IN THIS ISSUE

MONSOON SOLUTIONP2

MONSOON PUBLICATIONSP4

Newsletter 2019, Issue 6

The consortium also released severalacademic publications all tied to thedeveloped tools and related resultsand gains, based on the study cases.

Reaching the last month of the Project,it was organized the Final Workshop inTurin - Italy, with the support of 3other SPIRE projects. The eventcounted with the attendance of 64participants, sharing their feedbackand perspectives of the presentedtools.

It were 3 challenging years, learningand facing new opportunities,culminating in a very rewarding job -the MONSOON Solution.

Upon reaching the end of thischallenging project, we can only thankyou for having followed us and forremaining connected to us in someway. It was a pleasure to keep youaboard with us and we hope to see youagain. Who knows in a MONSOONversion 2.0.

Farewell dear reader!

Dear reader,Along this 3 years we’ve been sharing withyou our developments and news related tothe MONSOON project and we thank youfor having accompanied us for so long

These 6 months a lot of developments andrefinements were preformed to reach thegoals of the Project – the MONSOONFRAMEWORK SOLUTION.

During this last period the team facedseveral challenges to adjust and refine thetools in order to achieve a stable platformfor being used on an industrialenvironment. The consortium wassupported by the project Stakeholders -the ESG Group, that helped to align thedeveloped features to the market needs.Their feedback was very important tostablish the missing improvements, leadingto significant gains on the process'sefficiency and ecologic footprint impacts, asone of the targets of the project - thereduction of the Green House Gasesemissions, CO2.

Also during this period the consortiumdesigned the MONSOON FRAMEWORKcomposed by 5 main bundles, where all thefeatures and services that make up theMONSOON solution are based - describedin detail in this newsletter.

Marco Dias [GLN]Project Dissemination Manager

… Farewell MONSOON!

MONSOON FINAL

WORKSHOPP3

Newsletter

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MONSOON SOLUTION

The MONSOON solution it is a package ofseveral services’ end-users oriented, that aresupported by 5 main bundles, depending onend-users demands and it has specificrequirements for each scenario / application.The solution is not a standard/closed packageand it can work as add-on customizedassociated to the real needs and the requiredfunctionalities: this solution is something thatconnects the end-user to root causes andbased on a continuous involvement in thepersonalization of the tool, it will allow toreach long successful results, and significantgains in a short-medium term.

The MONSOON platform helps the industrialsto have a big data approach with a minimalcost, lowering the financial cost and humanimplication associated.

MONSOON FRAMEWORK

Datalab Platform SAASThe Datalab Platform is the tool for storing(Big Data Storage and Analytics Platform(BDSAP)) and collaboratively analyzing thedata coming from the shop floor and servesas a development environment for thepredictive functions that can be deployedseamlessly into the Runtime Container.

Runtime ContainerThe MONSOON Runtime Containercomponent is very similar to the Datalabplatform except that it doesn’t contain theData Scientists tools but offers a powerfulPredictive Function Manager which managesthe life-cycle of dockerized predictivefunctions ((un)deployment, scheduling, etc.)

System Integration ServiceThe MONSOON platform can combine theIntegration of new components (newpredictive functions, or new connectors),based on the need specification of theapplication to be used, and deliver solidmethodology and tools to support thecontinuous integration.

System Integration ServiceThe MONSOON platform can combine theIntegration of new components (newpredictive functions or new connectors),based on the need specification of theapplication to be used, and deliver solidmethodology and tools to support thecontinuous integration.

It follows different types of services in a Dockerbased infrastructure: the industrial Plant dataare collected using specific connectors andingested into the MONSOON Platform (Datalaband Runtime Container) by a NiFi data flow anda KairosDB databased and the automaticdeployment of the platforms (Datalab andRuntime Container) is based on Ansible andDocker Swarm.

Data Analytics ServiceThe Data Analytics Services are key services thatcan be proposed to end-users. The aim of thoseservices is to exploit the MONSOON DataLabplatform’s capabilities to collect, store and treatlarge volumes of data from several sources, aswell as the possibilities to easily deployfunctionalities in the plants using MONSOON’sRuntime Container.

