shaping the future a pem fuel cell ontology to facilitate assembly line generation using a semantic...
TRANSCRIPT
Shaping the Future
A PEM fuel cell ontology to facilitate assembly line generation using a
semantic approach: A proof of concept
WMG Doctoral Research and Innovation Conference 30th June - 1st July
Mussawar [email protected]
SupervisorsProf. Robert HarrisonDr. James Meredith
Dr. Axel Bindel
Outline
Fuel cell background Problem identification – manufacturing know-how A proposed solution using knowledge
representation Model description Test and results Conclusion Further work
Background Automation Systems Group – WMG– Automation in manufacturing– Process control– Virtual engineering – Tools developed for virtual commissioning
Partnered with Arcola Energy on Innovate UK – Fuel Cell Manufacturing Project
Collaboration with Tampere University of Technology (TUT)
PhD sponsored by EPSRC and High Speed Sustainable Manufacturing Institute (HSSMI)
Fuel Cells – General Types
Proton Exchange Membrane
PEM - Operation
PEM Applications and Types
Horizon H-series
10 100 500 1000 2000 5000 10000 50000 100000
Horizon XP-series
Horizon AEROSTACKS
Horizon MFCs
Air c
oole
d
Nuvera Orion
Liqu
id c
oole
d
Ballard FCgen 1020ACS
Ballard FCgen 1300
Ballard FCvelocity 9SSL
Horizon Educational
The H-Series stacks are not designed with a specific application in mind
Power (W)
PEM - Power
Single Cell
More cells=
More voltage=
Taller stack
Larger surface area=
More current=
“Fatter” stack
Fuel cell stack
Find the right balance to meet POWER needs
PEM Assembly
Diffusion layers
Membrane “Sub”-cell
Also referred to as an MEA (membrane electrode assembly)
Gaskets
PEM AssemblyOpen cathode Stack Closed cathode stack Liquid cooled stack
More power
More complexity
But…there is an underlying commonality!
If you can make one, can you make them all?
Know-how
The ProblemFuel cells are great, but…
Lack of hydrogen infrastructure
Costly compared to incumbent technologies
Material costs Manufacturing costs
Assembly Component manufactureAssembly costs:• 10-30% [1] of labour• Up to 50% of total
manufacturing [2, 3]
[1] J. L. Nevins and D. E. Whitney, “Concurrent design of product and processes,” McGraw-Hill, New York, 1989 [2] U. Rembold, C. Blume, and R. Dillmann, “Computer- integrated manufacturing technology and systems,” Mar-cel Dekker, New York, 1985 [3] S. S. F. Smith, “Using multiple genetic operators to re-duce premature convergence in genetic assembly plan-ning,” Computers in Industry, Vol. 54, Iss. 1, pp. 35–49, May 2004.
Equipment
Processes
Methods
Control
Criticality
Tolerances
Sequence
The Proposed Solution
Know-howKnowledge
Capture Store Reuse
Knowledge-baseOntology
“an explicit specification of a conceptualization” [4]
[4] T. R. Gruber, A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2): 199-200, 1993[5] Jose L. Martinez Lastra, Ivan M. Delamer, Fernando Ubis; Domain Ontologies for Reasoning Machines in Factory Automation; ISBN: 978-1-936007-01-1, 2010; 138 pages
Formally describe a ‘domain’ [5]
ExtensibleScalableFlexible
Ontological model - PPR
What is needed?
How to put it together?What is being
made?
Resource Domain
VolumesRequirements
Cost
Process Domain
Product Domain
Enterprise Domain
Customer/Competition
Ontology
Semantic rules
Mapping
Axioms
Pro
du
ct
Ch
ara
cte
risti
cs
Facto
ry
com
mis
sio
nin
g
Virtual engineering and commissioning tool
Use parametric product CAD to quickly assess what changes may be required on the manufacturing system.
Ontological Model Used Protégé - an ontology editor Uses a semantic language – Web Ontology Language (OWL) Extension of Resource Description Framework (RDF) Queried using SPARQL Protocol and RDF Query Language (SPARQL) Rules can be written in Semantic Web Rule Language (SWRL) RDF-based models are RDF triples which semantically describe concepts Mimics and formalises natural language Model has classes, hierarchies and relationships These are used to describe real world concepts
Subject Predicate Object
FuelCell hasType PEMFuelCell
PEMFuelCell hasVariant OpenCathodeCathodeStack
OpenCathodeStack hasComponent AnodeFlowFieldPlate
AnodeFlowFieldPlate hasLiaisonWith AnodeGDL
What do the domains look like?
Product Domain
What do the domains look like?
Process Domain
What do the domains look like?
Resource Domain
The bigger picture
The even bigger picture
What is needed?
How to put it together?What is being
made?
Resource Domain
VolumesRequirements
Cost
Process Domain
Product Domain
Enterprise Domain
Customer/Competition
Ontology
Semantic rules
Mapping
Axioms
Pro
du
ct
Ch
ara
cte
risti
cs
Facto
ry
com
mis
sio
nin
g
Virtual engineering and commissioning tool
Liaisons and Precedence
This method allows the modelling of the PROCESS SEQUENCE and thus the ASSEMBLY EQUIPMENT CONFIGURATION
Model
Only modelled the relationship between the GDLs and the CCM to test…
Testing and Results
Queries are written using SPARQL to test the model Two tests were carried out
Resource
Domain
Process Domain
Product Domai
n
1. Check that the mappings results in the selection of appropriate equipment
2. Check the model technique for precedence works
Query 1
Correctly selected appropriate assembly equipment i.e. Robot + gripper
Query 2
Correctly ordered and labelled the liaisons between components
Conclusion The concept has been proved– Equipment can be generated– Sequence model works
Designed to allow the addition of more information in the future
Some progress on building a fuel cell assembly KB BUT– It’s a time consuming process– Concepts being modelled are simple - unforeseen
complexity may need a model redesign
Further Work
XML File Ontology
Resource Domain
Process Domain
Product Domain
What is being made?
How to put it together?
What is needed?
VolumesRequirements
Cost
Enterprise Domain
Customer/Competition
XML File
Virtual engineering and commissioning tool
Use parametric product CAD to quickly assess what changes may be required on the manufacturing system.
