Computer methods for assessing reliability of complex structures
Submitting Institution
University of GreenwichUnit of Assessment
Computer Science and InformaticsSummary Impact Type
TechnologicalResearch Subject Area(s)
Mathematical Sciences: Applied Mathematics
Information and Computing Sciences: Artificial Intelligence and Image Processing
Engineering: Materials Engineering
Summary of the impact
The Computational Mechanics and Reliability Group at the University of
Greenwich has been
developing computational methods for predicting material behaviour and
component reliability
since the late 1990s. This case study details economic and environmental
impacts and impacts on
practitioners. In particular it shows how our expertise has:
- substantially aided companies to predict reliability of new electronic
systems before
physical prototyping providing significant cost savings;
- enabled companies to assess impact of new materials that address
environmental
legislation;
- provided information to the Cutty Sark Trust in help maintain this
national maritime
treasure.
Underpinning research
The university uses computational methods to assess the performance of
engineering structures. It
predicts how multi-component, multi-material systems will behave in myriad
situations including
variations in temperature, pressure, vibration, humidity, and over time. A
central theme of the work
is the development of methodologies for acquiring data, and predicting
material behaviour and
reliability of complex engineering structures — from heritage ships to
miniaturised electronic
components.
a) Multi-physics modelling and optimisation
Research began in the early 90s when we developed multi-physics tool
PHYSICA which uses finite
volume and finite element techniques to solve the governing equations of
fluid flow, heat transfer,
and stress in a coupled manner on high performance computers [3.1]. We
have coupled these
predictions with numerical optimisation tools to provide a framework that
is capable of performing
design optimisation procedures in an entirely automated and systematic
manner [3.2]. Supported
by numerous EPSRC projects [3a, 3b] this framework was used to predict the
reliability of
miniaturised electronic components. To use these tools effectively we
required data from physical
experiments and the input of design constraints such as environmental
operating conditions. With
these inputs, this framework was used to optimise the design of underfill
materials and solder joints
in packaged electronic components that addressed EU legislation such as
the Reduction of
Hazardous Substances Directive. Outputs from our work were used by our
industrial partners
Henkel, Celestica, MicroEmmisive Displays, DEK Printing Machines to
provide information that
was used to optimise their manufacturing processes.
Funded by the US Government [3c] in collaboration with Selex-Electronic
Systems, Rolls Royce,
General Dynamics, and Micross Semiconductors, we have extended the above
approach so that
our computational analysis is used within the qualification process for
assessing the performance
of a robotic controlled refinishing process for semiconductor packages
that are to be used in high
reliability applications. To ensure that the thermal modelling techniques
have accurate input data
we have integrated data obtained from material characterisation (eg
Scanning Electron
Microscopy, Scanning Acoustic Microscopy), and internal semiconductor
package geometric
characterisation (eg computer tomography) within the thermal modelling
computer analysis
software. For example data from computer tomography (eg .stl files) is
used to develop the finite
element models of the semiconductor package and data from scanning
acoustic microscopy to
assess any damage in the package. The results from the thermo-mechanical
modelling analysis
has been used to investigate different operating conditions of the robotic
controlled refinishing
process and hence optimise this process in terms of the temperatures that
the semiconductor
device is exposed to during manufacture [3.3].
b) Surrogate modelling
Undertaking extensive finite element analysis of semiconductor packages
within a design space
that has multi-dimensions in terms of design variables, and whose values
will have manufacturing
variability, is far too time consuming even for the most powerful
computers. To address this we
have used optimisation and statistical techniques to develop surrogate
models whose predictive
accuracy is the equivalent of a detailed finite element model in assessing
the reliability of these
packages. This work was originally supported under a Department of Trade
and Industry project
[3e] in collaboration with Dynex Semiconductors and SEMELAB and extended
under the EU
project PEMREL [3f]. Here we used design of simulation techniques to
develop fast surrogate
models that can be used to predict stress in the semiconductor packages
when subjected to
thermal or vibration loadings [3.4]. This led on to the development of the
PowerLife software tool
which embeds these surrogate models for power electronic package
reliability assessment. This
tool is now used within both companies to optimise designs of power
modules before physical
prototyping.
