2018 Project Engineer Internship (Data-Analysis),
PSA Group
Juan RiviereAcademic background
2018 - 2019
2013 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Polytechnic University of Catalonia (ETSEIB), Spain
Previous experience2017
2011 - 2016
Project Management intern, HP Inc.
Team Leader, RPM Racing
Supriya GuptaAcademic background
2018 - 2019
2006 - 2010
Management and Information Systems MSc, Cranfield UniversityBachelor of Technology (B.Tech), SRM, India
Previous experience2015
2010 - 2014
Records Administration Assistant, NHS Foundation Trust
Test Analyst, Tata Consultancy Services Ltd
Yisen Fang Academic background
2018 - 2019
2009 - 2013
Engineering and Management of Manufacturing Systems MSc, Cranfield University
Pharmaceutical Engineering BEng, Guangdong Pharmaceutical University, China
Previous experience2013 - 2018 Project Manager and Office Administrator,
Guangzhou Baiyunshan Tianxin Pharmaceutical Co. Ltd.
Xin Wang Academic background
2018 - 2019
2012 - 2016
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Nanjing Agricultural University, China
Previous experience2018
2018
Lean consultant assistant, Engineering-Academy Enterprise management consulting Co Ltd. Supply chain internship, B/S/H China
Matthieu Favrot Academic background
2018 - 2019
2014 - 2019
Management and Information Systems MSc, Cranfield University
Information Systems, ISEP, France
Previous experience2018
2018
Internship, SMA BTP
Internship, Addictgroup
Dr John ErkoyuncuE: [email protected]: +44 (0)1234 75 4717
Supervisor
Team members
(left to right) Yisen Fang, Matthieu Favrot, Supriya Gupta, Juan Riviere, Xin Wang, Flavien Tourtet.
www.cranfield.ac.uk2019
Supervisor: Dr. John Erkoyuncu - Email: [email protected]: Iñigo Fernández del amo blanco - Email: [email protected]
AR to Improve Data Usage in Manufacturing SettingsMs Supriya Gupta. Ms Xin Wang Mr Matthieu FavrotMr Yisen Fan Mr Flavien Tourtet Mr Juan Rivière
The widespread use of the Internet has supported the creation of “SmartFactories”, which have led to the digitalisation of processes. It has caused thecreation of abundant and dynamic data which has made interpretation moredifficult. AR can help humans to use this data for faster product developmentand more production. (Image 1)
1. BACKGROUND
1) Increase Efficiency 2) Improve Visualisation
• Saving the time an operator spends on a process
• Performing a task in less timewithout impacting the quality
• Real-time data will provide better control over parameters
• Visualise the data in user-friendly way
3. PROJECT OBJECTIVES
6. APPLICATION SYSTEM ARCHITECTURE
5. CONCEPTUAL MODEL4. METHODOLOGY
Identify problems AR system design AR application development Validation
• Manufacturing process analysis
• AR functions research
• On-site visits• Applications
proposal• Application
selection
• Software & hardware selection
• Conceptual model
• Use case• Story map
• AR application prototype
• Verification (Image2)
• Perform trials (Image3)
• Efficiency: program flow analysis of the trials
• Use satisfaction: questionnaire
Phase 1 Phase 3Phase 2 Phase 4
Image 2: Verification on-site
2. PROJECT AIM
Image 3: View of the application
Image 1: AR Interaction
8. CONCLUSIONS
7. RESULTS⚫ Information visualisation
Better process control: a quick overview of the process
Optimisation of operational procedures: reduce unnecessary WALKING time
⚫ Improve traceability: record information indigital way
⚫ High user satisfaction from users
⚫ A starting point for a change of culture within the company To become more engaged with new data-driven ways of
working To introduce an application with high user satisfaction
⚫ Better use of augmented reality in the future Scale-up the application system to the whole pilot plant Apply AR system in commercial factory
TRY AR
Developing an AR app to visualise real-time data of an ice cream pilot plant⚫ to help the employees to make more data-driven decisions⚫ to increase efficiency and productivity
Oyin Yusuff Academic background
2018 - 2019
2015 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBEng (Hons) Mechanical Engineering, University of Derby, England
Previous experience2018
2016 - 2018
Script Viewer and Internal Queries Supervisor, DRS Data Services Limited, England Programme/Student Representative, University of Derby, England
Mulanga Rosalie TshimangaAcademic background
2018 - 2019
2014 - 2017
Management and Information Systems MSc, Cranfield UniversityBA Business & Management, University of Northampton, United Kingdom
Previous experience2017 - 20182018 - Current
Team Leader/Men’s Department Manager, ClarksNational Sales Executive, Deltic Group
Luis Azana Academic background
2018 - 2019
2012 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Universidad de Sevilla, Spain
Previous experience2018
2017
Engineer Jr., Befesa
Intern, ATI
Michael Jason SolisAcademic background
2018 - 2019
1995 - 2001
Manufacturing Technology and Management MSc, Cranfield University
BSc Applied Physics major in Instrumentation, University of the Philippines - Los Banos, Philippines
Previous experience2001 - Current Supervising Science Research Specialist,
Industrial Technology Development Institute - National Metrology Laboratory of the Philippines
Chelsea Camilo MonteiroAcademic background
2018 - 2019
2014 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield University
BTech Electronics and Communication Engineering, Manipal Institute of Technology, India
2018
2018
Technical Support Analyst, Virgin Media BusinessWork experience placement, Top Hex Ltd.
Suphanvipha SaydaungAcademic background
2018 - 2019
2013 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield University
BEng Production Engineering, King Mongkut’s University of Technology North Bangkok, Thailand
Previous experience2017 Production engineer, SCS Fabrication.co.,ltd
Dr John ErkoyuncuE: [email protected]: +44 (0)1234 75 4717
Supervisor
Team members
(left to right) Chelsea Camilo Monteiro, Luis Azana, Suphanvipha Saydaung, Michael Jason Solis, Mulanga Rosalie Tshimanga, Oyinkansola Yusuff.
www.cranfield.ac.uk2019
Academic Supervisors:
Dr. John Ahmet Erkoyuncu
Building 30, Cranfield University
Mr. Samuel Court
Building 30, Cranfield University
Developing the Next Generation of Training for Network Rail
Luis Azana, Chelsea Camilo Monteiro, Suphanvipha Saydaung, Michael Jason Solis, Mulanga Rosalie Tshimanga, Oyinkansola Yusuff
AIM
RESEARCH METHODOLOGY
CONCLUSION
RESULTS
BACKGROUNDNetwork Rail employees undergosafety training to empower them todo their jobs efficiently and safely,yet there were incidents wheresafety protocols were ignored.Network Rail is exploring how newtechnological innovations could beutilised to improve the effectivenessof trainings and behavioural safety.
To guide Network Rail withassessing how ‘newtechnological innovations’could be used in increasingproductivity and efficiencywhen delivering training toimprove their employees’behaviours, actions anddecisions.
OBJECTIVES Investigate new technological innovations for training. Analyse the current training processes, strengths,
challenges, opportunities and gaps at Network Rail. Identify and evaluate which new technological innovation is
appropriate for delivering training that complies with training requirements and addresses target behaviours. Prioritise technological opportunities through the
development of a Return on Investment type toolkit. Validate the research findings in the Network Rail context.
Literature Review Interviews Data Analysis Outcomes ConclusionNon-Participant Observations
This project has successfully provided Network Rail with the means of assessing how ‘new technological innovations’ could be usedin increasing the productivity and efficiency when delivering training to improve the workforce’s actions, behaviours and decisionsthrough the development of a Report of New and Existing Technologies, Framework for Introduction of Technologies to Trainingand a Return on Investment Type Toolkit based on the Phillips ROI Methodology.
New and Existing Technologies in Training
Augmented Reality
Virtual Reality
Machine Learning
Gamification
E-Learning
Framework for Introduction of Technology to Training
Return on Investment Type Toolkit based on Phillips ROI Methodology
1. Evaluation Planning
2. Data Collection
3. Isolate Effects of Solution
4. Convert Data to Monetary Value
6. Capture Costs of Solution
7. Calculate the Return on Investment
5. Identify Intangibles
8. Reporting
Industry Sponsor:
“These are the kind of deliverables we were seeking when we assigned the group project, and I believe they willhelp support Network Rail Training in our review of future training and our ambitions to keep our people safe”
Michelle Nolan-McSweeney, Head of Training Strategy, Network Rail
Identify Parts of the training
Understand the Training Requirement
Map the Behaviourswith the Training
Requirements
Map the Training Requirements with the
Technologies
Rank the Technology Selection Criteria using Analytical
Hierarchical Process
Rank the Technologies using Analytical
Hierarchical Process for Each Criterion
Select the Technology with Highest Score
1 2
3 4
5 6
7
Matteo GregoriAcademic background
2018 - 2019
2010 - 2015
Management and Information Systems MSc, Cranfield UniversityMechanical Engineering, La Sapienza University of Rome, Italy
Previous experience2016 - 2018 Automation analyst/developer, Automate
s.r.l.
