Fortissimo Success Stories
Fortissimo`s Small & Medium, Manufacturing Enterprises

5th Edition - Volume II

Index4

Chapter 1:
The Fortissimo Marketplace

6

Chapter 2:Core Partners

8

Chapter 3:
Experiment Partners

10

Chapter 4:
Fortissimo Success Stories

34

Chapter 5:
Map of Success Stories

35

Chapter 6:
Projects at a Glance						
Fortissimo Success Stories - Fortissimo`s Small & Medium,
Manufacturing Enterprises - 5th Edition - Volume II, January
2018

The research leading to these results has received funding from the European Union Seventh
Framework Programme under grant agreement No 609029 and from the European European
Union’s Horizon 2020 research and innovation programme under grant agreement No 680481.
www.ec.europa.eu

www.fortissimo-project.eu

The Fortissimo Marketplace
The Fortissimo project is funded by the European Commission within the I4MS initiative (ICT
Innovation for Manufacturing Small & Medium Enterprises) framework. It consists of twophases: the first phase began in July 2013 and ended in December 2016; the second phasebegan in November 2015 and will end in October 2018.

SME PARTICIPATION
Fortissimo collaborates with SMEs, technical experts, independent software vendors(ISVs) and HPC-Computer centres to demonstrate the business benefits of Cloud-basedHPC simulations. SMEs can propose potential experiments through “open calls”. During
the 18-month duration of an experiment, the Fortissimo partners provide the participating
SMEs with free access to HPC-resources via a cloud-infrastructure and support them in theplanning, implementation and realisation of their experiment.

SUCCESS STORIESTHE AIM OF FORTISSIMO
The aim of Fortissimo is to strengthen the global competitiveness of European industry.
Fortissimo drives the uptake of advanced modelling, simulation and data analytics by
European engineering and manufacturing Small & Medium Enterprises (SMEs) and midcaps. Such an uptake will deliver improved design processes, better products and services,
and improved competitiveness. For the European Union as, a whole this means improved
employment opportunities and economic growth.

A success story is a summary of an experiment focusing on the resultant business benefits.
It has four main sections, the first presents the organizations involved in the experiment– SME as the end user, HPC provider, technical expert, and ISV; the second presents thechallenge where the reason for the experiment is described; the third presents the technicalsolution deployed in the experiment; the fourth presents the benefits resulting from the
exploitation of the solution.

THE BOOKLETTHE CHALLENGE
In the past, gaining access to the resources required for digital simulation has often posedserious technical and financial challenges to SMEs. Through the use of High Performance
Computing (HPC) simulations available via a cloud-based infrastructure, opportunities forbusiness benefits can be identified and applied across the complete value chain, thus saving
companies time and money and improving their competitive position.

This booklet presents eleven success stories from the second phase of the project. Further
success stories will be added as the respective experiments are completed.

THE MARKETPLACEThe Fortissimo Marketplace – launched in October 2016 – provides all European businesses,
in particular Small & Medium Enterprises (SMEs), with permanent, simple and cost-effective
access to the hardware, software, and expertise required for computationally intensive
simulations, via an on-demand, pay-per-use, “one-stop-shop” model.
Improvements resulting from the Fortissimo Marketplace approach are manifold, including:better and more precise design of complex components and systems; acceleration of timeto-market; and cost savings in development, production and operation.

For further information, please visit: www.fortissimo-project.eu

Joint review of I4MS projects in Edinburgh.
45Core Partners
For each Fortissimo experiment one of the core-partners acts as a provider of highperformance computing resources and expertise, enabling the other project partners to makebest use of HPC in their solution. Providing HPC resources on a pay-per-use basis removes
the need for the other partners to invest in their own HPC hardware, cutting costs. The corepartners benefit by generating income from the services via the Fortissimo Marketplace, andby developing new partnerships with users of those services. This helps keep them at theforefront of innovative support for industry.

THE UNIVERSITY OF EDINBURGH
EPCC is a leading European centre of excellence in advanced
research, technology transfer, and the provision of high-performancecomputing services to academia and industry.
www.epcc.ed.ac.uk

ARCTUR

Gompute is a leading HPC Cloud company, offering expert services
and full support to a large number of users worldwide. It delivers
comprehensive solutions for High Performance Computing, both inhouse and as a service.
www.gompute.com

HLRS – UNIVERSITY OF STUTTGART

The High Performance Computing Centre (HLRS) is one of threenational computing centres affiliated to the University of Stuttgart.
It operates and provides compute resources to research groups andindustry.
www.hlrs.de

INTELIntel (NASDAQ: INTC) is a world leader in computing innovation. The
company designs and builds the essential technologies that serve as
the foundation for the world’s computing devices.
www.intel.com

Arctur is the leading service provider of supercomputing inCentral Eastern Europe. Following the XaaS model, it leases thesupercomputer along with the services of system administration,code optimization or parallelization. Arctur delivers HPC services andsolutions to industrial and scientific users in various technologicallyintensive industries.
www.hpc.arctur.net

SCAPOS

ATOS

SICOS

Atos is a leader in digital services, with circa 100,000 employees in 72
countries. Its deep technology expertise and industry knowledge has
allowed it to build global client base across many different businesssectors.
www.atos.net/en

