Shaping the Future

Knowledge-based approach to assembly equipment selection – A

fuel cell case study

IECON Japan – 12th November 2015

Mussawar Ahmadmusssawar.ahmad@warwick.ac.uk

Co-AuthorsBorja Ramis Ferrer, Prof. Robert Harrison, Dr Bilal Ahmad, Prof. José L. Martinez Lastra, Dr.

James Meredith, Dr. Axel Bindel

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

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)

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!

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

This work

characteristics

components

performance

Product

Process

requirements sequence

bill of process

tasks Resource

equipment

safetylayout

.

.

.

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

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 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

Prod

uct

Char

acte

rist

ics

Fact

ory

com

mis

sio

ning

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

Prod

uct

Char

acte

rist

ics

Fact

ory

com

mis

sio

ning

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

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

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.

0. At component level (this work)1. At station level2. At line level3. At factory level

Acknowledgement

Questions

Contact Details:Mussawar Ahmad

mussawar.ahmad@warwick.ac.uk