Benjamin Miller Academic background
2018 - 2019
2014 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityMechanical Engineering with Industrial Year, Aston University, United Kingdom
Previous experience2017 - 2018
2016 - 2017
Manufacturing Summer Internship (X2), Rolls-Royce PlcMechanical Engineering Student Engineer, Cummins Inc
Srujil Vivek Saraf Academic background
2018 - 2019
2009 - 2012
Aerospace Manufacturing MSc, Cranfield University
Bachelor’s degree in Mechanical Engineering, Marathwada Institute of Technology, India
Previous experience2014 - 2018
2012 - 2013
Junior Executive, Tata Advanced Systems Ltd
Graduate Apprentice Trainee, Mahindra and Mahindra Ltd
Anli Liu Academic background
2018 - 2019
2009 - 2013
Global Product Development and Management MSc, Cranfield UniversityBachelor of Engineering, China
Previous experience2013 - Current Market development business manager, AVIC
Sadeq Al MeaibedAcademic background
2018 - 2019
2011 - 2016
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityChemical and Biological Engineering, Colorado State University, USA
Previous experience2016 - 2017
2017 - 2018
Technical Sales Engineer, IGES
Medical Delegate, Nestle
Dr John PatsavellasE: [email protected]: +44 (0)1234 75 4589
Supervisor
(left to right) Sadeq Al Meaibed, Matteo Gregori, Anli Liu, Benjamin Miller, Srujil Vivek Saraf.
Team members
www.cranfield.ac.uk2019
Mr. John PatsavellasEmail: [email protected]
Developing sustainable supply chains for UK Manufacturing growthAnli LiuBenjamin MillerMatteo Gregori
Sadeq Al MeaibedSrujil Vivek Saraf
OBJECTIVES▪Conduct a literature review of UK Manufacturing supplychains.▪Lead structured interviews with supply chain experts.▪Perform a qualitative analysis of literature and interviews.▪Present findings in the form of a White Paper for theNational Manufacturing Debate 2019.
METHODOLOGY
AIM The aim of the project is to outline a Supply ChainEcosystem and the actions required to enable thesustainable growth of UK supply chains.
Literature Review Data Collection Data Analysis Result
AI
•120 papers reviewed •6 structured Interviews •Qualitative analysis using Nvivo
⚫ Key Findings
Collaboration: Lack of awareness among businessleaders of the benefits of collaboration and how toimplement it.
Technology: Leadership fears of new technology andthe risks it can bring to the supply chain if notimplemented correctly.
Finance: Issues around late payment and extendedpayment terms resulting in reduced resilience throughthe supply chain
•Final recommendations•White paper
⚫ Recommendations
PartnerCompetitor
Community
Government
Institution
SMEsOrchestrator
SCE
389
650
769
1263
1950
R&D
Education
Collaboration
Technology
Finance
⚫ Topics Identified from Literature Review ⚫ Qualitative Analysis of interviews
It is our recommendation that an ecosystem isdeveloped to encourage sustainable UK manufacturingsupply chains. Government involvement in developingthe ecosystem is fundamental and should facilitate theunderlying infrastructure, policies and skills needed.Collaboration, finance and technology are the keyenablers to promote more resilient, responsive,sustainable and productive supply chains. Theorchestrating and monitoring of this new ecosystem canbe made possible through a central control tower.
The Ecosystem of Success
Eng Chuan OoiAcademic background
2018 - 2019
2011 - 2015
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor of Engineering (Electrical-Electronics), Universiti Teknologi Malaysia, Malaysia
Previous experience2015 - 2018 Failure Analysis Technology Development
Engineer, Intel Corporation2014 Intern (Quality & Supply Chain Engineer), Myreka
Technology
Juan Antonio Just AmargósAcademic background2018 - 2019
2013 - 2017
Management and Information Systems MSc, Cranfield University
Industrial Engineer, UPV, Spain
Previous experience20182017 - 2018
CEOs Assistant, Cerium Technologias SL Regional Sales Person Coordinator, B the Travel Brand (WAY)
Salma El AkraaAcademic background2018 - 2019
2014 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityGeneral Engineering, SeaTech, Engineering School of the University of Toulon, France
Previous experience2018
2017
Consulting Engineer, SLEFTY Medical Secretary in the radiology department, Hospital of Montsouris
Ludovico BarsottiAcademic background
2018 - 2019
2014 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBSc (Hons) Industrial Engineering, Pisa University, Italy
Previous experience2017 - 2018
2015 - 2017
Part Time Internship focused on Operations and Research, Pisa UniversityPresident of Gestionali in Opera student association, Pisa University
Alessandra CaradonioAcademic background2018 - 2019
2014 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Politecnico di Bari, Italy
Previous experience2018
2018
Junior Network Engineer, Enel S.p.A.
Business Process Management Consultant, Roboze S.r.l.
Fabio Lanave Academic background
2018 - 2019
2014 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityIndustrial Engineering, Polytechnic of Bari, Italy
Previous experience2018
2017
Business Process Management Consultant Project, ROBOZE s.r.l.Internship as Warehouse Engineer, BFP Group
(left to right) Salma El Akraa, Michela Lanotte, Ludovico Barsotti, Pedro De Jesus Sanchez Martinez, Alessandra Caradonio, Juan Antonio Just Amargós, Fabio Lanave, Eng Chuan Ooi.
Dr Konstantinos SalonitisE: [email protected]: +44 (0)1234 75 8347
Team members
Michela LanotteAcademic background
2018 - 2019
2013 - 2017
Engineering and Management of Manufacturing Systems MSc, Cranfield University
Industrial Engineering, Polytechnic of Bari, Italy
Previous experience20172018
Intern in work safety, Municipality of Matera BPM analyst, Bari Pharmacy
Pedro de Jesus Sanchez Martinez Academic background
2018 - 2019
2011 - 2015
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityMechatronics Engineering, University of Technology of Altamira, Mexico
Previous experience2018 - 2019
2015 - 2018
Lean Project Manager & Consultant, Lima Lama PanucoAdvanced Process Engineer, DENSO
Supervisor
www.cranfield.ac.uk2019
Dr Kostantinos Salonitis ([email protected]) Dr Emanuele Pagone ([email protected]) Building 50, Cranfield University, Cranfield, Bedfordshire
Shop floor simulation for continuous improvement in a Medical Device Company
Project AimThe aim of this project is to develop a strategy to increase the capacity of Sterifill and increase the efficiency throughthe reduction of the downtime of Physioject with the support of a discrete event simulation software (DES).
Data Collection Process Maps Physioject Sterifill
Modelling
Root Cause AnalysisWaste Identification
Strategy
Total Downtime/Cause
Ste
rifill
Phy
sioj
ect
Validation
Verification
What if ScenariosE a s e o f I m p l e m e n t a t i o n
Ou
tpu
t/E
ffic
ien
cy
Scenarios:SterifillPhysioject
Stopwatch
Database
Interview
Low
Sub
-Ass
embl
yTo
p Su
b-As
sem
bly
High wasteMiddle wasteLow waste
Increase the Cycle
Time
Increase Labour
Improve Worst Station
Increase Preventive
Maintenance
Doubling Moulding MachineIncrease
Moulding Cavities
50% Breakdown Reduction Moulding
Constraints Elimination
Difficult Easy
High
Low
Mr Ludovico Barsotti, Miss Alessandra Caradonio, Miss Salma El Akraa,Mr Juan Antonio Just Amargos, Mr Fabio Lanave, Miss Michela Lanotte, Mr Eng Chuan Ooi, Mr Pedro de Jesus Sanchez Martinez
Pacing Inventory
Level Definition
Zhao Yang Academic background
2018 - 2019
2007 - 2011
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor of Mechanical Engineering, Northwestern Polytechnical University, China
Previous experience2014 Manufacturing engineer, AVIC FACRI
Jingjing WangAcademic background
2018 - 2019
2006 - 2010
Aerospace Manufacturing MSc, Cranfield UniversityBachelor, Beihang University, China
Previous experience2010 - 2019 Engineer, Aviation Industry Corporation of
China, Ltd.