c) Prognostics and health monitoring
The ability to use surrogate models to predict semiconductor package
material behaviour has led
on to the development of prognostics and health management tools to
monitor the remaining
useful life of semiconductor packages when they are used in the field: in
particular for high power
Light Emitting Diodes (LED) where we used computational learning
algorithms to monitor the
degradation of light emitted by the diode by monitoring changes in
electrical current and voltage of
the semiconductor [3.5]. Our expertise in this area has also been used to
monitor the degradation
of aged heritage structures (eg the iron frame of the Cutty Sark clipper
ship) where we have
demonstrated that data from sensors monitoring temperature changes,
humidity and footfall can be
used within a Bayesian Network to assess degradation of the iron frame
over time [3.6]. This work
was supported by the Cutty Sark Trust in parallel with a Knowledge
Transfer Project [3g] that
investigated the structural behaviour of the ship during the recent
conservation programme.
Key staff: Professor Chris Bailey — Director of the Computational
Mechanics and Reliability Group
and project manager; Dr Stoyan Stoyanov (Reader), Dr Yasmine Rosunally
(now at University of
West London), Dr Xiangdong Xue (now at University of Sheffield).
References to the research
(REF 1 submitted staff in bold,**REF2 Output)
3.1 Bailey, C., Chow, P., Cross, M., Fryer, Y., & Pericleous, K.
(1996). Multiphysics Modelling of the
Metals Casting Process. Proceedings of the Royal Society of London.
Series A: Mathematical,
Physical and Engineering Sciences, 452(1946), 459-486.
http://dx.doi.org/10.1098/rspa.1996.0024
3.3 Stoyanov, S., Best, C., Yin, C., Alam, M. O., Bailey, C.,
& Tollafield, P. (2012). Experimental
and modelling study on the effects of refinishing lead-free
microelectronic components (pp. 1-6).
Presented at the Electronic System-Integration Technology Conference
(ESTC), 2012 4th,
IEEE. Amsterdam, Neitherlands. http://dx.doi.org/10.1109/ESTC.2012
3.4 Xue, X., Bailey, C., Lu, H., & Stoyanov, S. (2011).
Integration of analytical techniques in
stochastic optimization of microsystem reliability. Microelectronics
Reliability, 51(5), 936-945.
http://dx.doi.org/10.1016/j.microrel.2011.01.008
**3.5 Sutharssan, T., Stoyanov, S., Bailey, C., & Rosunally, Y.
(2012). Prognostics and Health
Monitoring of High Power LED. Micromachines, 3(1), 78-100.
http://dx.doi.org/10.3390/mi3010078
3.6 Rosunally, Y., Stoyanov, S., Bailey, C., Mason, P., Campbell,
S., Monger, G., & Bell, I. (2010).
Bayesian Networks for Predicting remaining Life. International Journal
of Performability
Engineering, 6(5), 499-512.
Research/consultancy grants:
3a EPSRC (GR/N14095), 2000-2002, £110,000 — Lead-Free Soldering for
Flip-Chip Assembly
Applications
3b EPSRC (GR/R09190 and GR/R09206/02), 2001-2003, £243,463 — Microsystems
Assembly
Technology for the 21St Century — MAT21
3c US Government (H94003-04-D-003-0056), 2011-2014, US$320,000
3d DTi (TP/3/DSM/6/I/16796), 2006-2009, £230,962 — Modelling Power
Modules (MPM)
3e EU Clean Skies (Grant No. 271788), 2010-2013, 200,000 euros — PEMREL
3f Cutty Sark KTP Project (Programme no: 000232) 2004-2008, continuation
through funding
from Cutty Sark into 2010. Awarded to University of Greenwich, Total
funding £150,000.
Details of the impact
Economic impact
The value of the electronics manufacturing industry worldwide is ~US$2tn;
Europe accounts for
~20% of this. Advances in electronics components and systems technologies
underpin much
larger markets which include industrial sectors, eg aerospace, automotive,
energy generation,
medical devices etc, and service sectors, eg internet, games,
broadcasting, telecoms etc, which
account for approximately 10% of world GDP.
