Post Processing

KTN
KTNKTN
Topic	
  3:	
  Post	
  Processing
Presenting
Simon	
  Rogers
Bethany	
  King
Graham	
  Robertson
Ben	
  Farmer
Dave	
  Cooper
Joseph	
  Crabtree
Project	
  title:	
  SEAMLESS	
  – Digitally-­‐Enabled,	
  Automated	
  Post	
  
processing	
  for	
  AM
Abstract:
SEAMLESS	
  is	
  a	
  major	
  upscale	
  of	
  FlexiFinish which	
  focussed	
  on	
  the	
  urgent	
  issue	
  of	
  post	
  
processing	
  for	
  AM.	
  The	
  key	
  technology	
  advances	
  over	
  the	
  FlexiFinish concept	
  include	
  super	
  
surface	
  finishing	
  (adaptive	
  shape	
  grinding)	
  for	
  applications	
  that	
  require	
  <0.1μm	
  Ra	
  (e.g.	
  
space	
  and	
  medical	
  sectors);	
  laser	
  shock	
  peening for	
  enhanced	
  functional	
  performance	
  
alternative	
  NDT	
  solutions	
  (eddy	
  current)	
  for	
  difficult-­‐to-­‐access	
  features;	
  empirical	
  modelling	
  
/	
  simulation	
  tool	
  for	
  right-­‐first-­‐time	
  KPV	
  identification	
  (therefore	
  minimum	
  or	
  no	
  re-­‐work);	
  
offline	
  programming	
  for	
  auto	
  tool	
  path	
  generation	
  and	
  a	
  digital	
  platform	
  (cloud)	
  to	
  enable	
  
smooth	
  and	
  seamless	
  connectivity	
  between	
  the	
  different	
  components	
  of	
  the	
  system,	
  
Presenter	
  name/	
  company:
Simon	
  Rogers	
  -­‐
Project	
  ref	
  103274
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
•Modularity: Use	
  of	
  a	
  robotic	
  platform	
  with	
  
interchangeable	
  ‘Eddy	
  Current	
  inspection’,	
  ‘Laser	
  
Shock	
  Peening’	
  and	
  ‘Shape	
  Adaptive	
  Grinding’	
  heads	
  
enables	
  parts	
  of	
  almost	
  unlimited	
  size	
  to	
  be	
  
processed.
•Real-­‐time	
  insight: Use	
  of	
  digital	
  manufacturing	
  
techniques	
  and	
  array	
  of	
  sensors	
  and	
  software	
  tools	
  to	
  
provide	
  data	
  both	
  on	
  the	
  process	
  and	
  the	
  quality	
  of	
  
parts	
  produced,	
  both	
  metallurgy	
  and	
  metrology.
•Autonomy:	
  Digital	
  information	
  used	
  to	
  enable	
  the	
  
cell	
  to	
  operate	
  in	
  an	
  autonomous	
  mode,	
  defining	
  if	
  
components	
  need	
  further	
  processing	
  to	
  enable	
  
‘Adaptive	
  AM	
  Post	
  Processing’	
  in	
  the	
  truest	
  sense.
•Enriched	
  modelling: Data	
  collected	
  from	
  the	
  
components	
  will	
  be	
  used	
  to	
  adjust	
  the	
  tool	
  path	
  
strategy	
  /	
  options	
  to	
  give	
  an	
  Adaptive	
  process,	
  
including	
  environmental	
  effects	
  on	
  the	
  cell	
  
performance.
• Novel	
  template	
  driven	
  AM	
  post	
  process	
  robot	
  
programming	
  (PROCESS)
• Automated	
  toolpath update	
  based	
  on	
  NDT	
  
measurement	
  (INSPECTION/DESIGN)
• Safer	
  working	
  environment	
  enclosed	
  (PROCESS)
• Reduced	
  AM	
  post	
  processing	
  costs	
  
(COST/FINANCIAL)
• Aerospace	
  and	
  Medical	
  Alloy	
  build	
  specs	
  and	
  standards	
  