Xiaochen Liu Academic background
2018 - 2019
2009 - 2013
Engineering and Management of Manufacturing Systems MSc, Cranfield UniversityBachelor Degree, Xi’ an Polytechnic University, Xi’an
Previous experience2013 Engineer, Aero Engine Corporation of China
Adrien De SoultraitAcademic background
2018 - 2019
2014 - 2019
Global Product Development and Management MSc, Cranfield University
Automotive mechanical engineering (double degree), ESTACA, France
Previous experience2018 Purchasing engineer Assistant, Treves PSI
Daheng (David) Zhao Academic background
2018 - 2019
2015 - 2018
Engineering and Management of Manufacturing Systems MSc, Cranfield University
Bachelor of Science in Mathmatics, Aberystwyth University, United Kingdom
Daniel Simon JimenezAcademic background
2018 - 2019
2012 - 2015
Global Product Development and Management MSc, Cranfield University
Industrial Engineering, Universitat Politecnica de Catalunya, Spain
Previous experience2017 Logistics and Engineering Intern, Autoneum
Automotive
Prof Harris MakatsorisE: [email protected]: +44 (0)1234 75 8284
Supervisor
Team members
(left to right) Xiaochen Liu, Adrien De Soultrait, Md Salahuddin Shahed, Daniel Simon, Jingjing Wang, Zhao Yang, Daheng (David) Zhao.
Md Salahuddin Shahed Academic background
2018 - 2019
2000 - 2005
Engineering and Management of Manufacturing Systems MSc, Cranfield University
BSc in Mechanical Engineering, Bangladesh University of Engineering and Technology (BUET), Bangladesh
Previous experience2015 - 2018
2013 - 2015
Manager, GSK Production System (Continuous Improvements), GlaxoSmithKline Bangladesh Ltd Operational Excellence (H&S) Specialist, Chevron Bangladesh
www.cranfield.ac.uk2019
3D printed maskusing softlithography(SLA printing)
Professor Harris Makatsoris Email: [email protected] of Aerospace, Transport & Manufacturing
Reconfigurable Micro-factories for Future Vaccines Manufacturing
To design and demonstrate a reconfigurable modularmicro-factory for vaccines manufacturing.
• Develop concepts of a reconfigurable micro-factory
• Build a prototype with suitable flow and filtrationtechniques & testing
Due to increasing threats by emerging pathogens, there is an urgent needfor vaccines manufacturing by using RNA platform. Our study part of theEPSRC future vaccines manufacturing hub focusing on making vaccinesaccessible to everyone especially for LMIC(low and medium incomecountries) countries by dropping the price at a $1/dose. This is a novelemerging technology and it shall be suitable for fast response to potentialepidemics and emergencies at any circumstances.
Mr. Daniel Simon Jimenez Miss Xiaochen Liu Mr. Shahed Md Salahuddin Mr. Adrien de Soultrait Miss Jingjing Wang Mr. Zhao YangMr. Daheng Zhao
AIMS & OBJECTIVES
METHODOLOGY
BACKGROUND
FURTHER WORK • Build and test a continuous flow system with integrated recycling channels• Appropriate design of filtration processes and testing in the laboratory
with reference samples• Validating the microfluidics calculated data by the experimentation in the lab• Building the automatic control system to control the pump
CONCEPTDESIGN
PLATFORM INTEGRATION
Bioreactor 1Length (m) 2.5Pressure Drop (Pa) 61.43Velocity (m/sec) 0.0001Residence Time (min) 417
TFF1Length (m) 1Pressure Drop (Pa) 85.99Filtrate Volume (ml/hr) 5
Bioreactor 2Length (m) 1.2Pressure Drop (Pa) 115.47Residence Time (min) 200
TFF2Length (m) 1Pressure Drop (Pa) 341.92Filtrate Volume (ml/hr) 10
CFD analysis verifies the calculated data according to the velocity profile in the microchannels. Both negative and positive data represents the directional flows.
UV/Vis absorption spectra of samples
CAD design for whole microfluidics chip
PH Calibration and real-time monitoring
Python reads the Arduino andOcean Optics spectrometer data
RESULTS
Vertical Tangential Flow FiltrationThe RNA goes though the top channel and the smallmolecules are filtered down. Those expensivereagents are pushing back to the reactor thanks torecycling channel
By applying PDMSover the mask andbaking it, the PDMSreactor is ready
Samples with different colours areintroduced in the chip, mixingeffectiveness, PH and absorbancecan be obtained.
Experimental Integrated Platform Design
MICRO-FLUDICS
ANALYSIS
PROTOTYPEBUILDING
Data analysis (RNA yield VS Mg2+)& Optimum reaction time selection(Shattock Group at Imperial College)
A B C D
Schematic of the continuous RNA production
TESTING
Flat sheet membrane
PDMS
REFERENCES• http://www.imperial.ac.uk/future-vaccine-hub/about-us/• https://ieeexplore.ieee.org/abstract/document/6487168/references#references
Amaury Boxberger Academic background
2018 - 2019
2014 - 2016
Management and Information Systems MSc, Cranfield University
Bachelor’s degree in Business Intelligence, Institut SupErieur d’Electronique de Paris (ISEP), France
Previous experience2018 Data analyst, Enedis
Max BradfordAcademic background
2018 - 2019
2016 - 2019
Management and Information Systems MSc, Cranfield University
Network security architect engineer, ISEP, France
Previous experience2018
2017
Associate Network Engineer, Autodesk
Development and implementation of cybersecurity tools internship, Thales Communications and Security
Theo DrousiotisAcademic background
2018 - 2019
2014 - 2018
Cyber Secure Manufacturing MSc, Cranfield UniversityBSc Computer Science, University of Nicosia, Cyprus
Previous experience2017 - Current
2017
Web Developer, Health Care Training Ltd, Nicosia, Cyprus
Lab Assistant Software Issue Solver - IT support, University of Nicosia
Alexandre Misson Academic background
2018 - 2019
2016 - 2019
Cyber Secure Manufacturing MSc, Cranfield UniversityEngineering and Management of Complex Systems, School Mines d’Ales, France
Previous experience2017
2018
Feasability study and organisational guidance, Catheram Competition, France
Monitoring of physical health (Data Science), Escola Superior de Tecnologia | Instituto Politecnico de Castelo Branco (Portugal)
Zexuan (Josh) FanAcademic background
2018 - 2019
2009 - 2013
Cyber Secure Manufacturing MSc, Cranfield UniversityBEng, Nanjing University of Aeronautics and Astronautics, China
Previous experience2013 - 2018 Engineer, COMAC
Dr Hongmei HeE: [email protected]: +44 (0)1234 75 8206
Supervisor
(left to right) Amaury Boxberger, Max Bradford, Theofylaktos Drousiotis, Zexuan (Josh) Fan, Alexandre Misson.
Team members
www.cranfield.ac.uk2019
Dr Hongmei He, [email protected] Zakwan Skaf, [email protected] Saba Al-Rubaye, [email protected] Paul Theron, [email protected]
CySMIC
Industrial System Pen-Testing
Amaury Boxberger, Max Bradford, Theo Drousiotis, Josh Fan, Alexandre Misson
g
Cybersecurity of industrial systems has become a paramount concern for all organisations across every industry. Most of industrialsystems are legacy systems that have been designed a long time ago without any consideration for cyber security. Consequently the needfor more secure and easier to defend industrial systems is pressing. Failing that can have huge harmful consequences on a enterprise orcountry’s infrastructure.
Background
Attack demonstration
One way of improving Industrial Automation & Control Systems’ cybersecurity is to perform pen-testing on a test rig, disconnected fromreal systems and realistic in terms of architecture, equipment and functionality. The objectives are to identify and exploit vulnerabilities ofthe test rig, thus to provide solutions and countermeasures to real life cyber attacks to secure SCADA systems. To implement the goal,three types of attacks, a remote attack, a direct attack and malware infection, are performed to demonstrate the penetrability of thesystem with vulnerabilities.