FUNDACION CENTRO TECNOLOGICO DE
SUPERCOMPUTACION DE GALICIA

Fundación Pública Galega Centro Tecnolóxico de Supercomputaciónde Galicia is a public foundation committed to the advancementof Science and Technical Knowledge, by means of research andapplication of HPC, communications and other IT resources for the
benefit of society.
www.cesga.es

CONSORZIO INTERUNIVERSITARIOCINECA’s mission is to enable the Italian and European researchcommunity to accelerate the scientific discovery using HPC resourcesin a profitable way, exploiting the newest technological advances.
www.cineca.it

6

GOMPUTE

Scapos was founded in 2009 for the sales, marketing and supportof software for technical computing and of advanced software
solutions. Its customers range from large industrial corporations andresearch institutes to SMEs.
www.scapos.com
Provides access to big data’s analysis, simulation and highperformance computing.
The Sicos BW GmbH, headquartered in Stuttgart, was founded in2011 by the Karlsruhe Institute of Technology (KIT) and the Universityof Stuttgart in order to facilitate especially small and medium
enterprises (SMEs) access to big data’s analysis, simulation and highperformance computing.
www.sicos-bw.de

SURFSARA

SURFsara supports research, education and industry in the
Netherlands in the areas of HPC and big data, through thedevelopment and provisioning of advanced ICT infrastructure,services and expertise.
www.surfsara.nl

XLAB

XLAB Research is recognized in Slovenia as one of the strongest
computer science research teams outside the academic world. Their
Its expertise lies in security and distributed systems.
www.xlab.si

7Experiment Partners

www.fortissimo-project.eu
89Fortissimo Success Stories
12

Cloud-based simulation for vehicle engineering
Koenigsegg, Sweden

14

Optimising gas and flame detector layouts in hazardous manufacturing andproduction plants
Micropack, United Kingdom

16

Advanced, cloud-based HPC simulation in the foundry business
ProService, Italy

18

HPC-based design of non-circular gears
STAM, Italy20

HPC-based high-resolution modelling of magnets
Magneti Ljubljana, Slovenia

22

Cloud-based-HPC optimisation of manufacturing processes
EMO Orodjarna, Slovenia

24

Cloud-based-HPC processing for knowledge generation in camshaft manufacture
EPC, Spain

26

Cloud-based simulation of box-framed timber beams
Maderas Besteiro, Spain

28

Near Real-time Analysis of Airframe Certification Test Data
Colosso, Netherlands

30

Cloud-based-HPC simulation of railway infrastructure for high-speed trains
Alstom, Italy

32

Predictive diagnosis services for the automotive industry
TEXA, Italy

www.fortissimo-project.eu
1011EXPERIMENT #701
HIGHLIGHTS
Industry Sector: 		
Automotive

Cloud-based simulation for vehicle
engineering

Country: Sweden
Software used:
iconCFD®

THE COMPANIES
Koenigsegg Automotive AB is a Swedish SME whose corebusiness is the development and production of highperformance, high-quality, limited-edition motor vehicles– so called hyper-cars. ICON Technology & Process
Consulting Ltd is UK company which specialises in
Computer Aided Engineering (CAE) services together with
IT/web/multimedia capabilities to manage and present
data.

THE SOLUTIONEnd User

HPC Expert and Provider

ISV

www.koenigsegg.com

www.epcc.ed.ac.uk

www.iconcfd.com

The solution developed by ICON is to provide cost-effective and easy-to-use access tohigh-performance computing. The ease of use is achieved by providing browser accessible‘apps’ which provide the necessary features to set up and analyse simulations. The apps
connect to HPC-systems which provide pay-per-use access; capital costs are avoided
altogether, as is the need for experienced personnel to run the HPC systems. The result for
the end-user is a feature-rich interface connected to computing resources capable of rapidly
returning simulation results. The entry cost and operational costs are very attractive for small
companies.

THE CHALLENGE
Analysing how air flows around a vehicle is essential to making it faster and more efficient.
Physical testing is expensive due to the costs of models and test facilities. Computer
simulation removes the need for these, and enables the engineers to make changes to thedesign more easily. However, simulating airflow with the required degree of accuracy requires
computing power beyond the reach of most designers, mainly due to the capital costs of theequipment.

12

BUSINESS IMPACT

BENEFITS

Obtaining an in-house capability for rotating wheel
aerodynamic simulation requires an initial investment of€200,000 - €300,000 including hardware, and software
licences allowing approximately 50 simulations per year.
In addition, an annual maintenance and operational costof approximately €100,000 including hardware warranties,
electricity, software licences, etc. is required. This is aprohibitive cost for SMEs.
In comparison, a streamlined process accessed on-line
and benefitting from on-demand HPC and ISV expertise
could cost as low as €900 per simulation to the end user,
therefore making high-end simulation affordable to SMEs.
This can reduce or even eliminate the need for physicaltesting, saving further time and money on models and windtunnels.
The experience of Koenigsegg is that around €100,000 can
be saved annually on design costs by using this technologythat was previously only affordable to large companies.
For ICON, the apps they have developed will allow them tooffer their services to new clients in the automotive SME
sector.

€100,000 annual
saving on design
costs – saving
30% over previous
solutions.
High-end simulations
for as little as €900
per simulation.
No need for SME topurchase expensive
equipment.
Significant timesaving as there isno need for physicaltesting.