(MATERIALS)
• Automated	
  metallurgy	
  inspection	
  and	
  critical	
  feature	
  
machining	
  for	
  AM	
  components	
  combined	
  (PROCESS)
• AM	
  build	
  for	
  post	
  processing	
  access	
  to	
  critical	
  structures	
  
(DESIGN)
Autonomy
Enriched	
  
modelling
Modularity
Real-­‐time	
  
insight
NDT Shape	
  Adaptive	
  	
  
Grinding	
  
Laser	
  Shock
Peening
Eddy	
  Current
Flexible	
  Media
Workflow
Alicona
Rigid	
  Media
Project	
  ref	
  103274
Topic	
  3:	
  Post	
  Processing
Pitches
Project	
  title:	
  ProAMP
Abstract:	
  This	
  project	
  is	
  examining	
  ways	
  to	
  improve	
  the	
  
surface	
  finish	
  of	
  parts	
  made	
  by	
  Selective	
  Laser	
  Sintering.	
  
This	
  will	
  be	
  done	
  at	
  looking	
  at	
  methods	
  of	
  improving	
  
scanning	
  methodologies,	
  and	
  developing	
  an	
  automatic	
  SLS	
  
part	
  finishing	
  system	
  with	
  auto	
  component	
  identification	
  
for	
  packaging.
Presenter	
  name/	
  company:	
  B.	
  King,	
  Lancaster	
  University
Project	
  ref	
  103448
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
• The	
  project	
  is	
  at	
  an	
  early	
  stage	
  and	
  
objectives	
  are	
  due	
  in	
  2020
• Project	
  will	
  allow	
  parts	
  to	
  be	
  unloaded	
  
from	
  an	
  SLS	
  machine,	
  cleaned,	
  identified	
  
and	
  packed	
  automatically.
• Methods	
  to	
  produce	
  better	
  surface	
  
finishes	
  arising	
  from	
  new	
  scan	
  algorithms	
  
will	
  be	
  trialed.
• Software	
  and	
  equipment	
  is	
  currently	
  
under	
  design
• Initial	
  testing	
  of	
  both	
  software	
  and	
  
equipment	
  is	
  expected	
  in	
  late	
  2018
• The	
  project	
  contributes	
  by	
  looking	
  at	
  
methods	
  to:
• improve	
  finishing	
  and	
  part	
  
consistency/quality;
• increase	
  speeds	
  of	
  production;
• reduce	
  costs;
• Areas	
  of	
  research	
  interest	
  include	
  
investigations	
  into:
• better	
  materials	
  for	
  SLS	
  AM	
  (e.g PEEK);
• construction	
  of	
  large	
  body	
  AM	
  
machines;
• automatic,	
  in-­‐process	
  	
  feedback	
  
systems;
Project	
  ref	
  103448
PowderCleanse -­‐ Automated	
  powder	
  recycling	
  and	
  quality	
  
assurance	
  for	
  enhanced	
  material	
  reuse	
  for	
  AM.
Abstract:
Challenging	
  “The	
  way	
  we’ve	
  always	
  done	
  things”.
Developing	
  a	
  closed	
  loop	
  powder	
  management	
  system	
  
including	
  powder	
  validation	
  which	
  utilises	
  digital	
  connectivity	
  
to	
  both	
  monitor	
  and	
  control	
  every	
  aspect	
  of	
  the	
  process.
Graham	
  Robertson	
  (LPW	
  Technology)
Ben	
  Blackham	
  (MTC)
Project	
  ref	
  103278
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
• Material	
  alloy	
  development
• Health	
  Safety	
  and	
  Environment	
  	
  guidelines
• Recycling	
  expertise
• Education	
  and	
  Training
Materials	
  and	
  processes
Inspection,	
  Test	
  and	
  Standards
Process	
  performance	
  
captured	
  digitally
Central	
  data	
  
repository
Project	
  ref	
  103278
Project	
  title:	
  Tailorable	
  &	
  Adaptive	
  Connected	
  Digital	
  Additive	
  Manufacturing	
  
(TACDAM)
Abstract:	
  The	
  TACDAM	
  project	
  will	
  perform	
  targeted	
  Additive	
  Manufacturing	
  