Aim & objectives
Tools
Architecture
Layout of the Aircraft Fuel System Rig
Methodology
Guan Hong Yap Academic background
2018 - 2019
2004 - 2008
Management and Information Systems MSc, Cranfield University
Bachelor of Electrical Engineering, National University of Singapore, Singapore
Previous experience2010 - Current
2008 - 2010
Field Engineer, Singapore Technologies Engineering Aerospace Ltd
Electrical Engineer, Panasonic AVC Networks Singapore Pte Ltd
Jinghui Wang Academic background
2018 - 2019
2012 - 2016
Aerospace Manufacturing MSc, Cranfield University
Bachelor, Shenyang Aerospace University, China
Previous experience2016 - 2018
2015 - 2016
Assistant Engineer, Chinese Aerospace Science and Industry Corporation Intern, Shenyang Aircraft Manufacturing Corporation
Chengwei Wang Academic background
2018 - 2019
2014 - 2018
Aerospace Manufacturing MSc, Cranfield UniversityBEng (Hons) Mechanical Engineering Technology, University of Greenwich, United Kingdom
Previous experience2017
2015 - 2016
Research Assistant, Natural Resources Institute
Mechanic, Specialized Elite Store, Yancheng, China
Tany Moses IsukapatlaAcademic background
2018 - 2019
2013 - 2017
Aerospace Manufacturing MSc, Cranfield UniversityB.E Aeronautical Engineering, Sathyabama University, India
Dr Ip-Shing FanE: [email protected]: +44 (0)1234 75 5651
Supervisor
(left to right) Tany Moses Isukapatla, Chengwei Wang, Jinghui Wang, Guan Hong Yap.
Team members
www.cranfield.ac.uk2019
56
21
0 01
01234567
Num
ber o
f per
son
Working Field
Working field of the participants
0
1
2
3
4
5
6
20-29 30-39 40-49 50 and above Unknown
Num
ber
Age range
Age range and gender of the participants
Gender F
Gender M
Dr Ip-Shing, [email protected]
Towards Digital Aircraft Engineer and Paperless MRO
Introduction
Aim & Objective
Methodology
Results & Outcomes
Analysis
Conclusion Future Works
• First trial aims to gather feedback on the use of HMT-1and the available technical content in device
• 10 participants from Boeing Apprenticeship Programme
Feedback on Usefulness of HMT Feedback on Quality of Information
• First trial:• Feedback on device and associated content have been
positive• Wearable device has the potential to improve current
aircraft maintenance practices• Second trial:
• Feedback was negative• Experienced engineers are familiar with pre-flight checks,
the trial scenario more appropriate for apprentice training• Wearable technology could be beneficial in real-life
maintenance for complex and unfamiliar scenarios withcommunication support from remote engineer(s)
Cengiz [email protected]
• Second trial aims to evaluate the feasibility of thetechnology and potential opportunity in real maintenanceenvironment with a group of experienced engineers.
• 15 participants from Human Factors in AviationMaintenance Course
Demographics on the participants1
2
3
4
5
1 2 3 4 5
0
5
4
11
1-easy 2 3-average 4 5-difficult
Helpfulness of technology compared to paper manuals
Difficulty to understand instructions
• Aircraft Engineers spend unproductive hourson redundant tasks
• High volume of paper documentation
Aim – To improve work efficiency and support e-documentation of current aircraft maintenanceObjective – Explore wearable device (HMT-1) in realistic MRO context using Cranfield’s 737-400
• Relatively high acceptance of wearable device• Technology could improve work efficiency, but need to be
utilised in the right work tasks• Investment in organisation learning and process changes is
substantial
• Integrate Remote Expert to provide further assistancewhen complex problems are detected on-site
• Integrate with MRO ERP to acknowledge task completionby digital signature
• Integrate AR technology with Digital Twin to facilitate taskexecution and error detection
Learning hardware &
software
Trial Design
Data Collection
Trial Execution
Data Analysis
Product Improvement
Extract of WorkfloPlus
Interface of HMT-1
Scenario is representative of the pre-flight check before aircraft despatch
Mr Guan Hong Yap, Mr Chengwei WangMr Jinghui Wang, Mr Tany Moses Isukapatla
Alice GrégoireAcademic background
2018 - 2019
2014 - 2018
Advanced Materials MSc, Cranfield University
Bachelor degree in Mechanical and Industrial Engineering, Arts et Metiers ParisTech, France
Previous experience2018
2016
Assistant Design Office Engineer Intern, SACATEC Group (Technical Rubber Company) Senior Technician Intern, French Aternative Energies and Atomic Energy Commission (CEA)
Rafael Ruiz Iglesias Academic background
2018 - 2019
2014 - 2018
Advanced Materials MSc, Cranfield University
Materials Engineering BSc, Universidad Politecnica de Madrid (UPM), Spain
Previous experience2018
2017
Research internship, Institute of Ceramic and Glass (ICV)Research internship, Institute of Materials Science (ICMM)
Aabid Husen Hakeem Academic background
2018 - 2019
2013 - 2017
Aerospace Materials MSc, Cranfield University
Aeronautical Engineering, Srinivas Institute of Technology, India
Previous experience2017 - 2018
2015
Editor in Chief, Evening Times
Intern, Hindustan Aeronautics Limited
Thijaya Sumoreeah Academic background
2018 - 2019
2015 - 2018
Aerospace Materials MSc, Cranfield UniversityBEng Aerospace Engineering, Kingston University, United Kingdom
Previous experience2017 - 2018
2014
Clearing Hotline Agent, Kingston University
Intern, Inmarsat
Yuliya HryshchenkoAcademic background
2018 - 2019
2011 - 2017
Aerospace Manufacturing MSc, Cranfield UniversityBSc Aerospace Engineering, Polytechnic University of Madrid (UPM), Spain
Previous experience2017 - 2018
2016 - 2017
MRO Maintenance Engineer at A400M Retrofit, CT Engineering at AIRBUS D&S Military (Barajas and Getafe, Spain)
Manufacturing Engineer, CT Engineering at AIRBUS Operations (Illescas Plant, Madrid, Spain)
Dr Nicolau MorarE: [email protected]: +44 (0)1234 75 8210
Supervisor
(left to right) Alice Grégoire, Aabid Husen Hakeem, Yuliya Hryshchenko, Rafael Ruiz Iglesias, Thijaya Sumoreeah.
Team members
www.cranfield.ac.uk2019
SupervisorsDr. Nicolau Iralal Morar - [email protected]. John Nicholls - [email protected]. Simon Gray - [email protected]. Grant Gibson - [email protected]
Surface Integrity of a Laser Shock Peened Single Crystal CMSX-4®Nickel-based SuperalloyAabid Husen Hakeem, Alice Grégoire, Rafael Ruiz Iglesias, ThijayaSumoreeah, Yuliya Hryshchenko
Aim: To investigate surface integrity of a laser shock peened without coating single crystal CMSX-4® nickel-based superalloy for turbine blade root application. Objective: To evaluate the surface and subsurface characteristics of laser peened CMSX-4® treated with three different laser power densities (4, 7 and 10 GW/cm2), before and after thermal exposure at 700°C for 50 hours.
Typical range of temperatures and damages onthe surface of a HPT Blade
Ref: Darolia R. Development of strong, oxidation and corrosion resistant nickel-based superalloys: critical review of challenges, progress and prospects. International Materials Reviews. 2018; 6608. Available at: DOI:10.1080/09506608.2018.1516713
Aim and objective
Methodology
Microstructural changesSurface topographyDislocation densityHardness distributionResidual stress distribution
Laser shock peening can be used to induce deeper surface compressive residual stress in the work piece than other conventional surfacetreatment processes Combined with the generated dislocation density, it improves fretting, fatigue and stress corrosion crackingresistance. It offers a promising approach for high temperature corrosion-fatigue damage mitigation on the turbine blades root region.
▪ Microstructural changes on sample subjected to 10 GW/cm2 had the most severe effect showing an oxide and recast layer.▪ After thermal exposure, recrystallisation and an oxide layer have been found in all samples.▪ The dislocation density increases in the peened surface with power densities 4 and 7 GW/cm2, and declines at higher values.▪ The surface roughness increases with respect to laser power density rise and reduces after thermal exposure.▪ The compressive residual stress is maximum in the near surface layer with power density 7 GW/cm2.▪ A significant part of beneficial surface compressive residual stress has been retained after thermal exposure for all LSP samples.▪ All LSP samples exhibit an improvement in hardness before and after thermal exposure.