Our multi-physics(1) and optimisation work(2), in
collaboration with Henkel, DEK Printing machines,
and Celestica, has provided a route to predict the reliability of
sub-100um pitch interconnections
using lead-free solder pastes. Our work in optimising the refinishing
process of electronic
components for use in high reliability aerospace applications(3)
has been funded by the US
Department of Defense and industry, and has developed a methodology to
reduce dramatically the
amount of physical testing required to prove integrity, where normally
such testing can cost
upwards of £100,000 per component.
The overall cost of saving the Cutty Sark for the nation was £50M of
which the Heritage Lottery
awarded £25m. Scientific underpinning provided by the university was
instrumental in securing
Lottery funding, and structural health monitoring work by the university
was a condition of the
award. An aim was to minimise the amount of new conservation work required
for at least 50
years: we developed a decision support tool(6) for
post-restoration maintenance of the vessel,
ensuring that potential future losses due to structural problems with the
ship have been mitigated.
Our overall contribution has also secured local jobs for 20 people who now
work on the Cutty Sark.
This international icon is helping to boost tourism which plays such an
important role in the UK
economy, adding £12bn per year to GDP and supporting over 195,000 jobs.
Environmental impact
European legislation such as the Reduction of Hazardous Substances (RoHS),
and Waste
Electrical and Electronic Equipment directives, have posed significant
challenges for the
electronics industry in finding replacements to a number of materials used
in electronics
manufacturing — including lead-based solders. Our work in assessing the
reliability of electronic
components using material replacements such as Tin-Silver-Copper solders(2-4)
has helped our
industry partners meet these challenges as well as avoid the placement of
harmful materials such
as lead in landfill. Although RoHS only applied to certain sectors (eg
high reliability sectors have an
opt-out) the use of commercial lead-free components in high reliability
systems means that that
most sectors have had to abide with the RoHS legislation. Our work on
power electronics
modules(4) and the use of our tool — PowerLife — by industrial
partners is providing a route for the
adoption of power electronics modules in a wide range of applications
including aerospace, rail and
automotive. For example our work on glob-top materials clearly identified
this as a process to
increase the reliability of wirebond interconnects in harsh environments.
The adoption of power
electronics has the potential for energy savings of $400Bn annually and
the UK is well placed to
benefit from innovations in this area.
Impact on practitioners
Our work has resulted in design rules for a number of companies who are
using these to ensure
that quality and reliability requirements of their components are met.
Examples include Selex
Electronic Systems, who are using our modelling technologies as part of
their qualification process
for avionics electronics. In addition to this our expertise in
computational intelligence and
prognostics(5,6) is contributing to the new IEEE Standard P1856
(http://bit.ly/1a2eZy0) — Prognostics
and Health Management of Electronic Systems. Our modelling expertise has
also
contributed to the 2013 International Electronics Manufacturing Initiative
Roadmap
(http://bit.ly/1ea0Hjk). We work
closely with the National Microelectronics Institute and the IEEE
(where Professor Bailey is UK&RI Chapter Chair for the IEEE
Components, Packaging, and
Manufacturing Technology Society, and Reliability Society) in
disseminating our research outputs
to practitioners.
Sources to corroborate the impact
- Director of Product Development, Henkel Technologies (UK),
Beneficiary, can provide a
statement on the impact our work has had on new solder and adhesive
materials development
- CTO, Selex-Electronic Systems, Beneficiary, can provide a statement on
the impact of our
work for predicting the reliability of avionic electronic systems
- R&D Manager, Dynex Semiconductors Limited, User, can provide a
statement on the impact of
our work for predicting the reliability of power electronics modules
- Chief Engineer Cutty Sark Trust (2004-2009), User, can provide a
statement supporting the
impact that our work had details of how our work helped inform his
engineering decisions and
those of the contractors working on the project.
- Engineering Director, Micross Semiconductor Limited, Beneficiary, Can
provide a statement on
how our work on the robotic refinishing process has helped optimise the
process.
- IEEE Standard P1856 (http://bit.ly/1a2eZy0)
— Standard Framework for Prognostics and Health
Management of Electronic Systems, Chair is Professor Michael Pecht
(pecht@calce.umd.edu),
University of Maryland. University of Greenwich based on its research in
reliability of
electronics systems is a member of the working group.
- BBC News: http://bbc.in/17CcYW1,
demonstrating outreach with the media and informing the
public of our work for the heritage sector.