(AM)	
  pre-­‐ and	
  post-­‐process	
  value	
  chain	
  technology	
  developments,	
  develop	
  
an	
  adaptive	
  quality	
  assurance	
  model,	
  introduce	
  parametric	
  design	
  as	
  a	
  key	
  
process	
  variable	
  and	
  demonstrate	
  the	
  capability	
  to	
  deliver	
  cost	
  and	
  quality	
  
outcomes	
  at	
  Manufacturing	
  Readiness	
  Level	
  6	
  to	
  the	
  automotive	
  industry.
Presenter:	
  Dr Ben	
  Farmer	
  /	
  HiETA Technologies	
  Ltd
Project	
  ref	
  103279
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
• £	
  Automotive	
  &	
  staged	
  1/3/6s quality
• Machine	
  learning	
  to	
  facilitate	
  automation	
  reduce	
  
cost	
  and	
  variability
• Design:	
  Quantification	
  of	
  the	
  
performance/yield	
  trade	
  off
• Materials:	
  More	
  cost	
  effective	
  Inconel	
  
&	
  titanium	
  
• Inspection:	
  Non-­‐contact	
  inspection	
  to	
  
establish	
  that	
  powder	
  is	
  removed
• Supply chain:	
  Industry	
  vertical	
  
• Design	
  methods	
  and	
  tools
• Physics	
  and	
  AI-­‐based	
  modelling	
  for	
  design	
  and	
  
manufacturing
• New	
  Al	
  and	
  Ni-­‐based	
  materials
• NDT/NDI	
  of	
  complex,	
  dense	
  parts
• Automation,	
  simulation	
  and	
  optimisation	
  of	
  future	
  
industrial	
  environment
• Parametric	
  design	
  
as	
  a	
  key	
  process	
  
variable	
  
• Started	
  at	
  MRL3,	
  
currently	
  MRL5,	
  
finish	
  at	
  MRL6
OperationsDesign
Concept design
AM process
selection
Detailed design, optimisation,
DFM
Build design
and
preparation
Material
Process and post-process Quality assurance
AM process
Powder
removal
Heat &
pressure
treatment
Removal from
plate
Support
removal
Machining and
smoothing
Surface
treatment
Destructive
testing of
traveller
NDT/NDI Finished part
Validation
testing
Maintainence Overhall Repair
£££ ££ £ ££ £ ££Cost	
  challenges
Quality	
  challenges
££
Project	
  ref	
  103279
Automated	
  Post-­‐Processing	
  Platform	
  for	
  Metals	
  Additive	
  
Manufacturing	
  – (PLATFORM)
One	
  of	
  the	
  key	
  technical	
  challenges	
  facing	
  the	
  metal	
  AM	
  
market	
  is	
  the	
  need	
  for	
  post-­‐processing	
  of	
  parts	
  to	
  achieve	
  
required	
  tolerances.	
  The	
  PLATFORM	
  project	
  aims	
  to	
  
revolutionise	
  the	
  way	
  in	
  which	
  metal	
  AM	
  products	
  are	
  
finished	
  by	
  developing	
  a	
  modular	
  system	
  and	
  automatic	
  CAM	
  
software	
  for	
  support	
  removal	
  and	
  proof	
  machining.
Dr.	
  Dave	
  Cooper	
  – Progressive	
  Technology
Project	
  ref	
  103453
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
• Deliver	
  a	
  modular	
  work	
  holding	
  
system	
  to	
  enable	
  end	
  to	
  end	
  complex	
  
AM	
  part	
  production	
  and	
  reduce	
  
fixture	
  costs
• Automate	
  CNC	
  support	
  removal	
  &	
  
proof	
  machining.
• Combine	
  with	
  efficient	
  CT	
  techniques	
  
to	
  aid	
  alignment	
  of	
  machining	
  to	
  
blanks	
  and	
  reduce	
  setup	
  time/scrap
• First	
  steps	
  toward	
  AM/CNC	
  
integration	
  have	
  begun
• Key	
  issues/likely	
  problems	
  are	
  
beginning	
  to	
  be	
  understood
• Streamlines	
  production	
  of	
  high	
  value	
  