Conclusions
Background
▪ Microstructural changes by Scanning Electron MicroscopyResults
▪ Microhardness by Vickers testing machine
▪ Surface topographyby Interferometry
▪ Dislocation densityby X-Ray diffraction
▪ Residual Stress by Central Hole Drilling
50 µm
a
5 µm
b𝜸𝜸′
𝜸𝜸
(a) 4 GW/cm2 peened sample at low magnification (b) 4 GW/cm2 peened sample at high magnification
(a) 7 GW/cm2 peened sample at low magnification (b) 7 GW/cm2 peened sample at high magnification
50 µm
a Oxide layer Re-cast layer𝜸𝜸′′
𝜸𝜸′
50 µm
b
(a) 10 GW/cm2 peened sample at low magnification (b) 10 GW/cm2 peened sample at high magnification
100 µm Dendrites
4 GW/cm2 peened sample after thermal exposure at low magnification
Variation of Ra values over laser power density Dislocation density for {200} peak broadening In-depth microhardness distribution In-depth residual stress distribution
b
50 µm
a b
AcknowledgmentDr. Hackel Lloyd (Curtiss-Wright Surface Technologies)
Gatien Nicot Academic background
2018 - 2019
2014 - 2019
Aerospace Materials MSc, Cranfield University
Diplome d’Ingenieur, Universite de Technologie de Compiegne, France
Previous experience2017
2016
Internship, Air France Industries
Maintenance Technician, Cauquil SAS
Erika Ramos da Silva Teixeira Academic background
2018 - 2019
2012 - 2017
Aerospace Materials MSc, Cranfield University
BSc Mechanical Engineering, Amazonas State University – UEA, Brazil
Previous experience2018
2016 - 2018
Process & Quality Analyst, Boreo Electronic Components Industrial Maintenance Intern, S.C. Johnson & Son
Thayalan Kalaiselvan Academic background
2018 - 2019
2014 - 2018
Aerospace Materials MSc, Cranfield University
Aerospace Engineering B.Tech, Amrita Vishwa Vidyapeetham, Coimbatore, India
Previous experience2016 Internship at Aircraft Division, Hindustan
Aeronautics Limited
Dominik Antoni Zdybal Academic background
2018 - 2019
2014 - 2018
Aerospace Materials MSc, Cranfield UniversityBSc Chemistry, The Silesian University of Technology, Poland
Previous experience2017
2017
Laboratory Assistant, The Silesian University of Technology R & D Intern, ABB
Ashutosh GuptaAcademic background
2018 - 2019
2014 - 2018
Aerospace Manufacturing MSc, Cranfield UniversityB-Tech in Mechanical Engineering, Vellore Institute of Technology, India
Dr Christine Chalk E: [email protected]: +44 (0)1234 75 3501
Supervisor
(left to right) Erika Ramos Da Silva Teixeira, Ashutosh Gupta, Thayalan Kalaiselvan, Gatien Nicot, Dominik Antoni Zdybal.
Team members
www.cranfield.ac.uk2019
Dr. Christine Chalk ([email protected]), Dr. John R. Nicholls ([email protected]),Dr. Luis Isern Arrom ([email protected]), Dr. Matthew Appleton ([email protected]), Dr. Gyn Brewster ([email protected]).
Quantifying Sintering Behaviour of Thermal Barrier Coatings at High TemperatureMr Ashutosh GUPTAMr Gatien NICOTMr Dominik ZDYBAL
Mr Thayalan KALAISELVANMs Erika RAMOS DA SILVA TEIXEIRA
IntroductionTBCs deposited by Electron Beam Physical Vapour Deposition (EB-PVD) are used onhigh temperature and high pressure turbine blades in aero-engines to protectunderlying nickel superalloy substrate from thermal degradation• 7wt%Y2O3 stabilised ZrO2 (7YSZ) is the Industry standard TBC . Newer ceramics
include lanthanide dopants to further lower thermal conductivity, 4mol%Er2O37YSZ.• Porous, columnar TBCs obtained from EB-PVD deposition provide low thermal
conductivity and superior strain tolerance under demanding service conditions.During prolonged exposure to high temperatures, columnar TBCs evolve towards abulk state following the sintering process.
• Sintering Processes:• Loss of feathery porosity (FP) and internal porosity (IP) – surface diffusion• Necking between columns (N) – loss of intercolumnar porosity• Phase changes – (t-m) (PC)
Results
Phase Composition (PC)
Conclusion:
Porosity Measurements (IP/FP)
8
10
12
14
16
18
20
22
800 900 1000 1100 1200 1300 1400
Poro
sity (
%)
Heat treatment temperature (100h exposure) (°C)
Porosity evolution from Archimedes Method(AM) and Image Analysis(IA)
7YSZ Archimedes Method 7YSZ +Er Archimedes Method7YSZ Image Analysis 7YSZ +Er Image Analysis
Dynamic Young’s Modulus (PC/N)
7YSZ, 100 Hours Thermal Exposure, Increasing Temperatures
• Porosity study shows a drop around 1200°C.• Convergence of results for sintered samples indicates
closure of open porosity (1300°C):• Surface phase composition assessment shows that
monoclinic transformation occurs between 1350°Cand 1400°C on 7YSZ samples.
• Peak shift study was inconclusive because of aleatorystress dispersion on 7YSZ samples.
• Spectroscopy of Erbia doped samples was affected byfluorescence, making investigation of phasecomposition inconclusive.
ArchimedesImage
AnalysisFEA
Replica
RFDA
Raman
Image Analysis
EDX/XRD
Raman
Prop
erty
Met
hod
Property
Method
AIMQUANTIFYING
SINTERING
Porosity Evolution
Dynamic Young’s
Modulus
Internal Stresses
Columns Roughness
ChemicalComposition
Phase Composition
100µm
As deposited 1300°C
100µm100µm
1200°C
100µm
1400°C
Left half:SEM image
Right half: Threshold image using Otsu method
WaterWater PenetrationPorosity measured by AM
Porosity measured by IA
SINTERING
TBC columns
Water
0
20
40
60
80
100
120
140
160
900 1000 1100 1200 1300 1400
Dyna
mic
Youn
g’s m
odul
us o
f coa
ting (
GPa)
Heat treatment temperature (100 h exposure) (°C)
Dynamic Young’s modulus evolution
7YSZ analytical 7YSZ FEA 7YSZ+Er analytical 7YSZ+Er FEA
• Young’s Modulus starts to increase from 1200°C.• Rate of increase is higher for 7YSZ than Erbia doped. • 7YSZ : 10-fold increase from as deposited state to
sintered (1400°C).• 7YSZ+Er 3-fold increase from as deposited state to
sintered (1400°C).• 50% higher activation energy value for Er2O3 doped TBC.
125 175 225 275 325 375 425 475 525 575 625 675
Inte
nsity
(a.u
.)
Raman Phase Composition of 7YSZ
INGOT 7YSZ AS DEPOSITED 1300 ᵒ C 1350 ᵒ C 1400 ᵒ C
: Tetragonal peak: Monoclinic peak
: Tetra/Mono peak
Raman shift (cm-1)
Porosity measured by IA
Porosity measured by AM
Alumina coated with TBC
Dimensions measurement
RFDA measurement
Real flexural frequency
Restoration of geometry
in Ansys Modal
Simulated flexural
frequency
freal=
Estimate Ecoating
Ecoatingdetermined
No
Yes
• First increase in Young’s modulus (1200°C-1300°C) might berelated to intra-columnar porosity decline.
• Second increase in Young’s modulus (1300°C-1400°C) might berelated to extra-columnar porosity augmentation and neckingphenomenon, inducing more significant stiffening.
• Erbia addition impedes sintering process and decreases its rate,enabling extension in maximum service temperature of enginesfrom 1200°C to 1300°C, improving combustion efficiency.
• Sintering evolution was successfully studied throughquantitative and qualitative methods.
• Surface Raman was proved to deliver insufficient results.• Cross-section Raman was determined as more conclusive.• The different methods converge toward similar conclusion:
bulk diffusion commences at temperatures above 1200°C for7YSZ: coating stiffening initiation and porosity drop.
fsimulated
Chenguang Yang Academic background
2018 - 2019
2011 - 2015
Advanced Materials MSc, Cranfield University
Bachelor of Chemical Engineering and Technology, Northwest University, China
Previous experience2015 - 2018 Process Engineer, AVIC Xi’an Aviation Brake
Technology Co., Ltd
Jocelyn Delansorne Academic background
2018 - 2019
2014 - 2016
Aerospace Materials MSc, Cranfield University
Preparatory class, LycEe International de Valbonne, France
Previous experience2017 - 2018 Internship, Mecaprotec Industries
Junfeng Chen Academic background
2018 - 2019
2014 - 2017
Advanced Materials MSc, Cranfield UniversityBachelor of Engineering with Honours, Queen Mary University of London, United Kingdom
Previous experience2015
2016
Quality Inspector, Shenye Air Nail (Zhongshan) Co., Ltd
Assembly worker, Guangdong Xinbao Electrical Appliances Holdings Co., Ltd
Mylene LeducAcademic background
2018 - 2019
2013 - 2019
Aerospace Materials MSc, Cranfield University
Preparatory classes, Ecole des Mines de Saint-Etienne, France
Previous experience2018 Assistant engineer internship, De Dietrich SAS
Dr Indrat Aria E: [email protected]: +44 (0)1234 75 8066
Supervisor
(left to right) Junfeng Chen, Jocelyn Delansorne, Mylène Leduc, Chenguang Yang.