13

EXPERIMENT #702
HIGHLIGHTS
Industry Sector: 		
Oil and Gas Processing

Optimising gas and flame detector
layouts in hazardous manufacturing
and production plants

Country:
United Kingdom
Software used:
FLACS Risk and FLACS
Cloud

THE COMPANIESMicropack is a British SME which designs, manufacturesand installs its own range of detectors for use in fire andgas safety. It also consults on fire and gas safety design
and gas dispersion. Gexcon AS is a Norwegian company
and the market leader in dispersion, fire and explosion
modelling software for hazardous production areas.
Gexcon develops the multi-physics modelling application
FLACS, a simulation tool used worldwide for safety studies.

THE SOLUTIONEnd User

HPC Expert and Provider

ISV

www.micropack.co.uk

www.epcc.ed.ac.uk

www.gexcon.com

The goal of the Fortissimo experiment has been to provide FLACS as Software as a Service(SaaS) offering, with the usage of HPC fully integrated in the FLACS GUIs, under the new
product name “FLACS-Cloud”. The new service enables Gexcon’s customers to tap into
powerful HPC-cloud resources seamlessly from the GUI, so that it appears no different to theuser compared to accessing a local cluster. The key difference is that the users only pay forthe time that they use, making it much more cost-effective. The access to HPC computing
resources available through the FLACS-Cloud service renders it feasible to apply proper CFDbased optimisation to the placement of gas detection systems. This is expected to result
in reduction of the costs for the installation and maintenance of the detection system, andlowering the risk of severe accidents in a facility.

THE CHALLENGE
Gas detectors are commonly installed in manufacturing and production facilities where
hazardous substances are processed (such as oil and gas installations), to automaticallyalarm and trigger safety measures in response to leak events. Gexcon, the software provider,produces FLACS, a CFD modelling software used for safety studies. To date, the amount ofcomputing power required for a CFD-based optimisation of gas detector layouts has beenprohibitive in terms of both costs and time. Gexcon and Micropack joined forces to develop
the next-generation methodology for gas detection system design.

14

BUSINESS IMPACT

BENEFITS

Using FLACS-Cloud, Micropack and other users canimprove safety and reduce the costs of detector
installations and ongoing operational expenses in industrial
and manufacturing facilities that incur potential risks of gas
leaks, explosions, fires, and other hazards.
Optimisation means that fewer detectors are needed tocover the same space. The cost savings of one or more
detectors per sector of the detection system can quickly
add up to figures in excess of €100,000. Typical gas
detection systems can easily comprise multiple tens ofdetectors, so the savings can run into millions of Euro per
installation.
The use of on-demand resources is attractive to Micropack,as they save tens of thousands of Euro on computing
equipment. Using HPC, a project’s computing phase
can also typically be shortened by up to a factor of ten(compared to using in-house resources), which will allow toservice more clients, and offer a better client experience.
Gexcon will offer FLACS-Cloud via the FortissimoMarketplace and continue to develop cloud-based industrial
safety software and business models.

Potential savings
into the millions ofEuro for a typicalinstallation.
The realisationof FLACS-Cloud,creating revenues for
Gexcon.
Computational
speedup, up to afactor of 10, using
HPC over traditional
resources.
Improved placementof detectors, therefore
improving safety.

15

EXPERIMENT #703
HIGHLIGHTS
Industry Sector: 		
Automotive

Advanced, cloud-based HPC
simulation in the foundry businessCountry: Italy
Software used:
Optimus, ITACA andelasticLM

THE COMPANIESProService s.r.l. is an SME based in Italy. Founded in 2002, it
provides machines, tools and consultancy services for the metal
casting industry, focusing on iron foundries. Noesis Solutions is
a Belgian system integrator and independent software vendor.
Its research areas include integrated simulation frameworks,
large-scale optimization and high-performance computing.
Fraunhofer SCAI is the Institute for Algorithms and Scientific
Computing of the Fraunhofer Society, based in Germany.

THE SOLUTIONEnd User

HPC Expert

ISV and Domain expert

HPC Provider

www.proservicetech.it

www.noesissolutions.com

www.scai.fraunhofer.de

www.hlrs.de

Noesis and ProService collaborated to develop a new adaptive process for controlling theliquid-iron stage of the foundry-casting process, based on Noesis’ Optimus software and
ProService ITACA technologies.
The two companies worked together to create a model of the process based on historicalfoundry data, and provided the required expertise to deploy the solution on a Cloud-based
HPC platform. Thermal analysis software is used to generate production data, which is sent
to the Fortissimo Cloud-based HPC infrastructure. The correction model is updated by the
HPC resources based on the production data, and then returned to the foundry system, where
the correction is calculated and applied.

THE CHALLENGE
The goal of this experiment was to reduce the scrap rate of the foundry process. A service
was needed which could predict the behaviour of the current batch of metal to reduce theamount of waste. If it were possible to adjust the process in real time, the foundry could lower
energy consumption and production costs. Using historical data from previous production
runs was seen as the key to this problem, but this entails data analytics requiring computing
resources far in excess of those available to foundries or consultants like ProService.