machined	
  AM	
  parts
• Reduces	
  scrap	
  and	
  “black	
  magic”,	
  
lowering	
  barriers	
  to	
  entry	
  for	
  SME’s
• Integration	
  of	
  AM	
  into	
  post	
  
processing	
  supply	
  chain	
  
Project	
  ref	
  103453
AMSURFIN	
  -­‐ Additive	
  Manufacturing	
  SURface FINishing -­‐
An	
  automated	
  intelligent	
  solution	
  for	
  polymer	
  parts
The	
  project’s	
  vision	
  is	
  to	
  create	
  an	
  automated	
  intelligent	
  
post	
  processing	
  machine	
  capable	
  of	
  finishing	
  additively	
  
manufactured	
  thermoplastic	
  polymer	
  parts	
  to	
  an	
  injection	
  
moulded	
  level	
  surface	
  finish.
Joseph	
  Crabtree	
  /	
  Additive	
  Manufacturing	
  Technologies	
  
Limited
Project	
  ref	
  103275
Project	
  Objectives
Your	
  requests	
  to	
  UK	
  Research	
  (Universities,	
  UKRI)How	
  does	
  this	
  contribute	
  to	
  delivering	
  the	
  AM-­‐UK	
  Strategy?
Progress/	
  Learning/	
  Outcomes
1. Create	
  a	
  saleable	
  automated	
  post	
  processing	
  
machine	
  capable	
  of	
  generating	
  a	
  repeatable	
  and	
  
reproducible	
  surface	
  finish	
  equivalent	
  to	
  that	
  
achieved	
  in	
  injection	
  moulding	
  for	
  additively	
  
manufactured	
  parts.
2. Develop	
  intelligent	
  algorithms	
  that	
  control	
  the	
  
amount	
  of	
  post	
  processing	
  for	
  a	
  given	
  material	
  
and	
  geometric	
  design.
3. Develop	
  a	
  machine	
  that	
  is	
  integrated	
  into	
  the	
  
digital	
  manufacturing	
  chain.	
  
1. Directly	
  addresses	
  the	
  issue	
  around	
  the	
  
optimisation	
  and	
  automation	
  of	
  Post	
  Processing	
  
in	
  3D	
  Printing.
2. Protected	
  by	
  IP	
  and	
  CE/UL	
  Standards.
3. Industry	
  4.0	
  compliant.
1. Understanding	
  the	
  total	
  value	
  chain	
  proposition	
  
from	
  Materials	
  à parts.
2. Application	
  and	
  Industry	
  4.0	
  relevant.
3. Must	
  have	
  ‘hands	
  on’,	
  practical	
  approach.
Project	
  ref	
  103275
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Post Processing

