Novel Statistical Methods for Optimising Production of Disc Brake Pads
Submitting Institution
University of ManchesterUnit of Assessment
Mathematical SciencesSummary Impact Type
TechnologicalResearch Subject Area(s)
Mathematical Sciences: Statistics
Economics: Econometrics
Summary of the impact
Novel statistical methods were developed in order to address the needs of
Federal-Mogul
Corporation (FM), an innovative and diversified $6.9bn global component
supplier to vehicle
manufacturers, with a broad range of customers in the industrial sector.
During 2012, the research
underpinned the production of new disc brake pad products for Audi, BMW,
Ford, GM, Mercedes
Benz and VW. The research has already resulted in significant benefits for
the company by
improving the manufacturing process, allowing it to be optimised to a mean
specification, and by
reducing the production cycle time by 30%.
Underpinning research
The impact is based on research that has been conducted at The University
of Manchester since
2008 and was carried out by
Dr. Alexander Donev (Senior Lecturer, September 2007 — present)
Mr. Liam Brown (PhD student 2010 — present) [fully funded by FM],
Mr. Sergio Loeza-Serrano (PhD student 2009 — present), [undertook sKTP
with FM in 2011]
The principal outcomes of the research were:
- the development of novel statistical methodology to inform the design
of physical
experiments used in product testing. The key insights were to take prior
information into
account when evaluating sources of variability in the manufacturing
process; and to develop
a novel graphical representation of the results to aid decision making
[1]. The new methods
allow the design of experiments in the most efficient and economical way
[2].
- the development of new statistical models for studies of products
constructed from different
mixtures of materials, as well as methods for designing experiments to
collect the data
required by such models. The key insight was to use models that are
nonlinear in
parameters, formulated in terms of estimable flexible regressors. These
can describe fast
changing and localized effects which had not been possible with standard
statistical models
for mixture experiments. Nonlinear models of this kind had never
been proposed before
and are potentially applicable to a huge range of other industrial
processes.
References to the research
The research has been published in a leading journal in computation and
statistics, the official
journal of the International Association of Statistical Computing [1].
[2] Technical Report prepared for Federal-Mogul.
Details of the impact
Context
Federal-Mogul Corporation (FM) is a leading global supplier of products
and services to the world's
manufacturers and servicers of vehicles and equipment in the automotive,
light, medium and
heavy-duty commercial, marine, rail, aerospace, power generation and
industrial markets. The
company's products and services enable improved fuel economy, reduced
emissions and
enhanced vehicle safety.
In 2008 FM approached Dr. Alexander Donev for help in reviewing
statistical issues in their
experimental practices both in R&D and in the manufacture of friction
materials for use in disc
brakes. Poor repeatability and prediction from experiments using different
material compositions
had led them to suspect that there could be something missing in the
existing statistical
methodology.
Prior to the work described in this case study, FM had used open source
and commercial software
(e.g. R, JMP) to design and analyse their experimental studies. However,
there is no such software
that can be used to construct designs for studying variability, and
therefore the company was using
only the so-called six-sigma methods. The benefits that such methods can
bring were already
exhausted, and more advanced statistical methods were required to achieve
the necessary
reduction in manufacturing variability.
Pathways to the Impact
Since approaching Dr Donev in 2008, Federal-Mogul has funded the PhD
studentship of Liam
Brown, as well as an sKTP project with Sergio Loeza-Serrano. The very
nature of the projects
provided a natural pathway to implementing the results in the company's
technological processes.
The novel models have been reported directly to Federal-Mogul [2] along
with computer codes that
implement the new statistical methods. Consequently, the new experimental
designs have become
standard procedures within the company. The collaboration remains active
and an EPSRC grant
application, with financial commitment of £250k from Federal-Mogul, has
been submitted.
An additional pathway to broader impact is provided via open source
versions of the computer
codes that implement the new statistical methods, which have been made
available for other
academic and non-academic users.
Reach and Significance of the Impact
The research has had a significant influence on the practices within FM.
Comparative analysis of
variation data from a recent production study and the methodology proposed
[1] showed that
statistically the same conclusions could have been reached with only 12%
of the experimental trials
originally used by the company, leading to considerable savings in R&D
and in manufacturing [S1].
As a result, the new experimental designs have been adopted as standard
procedures within
Federal-Mogul [S1].
The first commercial application of the research was for modelling and
optimising the production of
a new design of the disc pad for Ford P415 SUV vehicles (typical US sales
of 40,000 per year
since 2010 [S2]). Response surface models based on the design were
verified experimentally and
found to be highly accurate. Disc brake pad production costs are due to
combination of raw
material costs and manufacture. The manufacturing costs are particularly
sensitive to process cycle
times, which determine the production rates on the allocated presses.
Application of the new
statistical methodology identified optimal process conditions that lead to
a 30% reduction in overall
cycle time compared to that previously obtained with a conventional
production engineering
approach. This reduction in cycle time was critical to the economic
viability of the product and lead
to substantial cost savings for the company [S1].
Further analysis of the new model identified multiple solutions that made
it possible to select
production process conditions to yield the desired specification with
minimum inherent variation. To
combine these aspects of maximising production efficiency with maximizing
product quality
requires accurate and detailed process models, which the company had been
unable to achieve
without such an effective experimental design [S1].
Following the outstanding success of this Ford project, the use of same
basic design has become a
standard procedure within Federal Mogul for introducing new friction
products into production.
During 2012, based on this experimental design, new disc brake pad
products for Audi, BMW,
Ford, GM, Mercedes Benz and VW have been optimised for production [S1].
Sources to corroborate the impact
[S1] Letter from Federal Mogul supporting claim that FM have adopted the
new experimental
designs; that cost savings have been made; production cycle times reduced;
and that the designs
have been used in brake pad production for the vehicle manufacturers
listed in the case.
[S2] http://www.goodcarbadcar.net/2011/01/ford-expedition-sales-figures.html
(Gives yearly US sales figures for the Ford Expedition (P415 SUV))