16

BUSINESS IMPACT

BENEFITSFor ProService, the tools developed in the experiment mean it
can realistically expect to reduce the scrap rate of a foundry
customer from a current rate of around 3% to 2.5%. For asmall foundry, this translates to a saving of €50,000 per year –with the number growing to €500,000 for the largest facilities.
The ability to deliver this kind of saving to a customer puts
ProService at a significant advantage over its competitors.
The experiment partners plan to offer the foundry
optimisation tools as a service, marketed to end-users via
the Fortissimo Marketplace. This is expected to provide anannual revenue of €236,000 for ProService.
The EU is one of the largest steel producers in the world,
second only to China in terms of output. Around 11% ofsteel worldwide comes from EU foundries. With increasing
demand for cast metal products from developing countries,
ensuring the competitiveness of European foundries is key
to tapping into a global market. Europe has more than
1,900 foundries. If just 10% of them were to use this system,with each saving the minimum potential of €50,000, thiswould mean savings for the sector in excess of €9.5M per
year. The potential of this service is therefore extremely high.

Decrease in foundry
scrap rate by
0.5%, saving up to€500,000 per year.
Increase in revenueof €236,000 per year
for ProService andability to offer service
via the FortissimoMarketplace.
Massive potential
saving for EU foundry
industry.

17

EXPERIMENT #705
HIGHLIGHTS
Industry Sector:
Mechanical Engineering

HPC-based design of non-circular
gears

Country: Italy
Software used:
Noesis Optimus, Maple,
Matlab

THE COMPANIESSTAM is an Italian engineering and manufacturing firm.
Since 2011, it has pioneered the development of NonCircular Gears, which are used in many sectors such as
automation & robotics, defence & security, aerospace,transport, and energy. Noesis solutions is a Belgian
system integrator and independent software vendor.

THE SOLUTIONEnd UserISV

HPC Provider

www.stamtech.com

www.noesissolutions.com

www.arctur.si

The partners developed an HPC-based engineering workflow for NCG design. The workflow,
CloudGear, allows STAM to optimise the design of an NCG in less than 3 minutes, providing
fast feedback concerning potential modifications and improvements. Previously, just thecomputation phase of the workflow would take 25 minutes, not including set-up and resultsdelivery. Due to the near-real-time delivery of results, STAM is able to significant speed up its
internal design process.
Using Noesis’ Optimus software, the design process was automated and the mostcomputationally expensive part of the process sent to an HPC system. CloudGear will also beoffered by Arctur through the Fortissimo Marketplace.

THE CHALLENGE
Non-Circular Gears generate a prescribed motion with great precision, regardless of external
factors. This is a highly desirable feature in advanced transmissions. Designing thesegears is a complex process that requires a significant amount of expertise and expensive,
computationally intensive iterations. In-house computing systems are not powerful enoughto perform these calculations.
A cloud-based engineering workflow would significantly shorten the time required todesign and deliver an NCG. A key element of this is cost-effective access to the necessary
computing power.

18

BUSINESS IMPACT

BENEFITS

Customers of the CloudGear workflow will be able todesign better NCG-based solutions at lower costs. This inturn benefits users of their machinery, plants, prototypes
and other products. Five potential customers for
CloudGear have already been identified.
STAM sells a custom NCG solution for approximately€15,000 each. The CloudGear approach will allow themto sell 8 new solutions in the first year, 10 in the second,and 12 in the third. The reduction in development timeand lower manufacturing costs give STAM a significant
advantage.
Noesis will benefit through an increase in sales of the
Optimus software directly related to the sales of the
CloudGear solution, as CloudGear is built on the Optimus
platform. The Optimus optimization tool is extremely
flexible and can easily capture the simulation needs of
end-users in a number of different industries.

Increase in turnover,rising to 20% after 7
years, for STAM, due
to sales of NCGbased solutions andsoftware.
NCGs can be
designed faster, andwith more advanced
features that would
not be possible tosimulate without
HPC.
Noesis expects a 3%
increase in total sales,
worth a total of €1.6
M over five years.

19

EXPERIMENT #706
HIGHLIGHTS
Industry Sector: 		
Automotive

HPC based high-resolution modellingof magnets

Country: Slovenia
Software used:
ELMER, ParaView,
NetGenTHE COMPANIESMagneti Ljubljana is a Slovenian SME that has produced
permanent metallic and systems magnets for theEuropean market for over 60 years. These have many
uses in a variety of sectors. XLAB is a Slovenian R&D
company with a strong research background in thefields of distributed systems, cloud computing, systemsecurity, information visualization and image processing.

THE SOLUTIONEnd User

HPC Expert

HPC Provider

www.magneti.si

www. xlab.si

www.arctur.si

To tackle the problem of pressing tool optimization, XLAB developed a set of software
services based on open-source solutions. XLAB built a computer model of the pressing
tool and its behaviour during the compaction process. This model is highly configurable, so
Magneti can reuse it for other applications.
The optimization service runs as a web application, which provides an easy-to-use interface.
The application connects to Arctur’s HPC system and submits an HPC job according toconfiguration and input parameters from the end user. This means that even inexperienced
users are able to design and run experiments using HPC resources, avoiding the need forcostly training. Magneti only needs to pay for the computing resources it uses, providing thecompany with a cost-effective solution.