Team members
www.cranfield.ac.uk2019
4. Results:
0
20
40
60
80
100
0
5
10
15
20
25
0 2 4 6 8
Pow
er /
mW
Cur
rent
/ m
A
Voltage / V
I-V & P-V Curve
I-V of Control in 1.3 SunI-V of QD1 in 1.3 SunP-V of Control in 1.3 SunP-V of QD1 in 1.3 Sun
3. Methodology:
Dr. Adrianus Indrat Aria [email protected]. Debabrata Bhattacharyya [email protected]
Industrial advisors: Mr. Mark BrenchleyDr. Monica Saavedra Mr. Angelos Lampropoulos
2. Aim: Manufacturing and characterisation of photoluminescent downshifting thin films containing various QDs, and assessment of power conversion performance through optimisation of process parameters.
5. Discussion:● Overall improvement of PCE for high concentration samples up
to 4.96% and fill factor up to 1.98%.● Luminescent film decreases PV thermalization as observed by an
improvement in Voc, which may improve on the longevity of PV.● Manufacturing process affects the photoluminescence properties
of all tested QDs by shifting their λem of up to 55 nm.
6. Future Work:● Verify the impact of integrating anti-reflective
coating with luminescent film to PV performance.● Explore the feasibility of replacing PMMA by UV-
curable isobornyl acrylate (IBOA).
PMMA solution
Liquid phase fluorescence spectroscopy SEM / EDX and AFMStylus
profilometry
Quantum dot solution
Spin-coating and annealing Film sample
Figure 4. PV performance in presence of luminescent film
Photoluminescence thin films for improvement of solar photovoltaic performanceChenguang Yang, Jocelyn Delansorne, Junfeng Chen, Mylène Leduc
1. Background:● Fundamental losses in solar PVSolar PV technologies suffer from inefficiencies in energy conversion due to mismatch between solar radiation spectrum and PV spectral response: Eph<<Eg: sub-bandgap transmission loss.Eph>>Eg: thermalization loss. Figure 1. Spectral response of different PVs
against AM1.5G solar irradiance [1]
● Quantum dot (QD)The luminescent film containing QDs can absorb photons in the spectrum region where solar power peaks and shift the photon energy to regions where Si solar PV convert photons most efficiently.
Figure 2. Luminescent ink and film
(a)
Figure 5. Fluorescence excitation-emission of (a) liquid QD2 ink and (b) solid QD2 film
(b)
Figure 3. I-V and P-V curve of PV with only PMMA on top (control) and a PV with luminescent film on top under 1.3 sunlight intensity
1: Control 1 Sun3: QD1 50 mg/mL 1 Sun5: QD2 25 mg/mL 1 Sun
Reference: [1] Betcke, J et al. (2010) ‘Spectrally Resolved Solar Irradiance Derived from Meteosat Cloud Information-methods and Validation’, University of Oldenburg, Energy and Semiconductor Laboratory, Energy Meteorology Group
Voc
Maximum Power P = Imp x Vmp
Isc
PV test using solar simulator
Solid phase fluorescence spectroscopy
Ink
2: Control 1.3 Sun4: QD1 50 mg/mL 1.3 Sun6: QD2 25 mg/mL 1.3 Sun
Techniques Parameters
Liquid/Solid phase fluorescence λex and λem
SEM/AFM TopographyEDX Composition
Stylus profilometry Thickness
PV test PCE, FF,Voc, Isc
Qihong Jiang Academic background
2018 - 2019
2014 - 2017
Advanced Materials MSc, Cranfield University
Material science and technology, University of Birmingham, UK
Virginia Amfilochiou Academic background
2018 - 2019
2011 - 2017
Aerospace Materials MSc, Cranfield University
Mechanical and Aeronautical Engineer, University of Patras, Greece
María Fernández Carbayo Academic background
2018 - 2019
2014 - 2018
Advanced Materials MSc, Cranfield University
Materials Engineering, Polythechnic University of Madrid, Spain
Previous experience2017 - 2018 Internship, IMDEA Materials
Guiyong Chen Academic background
2018 - 2019
2006 - 2010
Manufacturing Technology and Management MSc, Cranfield UniversityMaterials science and engineering, Beihang University, China
Previous experience2013 - 2019 Composite manufacturing engineer, AVIC
Jim NourryAcademic background
2018 - 2019
2014 - 2019
Aerospace Materials MSc, Cranfield University
Material engineer, Polytech Lyon, France
Prof Krzysztof Koziol E: [email protected]: +44 (0)1234 75 4153
Supervisor
(left to right) Virginia Amfilochiou, Guiyong Chen, Maria Fernandez Carbayo, Qihong Jiang, Jim Nourry.
Team members
www.cranfield.ac.uk 2019
•Varying combination of model parameters for k and k +5% change •Post-processing ANSYS results by FFT •Sensitivity to k changes of amplitude and phase of T wave obtained •Effect of parameters identified •T change and phase change calculated
Motivation
Increasing use of composites with tailored thermal properties, e.g. automotive engine casing, chassis Need of thermal conductivity measurements of assembled component: one sided access, non-contact, portable, accurate, reproducible measurements
Aims Feasibility study of thermal conductivity apparatus for composites Model development of experimental apparatus
Objectives Develop FEA model Investigate optimum set of model parameters Define requirements of apparatus components
MODEL PARAMETERS TESTED VALUES UNITS
Laser Power Varied for ΔΤ ≅ 30oC at beam centre W
Laser Beam Radius R = 1, 2, 5 mm
Modulation Frequency f = 1/30, 1/60, 1/100 Hz
Material Thermal
Conductivity
Isotropic k = 0.2 W/m K
Orthotropic kx = 7, kz = 0.2
Sample thickness h = 1, 10 mm
Top surface temperature measurements at varying distance from laser beam centre FFT analysis of multiple frequencies
Changes of k temperature wave amplitude and phase change
• Temperature wave amplitude at varying x-axis points derived • Temperature wave phase lag at varying x-axis points derived
Measuring Technique 1.
Procedure of Model Analysis FEA Model – ANSYS Fluent 2.
Laser sinusoidal modulated heat source: multiple frequencies applied simultaneously
Model Parameters
Results & Conclusions Laser power does not affect either temperature or phase change when k varies Lower R provide greater phase sensitivity to k Higher R increase T change. Higher accuracy for rig measurement expected f ≤ 1/60 Hz provide more reliable results and increased sensitivity R = 2mm and f = 1/60 Hz give best results for amplitude/phase sensitivity and T changes. Advantage: time efficiency Minimum phase lag to be detected 0.01 s Minimum T change to detect 0.04 oC Linearity applies for FFT to be used in multi-frequency heat source
Future Work Investigation of multiple layer composite model Research of two-laser model Retrieve k values from amplitude and phase temperature data Assemble apparatus and test measurement technique
Alex Skordos: [email protected] Krzysztof Koziol: [email protected]
Portable thermal conductivity testing rig for composites
Jim Nourry Virginia Amfilochiou
Guiyong Chen Qihong Jiang
María Fernández Carbayo
Chenkai Zhang Academic background
2018 - 2019
2014 - 2018
Aerospace Materials MSc, Cranfield University
Metallic Materials Engineering, Changzhou University, China
Noor Ghadarah Academic background
2018 - 2019
2015 - 2018
Advanced Materials MSc, Cranfield University
BEng Materials Science and Engineering, Swansea University, United Kingdom
Previous experience2017 Research on the galvanising bath, Specific
Krutarth Jani Academic background
2018 - 2019
2013 - 2017
Aerospace Materials MSc, Cranfield University
Mechanical Engineering, Gujarat Technological University, India
Previous experience2018 - 2019 Casual Laboratory Assistant,
Cranfield University
Lakshmi Priya Muthe Academic background
2018 - 2019
2011 - 2015
Aerospace Materials MSc, Cranfield UniversityAeronautical Engineering, Jawaharlal Nehru Technological University, India
Previous experience2017 - 2018
2016 - 2017
Seller Support Associate, Amazon
Graduate Engineer, IBM India Pvt.ltd
Xinyi GuanAcademic background
2018 - 2019
2014 - 2018
Manufacturing Technology and Management MSc, Cranfield University
Bachelor Degree of Chemistry, Keele University, UK
Prof Krzysztof Koziol E: [email protected]: +44 (0)1234 75 4153
Supervisor
(left to right) Noor Ghadarah, Xinyi Guan, Krutarth Jani, Lakshmi Priya Muthe, Chenkai Zhang.