  • 1. Topic  3:  Post  Processing Presenting Simon  Rogers Bethany  King Graham  Robertson Ben  Farmer Dave  Cooper Joseph  Crabtree
  • 2. Project  title:  SEAMLESS  – Digitally-­‐Enabled,  Automated  Post   processing  for  AM Abstract: SEAMLESS  is  a  major  upscale  of  FlexiFinish which  focussed  on  the  urgent  issue  of  post   processing  for  AM.  The  key  technology  advances  over  the  FlexiFinish concept  include  super   surface  finishing  (adaptive  shape  grinding)  for  applications  that  require  <0.1μm  Ra  (e.g.   space  and  medical  sectors);  laser  shock  peening for  enhanced  functional  performance   alternative  NDT  solutions  (eddy  current)  for  difficult-­‐to-­‐access  features;  empirical  modelling   /  simulation  tool  for  right-­‐first-­‐time  KPV  identification  (therefore  minimum  or  no  re-­‐work);   offline  programming  for  auto  tool  path  generation  and  a  digital  platform  (cloud)  to  enable   smooth  and  seamless  connectivity  between  the  different  components  of  the  system,   Presenter  name/  company: Simon  Rogers  -­‐ Project  ref  103274
  • 3. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes •Modularity: Use  of  a  robotic  platform  with   interchangeable  ‘Eddy  Current  inspection’,  ‘Laser   Shock  Peening’  and  ‘Shape  Adaptive  Grinding’  heads   enables  parts  of  almost  unlimited  size  to  be   processed. •Real-­‐time  insight: Use  of  digital  manufacturing   techniques  and  array  of  sensors  and  software  tools  to   provide  data  both  on  the  process  and  the  quality  of   parts  produced,  both  metallurgy  and  metrology. •Autonomy:  Digital  information  used  to  enable  the   cell  to  operate  in  an  autonomous  mode,  defining  if   components  need  further  processing  to  enable   ‘Adaptive  AM  Post  Processing’  in  the  truest  sense. •Enriched  modelling: Data  collected  from  the   components  will  be  used  to  adjust  the  tool  path   strategy  /  options  to  give  an  Adaptive  process,   including  environmental  effects  on  the  cell   performance. • Novel  template  driven  AM  post  process  robot   programming  (PROCESS) • Automated  toolpath update  based  on  NDT   measurement  (INSPECTION/DESIGN) • Safer  working  environment  enclosed  (PROCESS) • Reduced  AM  post  processing  costs   (COST/FINANCIAL) • Aerospace  and  Medical  Alloy  build  specs  and  standards   (MATERIALS) • Automated  metallurgy  inspection  and  critical  feature   machining  for  AM  components  combined  (PROCESS) • AM  build  for  post  processing  access  to  critical  structures   (DESIGN) Autonomy Enriched   modelling Modularity Real-­‐time   insight NDT Shape  Adaptive     Grinding   Laser  Shock Peening Eddy  Current Flexible  Media Workflow Alicona Rigid  Media Project  ref  103274
  • 4. Topic  3:  Post  Processing Pitches
  • 5. Project  title:  ProAMP Abstract:  This  project  is  examining  ways  to  improve  the   surface  finish  of  parts  made  by  Selective  Laser  Sintering.   This  will  be  done  at  looking  at  methods  of  improving   scanning  methodologies,  and  developing  an  automatic  SLS   part  finishing  system  with  auto  component  identification   for  packaging. Presenter  name/  company:  B.  King,  Lancaster  University Project  ref  103448
  • 6. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes • The  project  is  at  an  early  stage  and   objectives  are  due  in  2020 • Project  will  allow  parts  to  be  unloaded   from  an  SLS  machine,  cleaned,  identified   and  packed  automatically. • Methods  to  produce  better  surface   finishes  arising  from  new  scan  algorithms   will  be  trialed. • Software  and  equipment  is  currently   under  design • Initial  testing  of  both  software  and   equipment  is  expected  in  late  2018 • The  project  contributes  by  looking  at   methods  to: • improve  finishing  and  part   consistency/quality; • increase  speeds  of  production; • reduce  costs; • Areas  of  research  interest  include   investigations  into: • better  materials  for  SLS  AM  (e.g PEEK); • construction  of  large  body  AM   machines; • automatic,  in-­‐process    feedback   systems; Project  ref  103448
  • 7. PowderCleanse -­‐ Automated  powder  recycling  and  quality   assurance  for  enhanced  material  reuse  for  AM. Abstract: Challenging  “The  way  we’ve  always  done  things”. Developing  a  closed  loop  powder  management  system   including  powder  validation  which  utilises  digital  connectivity   to  both  monitor  and  control  every  aspect  of  the  process. Graham  Robertson  (LPW  Technology) Ben  Blackham  (MTC) Project  ref  103278