THE CHALLENGE
Magneti produces its magnets through a process called compaction, which uses a hydraulicpress to apply pressure to magnetic powders until they solidify. The hydraulic press is madeup of several very expensive parts which regularly wear out and must be replaced. The
pressing tool needed to be optimized, so it could be used for longer and with lower material
costs, but doing this requires the ability to automatically detect yielding of the tool under agiven pressure. This requires many iterations of computer simulation and post-processing,which exceeds in-house capabililties.

20

BUSINESS IMPACT

BENEFITS

The partners in this experiment have derived a number ofbenefits from their involvement in the Fortissimo project.
For Magneti, there are several benefits. Due to the
optimized geometric properties of the pressing tool, thequantity of excess material in an existing tool was reduced
by around 32%, reducing material costs. This has reduced
the cost of making the pressing tool by 27%, which
represents an annual saving of €87k. The pressing tool isalso of a higher quality, containing narrower coils which
consume less power. Assuming Magneti replaces all of
their pressing tools with those designed by the HPC tool,
this will save another €16.2k annually.
XLAB has broadened its software development expertiseto the field of magnet production, and gained knowledge
about developing complex software with the help of opensource tools. The existing software developed for Magneti
can be extended and modified to potential new customers
coming from the same or similar industries.
Arctur has increased its reputation in the researchcommunity, potentially allowing it to attract newcustomers from the magnet production industry.

Design of a betterpressing tool thatsaves money, does
not need to be
replaced as often, anduses less energy.
Savings of over
€100,000 per year for
Magneti and ability tocreate new services
based on improvedpressing tool.
Magneti and
XLAB both gained
experience insimulation.

21

EXPERIMENT #707
HIGHLIGHTS
Industry Sector: 		
Automotive

Cloud-based-HPC optimisation of
manufacturing processes

Country: Slovenia
Software used:
TensorFlow

THE COMPANIESEMO is a Slovenian SME specialising in the production oftools and dies for stamping, particularly sheet metal, in
the automobile and aerospace industries. EMO utilises
laser metal deposition (LMD) technology. AIMEN isa Spanish not-for-profit organization with expertisein laser technologies, manufacturing processes andthe development of monitoring systems for industrial
applications.

THE SOLUTIONEnd User

Domain Expert

HPC Provider and Expert

www.emo-orodjarna.com

www.aimen.es

www.cesga.es

EMO currently uses LMD. As part of this process, EMO needs to gather and analysesignificant amounts of data. A more efficient workflow would enable it to complete more
projects without extra investment. A new system has been developed in this experiment that
exploits recent advances in AI for image analysis and in data acquisition from images of theprocess.
The new technology, called CyPLAM, is a novel approach to the online monitoring of LMD.
It uses deep-learning principles, working on the Fortissimo infrastructure, to enable online
and real-time quality control and monitoring of key features such as dilution and clad height.
CyPLAM has been validated by testing on a repair application using LMD.

THE CHALLENGELMD is an additive manufacturing technology that enables the generic 3D printing of large
metal parts. Additive manufacturing is a rapidly growing sector, as it allows for complex
components to be produced with short lead times. However, the lack of sufficent control
remains a barrier, as it can result in unnecessary reworking, waste and an increase in 3D
printing times. This reduces both profits and efficiency.
This experiment aimed to overcome the current deficiencies in online monitoring and controlof laser processing, so that EMO can realise the full benefits of additive manufacturing andcreate better quality products.

22

BUSINESS IMPACT

BENEFITSCyPLAM addresses the quality issues of LMD-createdparts, putting EMO at an advantage as they are first to use
the technology. Future CyPLAM users can expect to cut
production times by over 30%, as well as producing a higherquality product needing less reworking. Overall, end users
can expect a 20% saving in operational costs and a 30%
reduction in lead-time, compared to traditional approaches.
AIMEN will use CyPLAM technology to support its recently
launched CLAMIR system, a commercial process control
system for Laser Additive Manufacturing.
The experience and knowledge acquired during thisexperiment have allowed CESGA to obtain new projects
and contracts within the industry. They have also created a
training course on Machine Learning.
3D printing and other additive manufacturing technologies have
had a major impact on the European manufacturing industry,allowing fast and flexible prototyping and part creation. This
industry is home to many SMEs due to the comparatively
low cost of entry, and is growing fast. The worldwide 3D
manufacturing industry is growing at a rate of 25% per year,
and is expected to be worth 6.5 billion USD in 2019.

Using HPC, EMO can
reduce operationalcosts by 20% andsave over 2,000
machine hours per
year.
Users of CyPLAM canstay competitive in
the global Additive
Manufacturingmarket.
As a result of theexpertise gainedin this experiment
CESGA is offeringa new Machine
Learning service(SaaS) based on
TensorFlow.

23

EXPERIMENT #708
HIGHLIGHTS
Industry Sector:
Automotive

Cloud-based HPC processing forknowledge generation in camshaft
manufacture

Country: Spain
Software used:
M3

THE COMPANIESEPC Group Europe is headquartered in Spain. It specialises
in the manufacture of large camshafts (over 2 meters long)for use in the naval industry, agriculture, military, generators,
and other sectors.TRIMEK is a Spanish SME founded in 1993.
TRIMEK is one of the main manufacturers of metrologicalsystems and solutions worldwide, and is the 4th worldwide
provider and the leading company in the Basque Country andSpanish markets of Coordinate Measuring Machines (CMM).