The Data Analytics Services consist in thedevelopment of specific functions, based ondata science and artificial intelligence tools, forimproving the performances of the plants. Suchfunctions in the industrial domain can help forinstance to anticipate equipment malfunction,to improve an industrial process by avoiding itsdeviations, or to better understand root causesof abnormal quality.

Life Cycle Assessment ServiceLife Cycle Assessment (LCA) is adopted in theMONSOON solution as backgroundmethodology for the life-cycle-managementplugin. LCA plays the role of the environmentalsustainability assessor, ensuring a cross levelapproach to support a quantitative evaluation ofthe environmental impact of the investigatedsystem. The main goal is to provide informationabout the environmental footprint of theinvestigated industrial process and the results ofthe LCA service are sent to a customizeddashboard, where environmental effect ofprocess optimization can be visualized by plantmanagers and HSE experts.

Newsletter

On 20th of September, the MONSOONconsortium organized his final workshop.With the support of 3 other SPIRE projects– FUDIPO, COPRO and COCOP, a fullagenda entitled to the “DigitizedOperations for Sustainable ProcessIndustries – Pathway Towards Industry 4.0”was performed, along with a participationof 64 experts and data-scientists fromdifferent industries segments.

The Workshop was designed in aperspective of sharing the results ofMONSOON project and interact with theother similar projects, highlighting thematching gains and profits to the industriesof the future.

Despite the continuous evolution of thetechnology, part of the Industries still workunder conventional methodologiesunknowing the potentialities of the toolsavailable on the market. In fact, their majorconcerns is to subsists in a very competitiveworld market, avoiding unnecessary cost,which justifies their retraction to newinvestments on Industry 4.0 tools. In thisperspective, MONSOON project offers anew way of seeing production, through thepredictive culture. The developedMONSOON solution interacts with installedworking flow (from a industrialenvironment) and creates the bridgesbetween methods and processimprovements, offering significant gains inshort-medium-term.

During the Final Workshop, the consortiumteam presented the solution functionalitiessupported by reliable results, based on thetwo industrial domains studied during theproject – Aluminium and Plastics. Theseresults were compared to the approachesinvestigated and developed in the otherSPIRE projects, such as the “ICTarchitecture for real-time plant operations,predictive control function developmentand life-cycle assessment”,“Communication architecture for plantwide optimization”, “Advanced control ofdigesters with “machine learning system”and “Rapid integration of real time modelbased applications into heterogeneous ITsystem environments”.

MONSOON FINAL WORKSHOP

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PROJECTMEETINGS

The event ended with a round table entitleto the “Full digitalization of processoperations - chances and challenges”,where the audience shared their visionabout the values of the presented toolsand potential enrichments to the ProcessIndustries.

With this event, the MONSOON consortiumthus ends its project, thanking allstakeholders for the support and positivefeedback that has been shared over thesethree years.

NewsletterMONSOON PUBLICATIONS

P4

Optimizing industrial processes through MONSOON

[JIMENEZ, Jose Antonio][read more]

Forecasting faults of industrial equipment using machine and deep learning classifiers

[KOLOKAS Nikolaos, VAFEIADIS, Thanasis, IOANNIDIS, Dimosthenis & TZOVARAS, Dimitrios]

[read more]

Anomaly detection in aluminum production with unsupervised machine learning classifiers [KOLOKAS Nikolaos, VAFEIADIS, Thanasis, IOANNIDIS,

Dimosthenis & TZOVARAS, Dimitrios][read more]

Forecasting bath and metal height features in electrolysis process

[PASIAS, Achilleas, VAFEIADIS, Thanasis, IOANNIDIS, Dimosthenis & TZOVARAS, Dimitrios]

[read more]

Cross-Sectorial Semantic Model for Support of Data Analytics in Process Industries

[SARNOVSKY, Martin, BEDNAR, Peter & SMATANA, Miroslav ]

[read more]

Anode Quality Monitoring Using Advanced Data Analytics

[AZENNOUD, Bilal, BERNARD Ameline, BONNIVARD Vincent & PEDROLI Hervé]

[read more]

MONSOONSOCIAL

COMMUNICATION

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