1. Shaping the Future
Knowledge-based approach to
assembly equipment selection – A
fuel cell case study
IECON Japan – 12th November 2015
Mussawar Ahmad
musssawar.ahmad@warwick.ac.uk
Co-Authors
Borja Ramis Ferrer, Prof. Robert Harrison, Dr
Bilal Ahmad, Prof. José L. Martinez Lastra, Dr.
James Meredith, Dr. Axel Bindel

2. Outline
 Background
 The big picture and the this work
 The fuel cell problem
 What is manufacturing know-how?
 Storing knowledge
 Model description
 Test and results
 Conclusion
 Proposed further work

3. Background
 Automation Systems Group – WMG
– Industrial automation systems
– 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) regarding domain mapping
 PhD sponsored by EPSRC and High Speed
Sustainable Manufacturing Institute (HSSMI)

4. The big picture
 To be competitive, manufacturers must be able to quickly meet
many demands of many customers and maintain affordability
 This means MASS CUSTOMISATION
 CUSTOMISATION = PRODUCT VARIETY + HEADACHE
 Requires flexibility and reconfigurability in the manufacturing
system
 This research focuses on assembly system, using a PPR model
Product
Process
Resource
Time
Maturity of
product
realisation
Concurrency is supposed to
reduced lead times, but
without effective
communication between
domains, time and cost can
increase i.e. pure series
approach could be better!

5. characteristics
components
performance
The big picture
Product
Process
requirements sequence
bill of process
tasks
Resource
equipment
safety
Build &
Commission
factory – make
mistakes layout
.
.
.
.
.
.
.
.
Product
realisation
process
• Different organisations
• Different “language”
• Cultural differences
• Loss of critical information
• Lack of effective communication
up and downstream

6. This work
characteristics
components
performance
Product
Process
requirements sequence
bill of process
tasks
Resource
equipment
safety
layout
.
.
.
More detailed mapping, with more considerations about
the PRODUCT. Thus, if product characteristics are changed,
the assessment of impact on the assembly system is more
accurate

7. Fuel Cells – General Types
Proton Exchange Membrane

8. PEM - Operation

9. PEM Applications and Types
Horizon H-series
10 100 500 1000 2000 5000 10000 50000 100000
Horizon XP-series
Horizon AEROSTACKS
Horizon MFCs
Aircooled
Nuvera Orion
Liquidcooled
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)

10. PEM Assembly
Diffusion layers
Membrane “Sub”-cell
Also referred to as an MEA
(membrane electrode
assembly)
Gaskets

11. PEM Assembly
Open 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?

12. Know-how
The Problem
Fuel 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

13. 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]
Extensible
Scalable
Flexible

14. Ontological model- PPR
Whatisneeded?
Howtoputittogether?
Whatisbeingmade?
ResourceDomain
Volumes
Requirements
Cost
ProcessDomainProductDomain
EnterpriseDomain Customer/
Competition
Ontology
Semanticrules
Mapping
Axioms
Product
Characteristics
Factory
commissioning
Virtualengineeringandcommissioningto
UseparametricproductCADto
quicklyassesswhatchanges
may berequiredon the
manufacturingsystem.

15. 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

16. What do the domains look like?
Product Domain

17. What do the domains look like?
Process Domain

18. What do the domains look like?
Resource Domain

19. The bigger picture

20. The even bigger picture
Whatisneeded?
Howtoputittogether?
Whatisbeingmade?
ResourceDomain
Volumes
Requirements
Cost
ProcessDomainProductDomain
EnterpriseDomain Customer/
Competition
Ontology
Semanticrules
Mapping
Axioms
Product
Characteristics
Factory
commissioning
Virtualengineeringandcommissioningto

21. Liaisons and Precedence
This method allows the modelling of the PROCESS SEQUENCE
and thus the ASSEMBLY EQUIPMENT CONFIGURATION

22. Model
Only modelled the
relationship between
the GDLs and the CCM
to test…

23. Testing and Results
 Queries are written using SPARQL to test the model
 Two tests were carried out
Resource
Domain
Process
Domain
Product
Domain
1. Check that the mappings results in the
selection of appropriate equipment
2. Check the model technique for
precedence works

24. Query 1
Correctly selected appropriate
assembly equipment i.e. Robot + gripper

25. Query 2
Correctly ordered and labelled the
liaisons between components

26. 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
– Standards not used! ISA-95 is being used by TUT

27. Further Work
XML File
Ontology
Resource
Domain
Process
Domain
Product
Domain
What is being
made?
How to put it
together?
What is
needed?
Volumes
Requirements
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.
0. At component level (this work)
1. At station level
2. At line level
3. At factory level

28. Acknowledgement
Questions
Contact Details:
Mussawar Ahmad
mussawar.ahmad@warwick.ac.uk