THE SOLUTIONEnd UserISV

HPC Expert

www.engpwr.com

www.trimek.com

www.cesga.es

TRIMEK developed a metrological module of its M3 software, which enables the use of
big data resources for data analysis. The new module is able to analyse scanning andmeasurement data and compare parts much faster than before by using cloud-based HPC.
The production process is therefore more time-efficient. The time savings enables moreof the produced parts to be checked in the same amount of time, increasing the overall
production quality.
Reducing the processing time for data analysis allows a higher knowledge and control of thequality of the production process and of its needs, such as maintenance requirements. By
using this system, the end-user receives a higher-quality product, saving time and money,
leading to benefits for their own client.

THE CHALLENGE
EPC manufactures more than half a million camshafts every year. The company needs
to ensure that it produces high-quality parts. Monitoring of the manufacturing process
generates a massive amount of data which could be used as a basis for machine learning
to improve the production process. However, current software solutions are not able to fully
process the data fast enough, so the potential knowledge that may be generated from itcannot be exploited.
In order to function alongside a busy production line, the solution requires significant
computational power, together with the application of novel machine learning technologies.

24

BUSINESS IMPACT

BENEFITSTRIMEK, as service expert, developed a new softwaremodule for statistical analysis. Due to the optimized dataprocessing software developed in this project, TRIMEK
expects an increase of 20% in new licences sales.
EPC has tested and used the new M3 capacities within
their production site, proving its ability to improve
production capacity and speed. In a short time, theexpected benefits to the internal production process will
reduce the number of defective parts to almost zero,
resulting in a cost reduction of €1.5M over the next five
years.
CESGA will exploit the experiment results in its big data
platform, which has been analysed and improved tofulfil the requirements of its commercial customers. As
initial step, CESGA has created a white paper to show thecapabilities of the infrastructure to use as marketing tool
to attract other companies to use it. CESGA expects to beable to increase its SME projects and services in the next
years to reach the strategic indicators for 2020.

20% increase inturnover over five
years for TRIMEK.
EPC can save €1.5M
over five years using
the new solution.
The number ofdefective parts is
reduced to almost
zero.

25

EXPERIMENT #709
HIGHLIGHTS
Industry Sector:
Construction

Cloud-based simulation of box
framed timber beams

Country: Spain
Software used:
ANSYS Mechanical

THE COMPANIESMaderas Besteiro is a Spanish SME that specializes
in timber solutions for structural applications, suchas house-building. It has recently taken an interest
in offering a new product line of box framed timber
beams made from Eucalyptus globulus. USC-PEMADE
is the Structural Timber Engineering Department of the
University of Santiago de Compostela.

THE SOLUTIONEnd User

Domain Expert

HPC Provider

www.mbesteiro.com

www.pemade.com

www.gompute.com

A virtual engineering workflow was designed and validated. The workflow combines thedesign, calculation and virtual validation stages of the process, through access to a Cloudbased HPC platform provided by Fortissimo. Using this solution has allowed Madera Besteiro
to reduce their development costs and design times. A pay-per-use HPC model significantly
reduces the computational costs compared to using in-house resources, and results in abetter, more refined end product. The company can now optimise Eucalyptus-based solutions
at minimum 19% faster than before the experiment. This will allow them to offer a better
product at a lower cost than their competitors.

THE CHALLENGE
Eucalyptus is ideal for structural purposes because of its high quality and resistance. Using
this wood can allow construction companies to build homes faster, with less waste and lessenergy, in line with European Union housing guidelines.
Designing and testing a new structural product is an extremely costly process. As an SME,
Maderas Besteiro faces a challenge to develop new products due to its small number of staff
and lack of sufficient financial resources. A cost-effective computer simulation process would
help to solve this problem.

26

BUSINESS IMPACT

BENEFITS

Thanks to the virtual design process offered by
the Fortissimo Marketplace, Maderas Besteiro hassignificantly reduced their cost per m², when comparing
the new box framed timber beam with the traditionalframing system. Using eucalyptus instead of otherhardwoods, their turnover is increased €40k per year.
More importantly, Maderas Besteiro is now able to easily
optimize new designs, meaning that it has a competitive
advantage in its industry.
From now on, PEMADE will be able to simulate more
complex models than before, including completeengineering structures. Moreover, the ability to simulate
hardwood species such as eucalyptus will make it theleading academic group in Spain in this field.
End users of this workflow can reduce their computing
costs by up to 81%. From a business perspective, it has
an enormous potential as the timber industry has over
400,000 active companies. Gompute is now ready to offer
a complete solution in the Fortissimo Marketplace forcustomers who need to simulate timber structures in a
fast, easy and affordable way.

Maderas Besteiro
can improve its
overall productivity
by 23%, thanks tooptimisation of justone of its products.
Increase in turnoverof €40,000 per
year and ability toeasily optimise new
designs.
PEMADE havegained the ability
to simulate wholecomplex structures,as opposed to theirprevious capabilities.