  • 8. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes • Material  alloy  development • Health  Safety  and  Environment    guidelines • Recycling  expertise • Education  and  Training Materials  and  processes Inspection,  Test  and  Standards Process  performance   captured  digitally Central  data   repository Project  ref  103278
  • 9. Project  title:  Tailorable  &  Adaptive  Connected  Digital  Additive  Manufacturing   (TACDAM) Abstract:  The  TACDAM  project  will  perform  targeted  Additive  Manufacturing   (AM)  pre-­‐ and  post-­‐process  value  chain  technology  developments,  develop   an  adaptive  quality  assurance  model,  introduce  parametric  design  as  a  key   process  variable  and  demonstrate  the  capability  to  deliver  cost  and  quality   outcomes  at  Manufacturing  Readiness  Level  6  to  the  automotive  industry. Presenter:  Dr Ben  Farmer  /  HiETA Technologies  Ltd Project  ref  103279
  • 10. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes • £  Automotive  &  staged  1/3/6s quality • Machine  learning  to  facilitate  automation  reduce   cost  and  variability • Design:  Quantification  of  the   performance/yield  trade  off • Materials:  More  cost  effective  Inconel   &  titanium   • Inspection:  Non-­‐contact  inspection  to   establish  that  powder  is  removed • Supply chain:  Industry  vertical   • Design  methods  and  tools • Physics  and  AI-­‐based  modelling  for  design  and   manufacturing • New  Al  and  Ni-­‐based  materials • NDT/NDI  of  complex,  dense  parts • Automation,  simulation  and  optimisation  of  future   industrial  environment • Parametric  design   as  a  key  process   variable   • Started  at  MRL3,   currently  MRL5,   finish  at  MRL6 OperationsDesign Concept design AM process selection Detailed design, optimisation, DFM Build design and preparation Material Process and post-process Quality assurance AM process Powder removal Heat & pressure treatment Removal from plate Support removal Machining and smoothing Surface treatment Destructive testing of traveller NDT/NDI Finished part Validation testing Maintainence Overhall Repair £££ ££ £ ££ £ ££Cost  challenges Quality  challenges ££ Project  ref  103279
  • 11. Automated  Post-­‐Processing  Platform  for  Metals  Additive   Manufacturing  – (PLATFORM) One  of  the  key  technical  challenges  facing  the  metal  AM   market  is  the  need  for  post-­‐processing  of  parts  to  achieve   required  tolerances.  The  PLATFORM  project  aims  to   revolutionise  the  way  in  which  metal  AM  products  are   finished  by  developing  a  modular  system  and  automatic  CAM   software  for  support  removal  and  proof  machining. Dr.  Dave  Cooper  – Progressive  Technology Project  ref  103453
  • 12. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes • Deliver  a  modular  work  holding   system  to  enable  end  to  end  complex   AM  part  production  and  reduce   fixture  costs • Automate  CNC  support  removal  &   proof  machining. • Combine  with  efficient  CT  techniques   to  aid  alignment  of  machining  to   blanks  and  reduce  setup  time/scrap • First  steps  toward  AM/CNC   integration  have  begun • Key  issues/likely  problems  are   beginning  to  be  understood • Streamlines  production  of  high  value   machined  AM  parts • Reduces  scrap  and  “black  magic”,   lowering  barriers  to  entry  for  SME’s • Integration  of  AM  into  post   processing  supply  chain   Project  ref  103453
  • 13. AMSURFIN  -­‐ Additive  Manufacturing  SURface FINishing -­‐ An  automated  intelligent  solution  for  polymer  parts The  project’s  vision  is  to  create  an  automated  intelligent   post  processing  machine  capable  of  finishing  additively   manufactured  thermoplastic  polymer  parts  to  an  injection   moulded  level  surface  finish. Joseph  Crabtree  /  Additive  Manufacturing  Technologies   Limited Project  ref  103275
  • 14. Project  Objectives Your  requests  to  UK  Research  (Universities,  UKRI)How  does  this  contribute  to  delivering  the  AM-­‐UK  Strategy? Progress/  Learning/  Outcomes 1. Create  a  saleable  automated  post  processing   machine  capable  of  generating  a  repeatable  and   reproducible  surface  finish  equivalent  to  that   achieved  in  injection  moulding  for  additively   manufactured  parts. 2. Develop  intelligent  algorithms  that  control  the   amount  of  post  processing  for  a  given  material   and  geometric  design. 3. Develop  a  machine  that  is  integrated  into  the   digital  manufacturing  chain.   1. Directly  addresses  the  issue  around  the   optimisation  and  automation  of  Post  Processing   in  3D  Printing. 2. Protected  by  IP  and  CE/UL  Standards. 3. Industry  4.0  compliant. 1. Understanding  the  total  value  chain  proposition   from  Materials  à parts. 2. Application  and  Industry  4.0  relevant. 3. Must  have  ‘hands  on’,  practical  approach. Project  ref  103275