Team members
www.cranfield.ac.uk2019
Prof Krzysztof Koziol, Dr David Ayre, Andrew MillsSchool of Aerospace, Transport and Manufacturing, Building [email protected], [email protected]@cranfield.ac.uk
Development of graphene enhanced composite hydrogen pipelinesChenkai Zhang, Krutarth Jani, Lakshmi Priya Muthe, Noor Salam Ghadarah, Xinyi Guan
Jiahui Yu Academic background
2018 - 2019
2014 - 2018
Aerospace Manufacturing MSc, Cranfield University
Aerospace Engineering, Swansea University, UK
Previous experience2017 Assistant Engineer (Intern), Shanghai
Electric
Pengtao YangAcademic background
2018 - 2019
2008 - 2012
Aerospace Manufacturing MSc, Cranfield UniversityBachelor of Engineering, Northwestern Polytechnical University, China
Previous experience2012 - 2018 Project Manager, Chengdu Aircraft Industrial
(Group) Co., Ltd
Elisa Bonigen Academic background
2018 - 2019
2014 - 2019
Aerospace Materials MSc, Cranfield UniversityMechanical engineer diploma, University of Technologies of Compiegne (UTC), France
Previous experience2017 - 2018 Intern, Safran Landing Systems
Sara Abu SafiehAcademic background
2018 - 2019
2014 - 2018
Manufacturing Technology and Management MSc, Cranfield University
Automative and Robotics, Mechnical Engineering, Silesian University of Technology.
Previous experience2014
2015 - 2018
Intern, KSK Developments
Intern, P.H.U. HATEL
Abhideep KumarAcademic background
2018 - 2019
2013 - 2017
Aerospace Materials MSc, Cranfield University
Mechanical Engineering, Vellore Institute of Technology, India
Chengxu Zhao Academic background
2018 - 2019
2014 - 2018
Management & Information Systems MSc, Cranfield University
Electronic Engineering, University of Warwick, UK
Previous experience2017
2016 - 2017
Internship in Bureau of Ecology and Environment of Yulin Shaanxi Province
Intern Engineer at Xi’an Honda
Dr Glenn Leighton E: [email protected]: +44 (0)1234 75 2724
Supervisor
Team members
(left to right) Abhideep Kumar, Elisa Bonigen, Jiahui Yu, Sara Abu Safieh, Pengtao Yang, Chengxu Zhao.
www.cranfield.ac.uk2019
Dr. Glenn Leighton, [email protected]. Christopher Shaw, [email protected], Cranfield University, Cranfield, Bedfordshire, MK43 0AL
RF Piezoelectric Tuning ElementChengxu Zhao; Jiahui Yu; Pengtao Yang; Elisa Bonigen; Abhideep Kumar; Sara Abu Safieh;
Objectives• Model a PZT actuator with potential tuneable air gap element for electronic devices to
avoid signal interference• Design a process flow for manufacturing• Generate photolithography masks for fabrication• Demonstrate piezoelectric actuation of manufactured cantilever structure devicesTiO2
Platinum (Sputtering)
5-layer Superimposed Mask Design
• Successful manufacturing route has produced intactmicro-cantilever structures based on dimensions frommodelling results.
• Surface roughness dramatically influences thin film’selectrical properties. Improved roughness of nickelplated surface needs to be addressed.
• Desired Nickel thickness was deposited, putting beam’snatural frequencies above potential interferenceapplication frequencies.
• Resonance free operation range: 10 to2000 Hz
• Critical beam length: 2.325 mm• Operating temperatures: -25 to 85°C• Maximum deflection: 25 μm
PZT (Spin coating)
Photoresist
Dry etching
Mask 2
Mask 1
Wet etchingMask 3
Nickel (Electroplating)
Mask 4
Mask 5
Back etching (DRIE)
Final device
Final Device
Optical Microscope
FEA Model of Actuator
Process FlowSiO2-Si-SiO2 wafer
200 μm
Ni
Au
200 μm
Pt
PZT
TiO2
Nickel Roughness
Post-electroplating Nickel Length Profile
Conclusion
Platinum as bottom electrode Nickel electroplated on Gold coated wafer
Device Specifications
24/4/2019 – Version 3
Felix Otuada Academic background
2018 - 2019
2009 - 2014
Welding Engineering MSc, Cranfield University
Welding and Fabrication, Delta State Polytechnic, Ogwashi-Uku, Nigeria
Previous experience2010 - 2011
2006 - 2008
Barge construction, Vessel repair, Construction oil tanks, Omote Dynamic (Nig.) Limited Warri
Construction & building design and metal machining & cutting, Jofaab Global (Nig.) Limited Warri
Dao Wang Academic background
2018 - 2019
2007 - 2011
Aerospace Materials MSc, Cranfield University
Material forming and control engineering, Heilongjiang University of Science and Technology, China
Previous experience2014 - 2018 Welding and Mechanical Engineer, Aero
Engine Corporation of China
Halil Emre Caglar Academic background
2018 - 2019
2013 - 2017
Manufacturing Technology and Management MSc, Cranfield University
Mechanical Engineer, Gazi University, Turkey
Previous experience2017 - 2018 Design and Analyses Engineer, OEMIA
Defence
Yuhan HeAcademic background
2018 - 2019
2011 - 2015
Welding Engineering MSc, Cranfield University
Bachelor, HIT (Harbin Institute of Technology), China
Previous experience2015 - 2018 Material Engineer, AECC (Aero Engine
Corporation of China)
Dr Supriyo Ganguly E: [email protected]: +44 (0)1234 75 5054
Supervisor
(left to right) Halil Emre Caglar, Yuhan He, Felix Otuada, Dao Wang.
Team members
www.cranfield.ac.uk2019
Supervisors:Dr. Supriyo Ganguly, [email protected]. Jialuo Ding, [email protected] Engineering and Laser Processing Centre, College road, Cranfield University, MK430AL © 2019 BÖHLER UK - Division of
voestalpine High Performance Metals UK Ltd+44 121 552 [email protected]@voestalpine.com
Wire plus Arc Additive Manufacture (WAAM) of 15-5 PH stainless steel using plasma arc process
Authors: Dao Wang, Yuhan He, Halil Emre Caglar, Felix Otuada.
Wire + Arc Additive Manufacturing (WAAM) is an importantmanufacturing tool for metal AM in aerospace, defence, andtransportation industry. The 15-5 precipitation hardening (PH)stainless steel (SS) is one of the advanced alloys and suitable forapplication in extreme conditions. The present study aims tounderstand the feasibility of using the WAAM process formanufacturing 15-5 PH SS structures.
● The 15-5 PH SS wire was used to deposit and manufacturecomponents using the Plasma arc welding based WAAM processto study the response of the metal when subjected to multiplethermal cycles due to successive layer deposition.
Fig 3.1 Geometry of single bead: ɑ-contact angle, lh-layer height,
ph-penetration height, ww-wall width
1. INTRODUCTION
2. MATERIAL AND METHODOLOGY
3. STATISTICAL ANALYSISThe bead geometry of each single bead was measured. Then theDoE software was adopted to investigate the effect and interactionsof WFS, TS and Current. For the desired bead geometry, twooptimised parameters were selected for the small walls, and the wallefficiency was used to determine the parameters for the final wall.
Fig 2.1 Heat treatment temperature vs time graph
C Si Mn Cr Ni Cu Nb Fe
0.02 0.50 0.50 14.8 4.50 3.30 0.28 Bal
Table 2.1 Chemical composition of 15-5 PH SS wire
Fig 3.2 Wall efficiency
Fig 3.4 Layer height in 3D surface
4.RESULTS
Fig 4.1 Hardness as a function of sample height
5. DISCUSSION AND CONCLUSION● Plasma arc welding based WAAM process can be successfully
used to build walls with 15-5 PH SS.● Partial solutionizing and ageing contribute to the higher hardness
of the layers which are closer to the substrate compared with the layers on the top of the wall.
● Solution treatment followed by ageing treatment makes the microstructure uniform and increases the hardness because of the precipitation hardening.
● The tensile test will be carried out later to investigate the influence of ageing on mechanical properties.