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EXPERIMENT #710
HIGHLIGHTS
Industry Sector: 		
Aeronautics

Near Real-time Analysis of Airframe
Certification Test Data

Country: Netherlands
Software used:
Pivotal

THE COMPANIESColosso is a Dutch SME specialized in the design,
analysis and physical testing of high-tech materials andstructures, such as those used in the aerospace industry.
Within this context, the key focus of Colosso is on the
improvement of its processes and products. KE-Works
is a Dutch software company. It develops KE-chain, amodelling platform for engineering applications.
End User and Domain expert

THE SOLUTION

ISV

HPC Provider and Expert

www.ke-works.com

www.gompute.com

One of the ways of reducing the cost and lead-time of the material qualification process is toimprove the predictive capability of material models. Improved models lead to a reduction of
the amount of testing required to achieve an reduction in the overall weight of the airframe.
The approach taken in this experiment was to use KE-chain, together with Colosso’s data
analysis and storage framework to calibrate a new algorithm to model materials based ondata from fatigue tests. An HPC environment provided by Gompute was used to provide
on-demand computing resources. This resulted in an improved ability to predict crack
propagation in airframe components and a reduction in the required amount of fatigue
testing.

THE CHALLENGE
The development of aircraft for civil aviation is driven largely by the economics of thematerials constituting the airframe. Improvements in strength and durability can reduce
aircraft weight and allow regulators to increase the inspection intervals.
There is a continuous demand for better materials and a greater understanding of how thesematerials perform in aircraft components. However, introducing a new structural material
for an airframe is costly and takes several years, so there is a significant need for better
certification processes.

28

BUSINESS IMPACT

BENEFITS

The results of this experiment directly contribute to thefurther development of a Colosso’s advanced physicaland virtual test data monitoring and analysis tool (Pivotal).
KE-works will integrate the developed features andinfrastructure deployment options in the offerings of KEchain.
Using HPC will enable (near) real-time data processing andevaluation. A cloud-based, pay-per-use HPC system meansthat using Pivotal and KE-chain is much more cost-effective
than using in-house resources, making these offerings
more competitive.
The experiment, supported by the cloud infrastructure
provided by Gompute, strengthened the competitive
position of both KE-works and Colosso. Because of theincreased potential and capabilities of KE-chain and Pivotal,
an increase in yearly revenue of €50-100,000 is predicted.

Improvements tothe material modelfor testing airframecomponents, which
will allow bettercomponents to be
manufactured.
Development of
a new, promising
software product,
Pivotal, which will beoffered together with
KE-chain.
Increase in revenueof up to €100,000 per
year.

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EXPERIMENT #713
HIGHLIGHTS
Industry Sector:
Mechanical Engineering

Cloud-based-HPC simulation ofrailway infrastructure forhigh-speed trains

Country: Italy
Software used:
Siemens NX

THE COMPANIES
Alstom Ferroviaria S.p.A. is the Italian branch of
Alstom Transport, a multinational leader in the railway
transportation sector. Alstom Transport has a presencein over 60 countries and employs over 28,000 people.
A promoter of sustainable mobility, Alstom Transport
develops and markets the most complete range ofequipment and services in the railway sector.

THE SOLUTIONEnd User

Application Expert

HPC Provider and Expert

www.alstom.com

www.hypertecs.it

www.hpc.cineca.it

This experiment focused on predicting the effects of failures in different components of theturnout (or set of points), one of the basic part of railways infrastructure, with high accuracy.
HPC was necessary as the turnout is a complex and large-sized system, which became evenclearer during the course of the experiment. The dynamic interactions between the basic
components of the system were studied by taking into account the dynamic load due tothe transit of high-speed trains and the failure modes of the turnout. Hypertec Solutions, an
Italian SME, was responsible for the development of the model, adapted by CINECA into theFortissimo cloud environment.

THE CHALLENGE
Alstom is investing huge effort in creating new services for the railway industry and othertransportation fields. One of the main areas of investment currently is the development of adiagnostic service to automatically schedule maintenance intervals.
A diagnostic service would need to: understand how parts degrade and determine which
would need to be serviced at each interval; automatically plan availability of spare parts or
consumables; and quickly report to engineers what needs to be done in order to service thetrain and the network, as efficiently as possible.

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BUSINESS IMPACT

BENEFITS

The major benefits reported by the partners are:
For Alstom, replacing the system based on fieldmeasurements with an effective diagnostic monitoring
based on simulation has resulted in up to a 50% decreasein time-to-results (from between 16 & 22 months to 8
months), with a corresponding cost saving of between€50k and €70k per application. In the best case scenario,
this will result in a saving of €280k per year.
For Hypertec, the experiment allowed it to increase its
engineers’ skills, enabling new services for Hypertec’s
industrial customers in many areas of CAE Simulation.
It is estimated that, as a consequence, HPC-related
revenue will increase 87% in 2017 to €45k. By 2020, this is
expected to reach €100k per year.

50% decrease in timerequired to create
a new diagnostic
system for a railway
component.
Savings up to €280k
per year for Alstom,
based on optimisingfour applications peryear.
A predictive service
developed which
will more accurately
monitor the railway
network and schedule
service interventions
when necessary.