Fig 4.2 Microstructures of selected points (the scale bar is 200 μm)
A
C
B
A CB
Fig 3.3 Contact angle in 3D surface
The overall hardness of the wall (HT) is higher than the wall (AD).As for the wall (AD), the hardness value decreases with theincrease of layer height.Depositing
single beadsOptimizing parameters
Building two small
wallsFinal input selection
Depositing two identical
walls
Comparison of mechanical properties and microstructure in the heat treatment (HT)
with the as-deposited (AD) condition
Eva Pelaez Alvarez Academic background
2018 - 2019
2014 - 2018
Aerospace Materials MSc, Cranfield University
Aerospace Engineering, University of Leon, Spain
Previous experience2017 - 2018
Internship - Research Group TAFI, University of Leon
Segolene Couty Academic background
2018 - 2019
2013 - 2019
Advanced Materials MSc, Cranfield University
Bachelor (Intensive preparatory class), Arts & Metiers PariTech (ENSAM), France
Previous experience2017 Internship, BucherVaslin
Nicolas Correa Academic background
2018 - 2019
2003 - 2012
Manufacturing Technology and Management MSc, Cranfield University
Metallurgical Engineer, Universidad Tecnica Federico Santa Maria, Chile
Previous experience2017 - 2018
2013 - 2016
Logistic Manager, Dry Cleaning
Project Engineer, Techint E&C
Runze Gong Academic background
2018 - 2019
2014 - 2018
Advanced Materials MSc, Cranfield University
Material Science and Engineering, Fuzhou University, China
Prof Krzysztof Koziol E: [email protected]: +44 (0)1234 75 4153
Supervisor
(left to right) Nicolas Correa, Ségolène Couty, Eva Peláez Álvarez, Runze Gong.
Team members
www.cranfield.ac.uk2019
Supervisor:Prof. Krzysztof Koziol, [email protected]
3D Printing of Latex Gloves
Authors: Nicolas Correa, Ségolène Couty, Runze Gong, Eva Peláez
Jiandong Li Academic background
2018 - 2019
2005 - 2009
Engineering and Management of Manufacturing Systems MSc, Cranfield University
B.S Mechanical Engineering and Automation, Nanjing University of Science and Technology, China
Previous experience2009 - 2018 CNC machine tool maintenance engineer,
Aviation Industry of China
Xiaolong Zhang Academic background
2018 - 2019
2009 - 2013
Aerospace Manufacturing MSc, Cranfield University
Bachelor, Nanjing University of Aeronautics and Astronautics, China
Previous experience2013 - 2018 Composites Manufacturing Engineer,
Shanghai Aircraft Manufacturing Company
Jun Xiao Academic background
2018 - 2019
2011 - 2014
Aerospace Manufacturing MSc, Cranfield University
Mechanical Engineering MSc, Dalian University of Technology, China
Previous experience2014 - 2018 Engineer, Aecc South Industry Company
Limited
Hamzah Baqasah Academic background
2018 - 2019
2010 - 2016
Aerospace Materials MSc, Cranfield UniversityMechanical Engineering Technology, Yanbu Industrial College, Saudi Arabia
Previous experience2016 - 2018 Field Engineer, Saudi Aramco
Robert Arhip Academic background
2018 - 2019
2014 - 2019
Aerospace Materials MSc, Cranfield University
Mechanical Engineering MSc, Universite de Technologie de Compiegne, France
Previous experience2018 - 2019
2017 - 2018
CEO and Co-founder, Fluddy
Laser Beam Melting Internship, Fusia
Dr Claudiu Giusca E: [email protected]: +44 (0)1234 75 2958
Supervisor
(left to right) Robert Arhip, Hamzah Baqasah, Jiandong Li, Jun Xiao, Xiaolong Zhang.
Team members
www.cranfield.ac.uk2019
Cross-section
Min
imum
cut
ting
dept
h (µ
m)
The Compact Linear Collider (CLIC project by CERN) should produce a 100 MV/m accelerating field achieving 3 TeV
total energy by 2035.
MOTIVATIONSMillions of discs
Ra 25 nm Accuracy A ±4 μm
Accuracy B ±20 μm
2 parts/day600 euros/part
Diamond machining
Optimise the process chain to reduce cost and increase production
rate
RESULTS
AIMSTATE OF THE ART
CONCLUSION
Cost analysisPre-machining 15% Tooling 5%
End-machining 80%
Objective 2: Selection of end-machining process
20 processes have been reviewed and evaluated. Only 4 are promising.LBM= Laser Beam Machining
LAM= Laser Assisted MachiningECMM= Electrochemical Micro-MachiningDM= Diamond Machining LAM was selected as the cutting depth is
increased by heating.
Objective 3: Optimisation of the parameters for the chosen processHAZ
Objective 1: Automation of the current end-machining steps
Significant improvements possible
Top view
HAZ
Min
imum
tool
siz
e (µ
m)
00.5
11.5
22.5
33.5
44.5
5Ra
Metrology
Centring
Energyconsumption
Tool setting
Automation
Comparison of 3 diamond turning-milling machines
Micro6650 FGv2Freeform L
Ultra-precision turning
WaveguideUltra-milling
Unloading and loading
Alignment Unloading and loading
Alignment
Iris final turning
End-machining steps
Can be eliminated by using a diamond
turning/milling machine
Can be automated thanks to automatic
workpiece repositioning and on-
machine measurement
The impact of wavelength, spot size, scanning speed and power on the cutting depth were investigated.
0%
20%
40%
60%
80%
100%
0.1 0.3 0.5 0.7 0.9
Abso
rptiv
ity
Wavelength (μm)
Copper Absorptivity vs Laser Wavelength
• A new optimised process chain was identified by incorporation of laser assistance to the precision micromachining.• A comparison of state-of-the-art precision machines reveals that a machine with an automated part loading/unloading will benefit
the yield• An FE analysis was carried out to study the extent of laser heating for evaluating the safe cutting depths during machining.• Cost can be significantly improved when loading & measurement steps are automated.
0
2
4
6
8
10
12
ECMM LAM LBM DM
2
5
12
5
0.86 0.025 0.2 0.025
Accuracy Surface roughness
Accuracy & Ra
ECMM
LAM
LBM
DM
0 5 10 15 20 25 30mm3/min
Material Removal Rate
+ 50%
Optimised process chain for rapid production of CLIC disc
Mr. Hamzah Baqasah, Mr. Jun Xiao, Mr. Jiandong Li, Mr. Robbie Arhip, Mr. Xiaolong Zhang
Dr. Claudiu Giusca, Cranfield, Building 90, [email protected]. Saurav Goel, Cranfield, Building 90, [email protected]
Xi Wang Academic background
2018 - 2019
2004 - 2008
Aerospace Manufacturing MSc, Cranfield University
Engineering Bachelor, Shenyang Aerospace University, China
Previous experience2008 - 2018
Cooperation Manager, AVIC HAIC
Siddarth Mohanty Academic background
2018 - 2019
2014 - 2018
Manufacturing Technology and Management MSc, Cranfield University
Bachelors in Mechanical Engineering, Kalinga Institute of Industrial Technology Bhubaneswar, India
Previous experience2017
2016
Internship, Indian Institute of Technology, Kharagpur Internship, TATA Technologies
Yvette Mwendwa Academic background
2018 - 2019
2011 - 2015
Aerospace Materials MSc, Cranfield University
BSc Aeronautical Engineering, Sheffield Hallam University, UK
Previous experience2017 - 2018 Executive Committee member, ABC Initiative
Wei Dai Academic background
2018 - 2019
2007 - 2011
Aerospace Manufacturing MSc, Cranfield University
BSC, Hunan Institute of Engineering, China
Previous experience2014 Mechanical Engineer, AECC
Dr Hamed Yazdani Nezhad E: [email protected]: +44 (0)1234 75 2204
Supervisor
(left to right) Wei Dai, Siddarth Mohanty, Yvette Mwendwa, Xi Wang
Team members
www.cranfield.ac.uk2019
Dr. Hamed Yazdani Nezhad [email protected]. John Ahmet Erkoyuncu [email protected] Dr. David Ayre [email protected]
Augmented Reality (AR) Equipped Composites RepairXi WANG Wei DAIYvette N.MWENDWA Siddarth MOHANTY
CHALLENGES & OBJECTIVES
Augmented Reality based toolkit development to facilitate reliable and repeatable aircraft composite repairing processes by providing real-time instructions to operators
METHODOLOGY
BOND FAILURE MODESCOMPOSITE REPAIR
CURRENT AR INDUSTRY APPLICATION
CONCEPT DESIGN
DELIVERABLES