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EXPERIMENT #714
HIGHLIGHTS
Industry Sector: 		
Automotive

Predictive diagnosis services forthe automotive industry

Country: Italy
Software used:
R, R Shiny

THE COMPANIESTEXA, an Italian SME founded in 1992, designs, produces
and sells diagnostic instruments for cars, motor bikes,
and other vehicles. This allows for services such as
real-time monitoring of fleet vehicles. T2I is an Italian
research organisation that supports companies throughthe design, development and testing of new products
and services.

THE SOLUTIONEnd User

Application Expert

HPC Provider and DA Expert

www.texa.com

www.t2i.it

www.hpc.cineca.it

During the experiments, four Data Analytics prototype services were defined. These are based
information gathered from on TEXA’s On-Board Diagnostics (OBD) systems. These services
cover areas that may affect the reliability, condition, or service needs of a vehicle - such as
how it is driven, failure patterns, and overall health of the vehicle.
A Cloud HPC-powered workflow was developed. This was designed to easily integrate into
TEXA’s existing automotive Data Analytics services. A service architecture has been definedthat connects the existing TEXA infrastructure, equipped to collect data from installed blackboxes, to an HPC Cloud provider.

THE CHALLENGE
Vehicle manufacturers generally have limited knowledge of a vehicle’s life once it leaves them.
A service that can predict failures, mechanical problems or damage at the component level,
and offer detailed information on these components, would be extremely valuable, saving
manufacturers and fleet managers time and money. This service would gather and analyse
data from TEXA’s sensors, which could be used to redesign parts and modify maintenanceschedules. This type of analysis requires significant computing power.

BUSINESS IMPACT

BENEFITSFor TEXA, the Net Present Value of these new services is
estimated to reach an overall value of €1.2 M over the next
3 years. The ability to use an HPC-enabled workflow toanalyse data from their diagnostics systems will enable
better oversight of fleet vehicles and predict failures intime for these to be addressed quickly.
T2I will apply the principles developed here to offer
HPC for predictive maintenance in other similar fields(mainly highly “sensorized” products in sectors like home
appliances, smart buildings, and energy). T2I estimates a
5% increase in commercial revenues from related services,in years 2018 – 2020, worth up to €105k.

Development of aservice using TEXA’s‘black boxes’, which
can monitor andpredict failures in fleet
vehicles. This hasvalue for both TEXA
and its customers.
New services have an
overall value of €1.2
M over three years for
TEXA.
T2I increase revenue
by 5% per year, worth
up to €105k overthree years.

32

33

Map of 2nd phase Success Stories andCore Partners

Projects at a Glance
PROJECT NAME Fortissimo - Factories of the Future Resources, Technology,
Infrastructure and Services for Simulation and Modelling

DURATION 1st phase: July 1st 2013 - December 31th 2016

2nd phase: November 1st 2015 - October 31st 2018

TOTAL BUDGET 1st phase: 21.7 M€

2nd phase: 11.1 M€

EU CONTRIBUTION 1st phase: 16.0 M€

2nd phase: 10.0 M€

CONTRACT NUMBER 1st phase: 609029 under the 7th Framework Programme

2nd phase: 680481 under the H2020 Framework Programme

NO OF PARTNERS 1st phase: 122 in total (14 Core Partners and 108 Partners inExperiments)
2nd phase: 38 in total (12 core Partners and currently 26
Partners involved in Experiments)

CORE PARTNERS 1st phase: The University of Edinburgh (EPCC), Arctur, Bull,

CESGA, CINECA, GENCI, Gompute, University of Stuttgart(HLRS), INRIA, Intel, Scapos, Sicos BW, SURFsara and Xlab.
2nd phase: The University of Edinburgh (EPCC), Arctur, Atos,CESGA, CINECA, Gompute, University of Stuttgart (HLRS),Intel, Scapos, Sicos BW, SURFsara and Xlab.

NO OF EXPERIMENTS Both phases comprise in total 92 experiments, of which 67

have already finished and 25 are currently running. The firstphase included 53 experiments in total, 33 of which wereadded as the result of two open calls. The second phase(Fortissimo 2) includes 39 experiments, 10 of which have been
added through the first open call from early 2016 and 15 havebeen added through the second open call from early 2017.

Terminology Open Call: Is a call for proposals made by the Fortissimo

Countries of Core Partners
Countries of Experiment Partners
34

project for new experiments to add to the current portfolio.
The call is aimed at involving additional end-user partners
and their business relevant experiments.
Experiment: A end-user-relevant case study demonstrating
the use of Cloud-based HPC and the benefits it brings tothe value chain from the end-user to the HPC-infrastructure
provider.
Success Story: Is a resumé of an experiment that has been
conducted within the Fortissimo project. This resumé focuseson the business benefits resulting from the experiment.

35

ICT Innovation for Manufacturing SMEs
www.i4ms.eu
Seventh Framework Programmewww.cordis.europa.eu/fp7

Horizon 2020
www.ec.europa.eu/programmes/horizon2020/

European Commissionwww.ec.europa.eu
The research leading to these results has received funding from the European
Union Seventh Framework Programme under grant agreement No 609029
and from the European European Union’s Horizon 2020 research andinnovation programme under grant agreement No 680481.
This publication does not represent the opinion of the EC and the EC is not
responsible for any use that might be made of information appearing herein.
For further information, please visit:www.fortissimo-project.eu

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