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[Music] can I say afternoon yes one o'clock and welcome ladies and gentlemen to the Siemens booth here at the Hannover Messe 2018 hope everybody is feeling good so far and is ready for a challenge and this is also something new for us this is the first so-called mind sphere open space challenge now I'm pretty sure our developers here and our clients have heard of this before of course otherwise they wouldn't be here now what it was or what it is is basically it was an open invitation to all developers around the world to submit their solutions their ideas to use cases of our clients and the best ideas were invited to present here live in front of you so this is going to be very interesting and I'd like to introduce our first client here he comes from Miki Technic International again Beha and he goes by the name of a christian hula Maya so welcome Christie onto the stage Kristin nice to have you now once again like I said before the challenge is basically it was open for everybody developers were supposed to submit their ideas come up with some great solutions maybe you can introduce your company real briefly what do you do how big are you and what was the challenge what are you looking for welcome first of all to all of you like my name is Cristian what am i I'm CEO and owner of Mt I Germany we are one of the leading manufacturers for mixing equipment for the plastics industry chemical pharmaceutical and food we are a small mid-sized family-owned business in the third generation we have 65 employees in our corporate headquarters in that mall Germany also we have a sales and service location in the United States and we have a licensed partner in Tokyo Japan so basically three global footprints as you would call it this way to serve our clients worldwide we export about 80% of our mixes through our worldwide clients so connectivity and like industry 4.0 is a very big thing for us to help our customers anywhere around the world anytime so what are you actually looking for what was the challenge here well our customers operate mixes so blending equipment problem is whenever a mixer is not operating correctly and the throughput rate or the quality of the compound is not good if you ask a customer what is the problem they normally say we didn't change anything it's all the same nothing was changed the only way to support our customers is to understand exactly what they want to do actually what they did on their raw materials on their blending processes and so on and the problem right now for us is that we cannot analyze the data which is available because the data is either not available or on the other hand side not correctly presented to us so with mine sphere and like our whole Siemens system on our blenders we see a big perspective for the future to go to the next generation and to basically support our customers under the idea of Industry 4.0 and connectivity so you must be at least as excited as we are to see what our startups have come up with right you bet well I wish all the companies good luck to present your ideas to us and we are very nosy to see what you did all right thank you very much so far christen you may take a seat over with the rest of the jury and as you can imagine what a challenge like this will be of course hosted and evaluated by a jury and I'd like to introduce them here real quick ladies and gentlemen is sitting on the seat number one is Dania Conan he is also known as the pitch professor he is an entrepreneur lecturer and presenter with a passion and addiction I can say for startups is that correct that's more than correct call me correct nice to have you with us Daniel conan ladies and gentlemen then also with us here today from next 47 is Vikings Machado nice to have you with us Vikings also a start-up expert and great to have you here with us today Kristian we just heard before then representing Siemens is mr. Zemke Inglis on my staff is Anka and from Siemens mine sphere Stephan stung now you guys know of course what this is all about and what you have to basically have your eyes on just you know the jury will be evaluating considering the following points feasibility of the idea target compliance market impact ingenuity did I forget anything those were four or five points you got them on there of course we'll be taking your notes okay now we're gonna do the following we're gonna call up one team after another each team has 15 minutes in total for presentation okay we're gonna split this up in seven minutes of presentation and eight minutes of questions and answers through the jury to the different teams so I'd like to start off with the first team oh by the way it's not only the jury that has a vote it's also you you are also able to vote for the team you think presented the best idea you hear but also you at home watching now I think we have a there we go we have an Internet address Siemens comm slash vote now is where you can leave your vote and I'll be calling for this after every session so once again we're gonna bring up our first team now with a big round of applause team fast forward let's play the video first I my name is Alex because it and I work as a data scientist and I'm really excited to participate in the Siemens our team 2018 - challenge hey my name is kaya ventilate I was trained as a physicist and work as a machine learning engineer at the moment I'm looking forward to take part in the Siemens IOT challenge 2018 a complex mixing process produces thousands of data points a human has no chance to understand them without the help of the machine and this is where our expertise comes in we create mathematical models which focus on the irregularities in the Siemens mines here is a great tool to collect and store data our job is to make sense of this data will be able to detect anomalies when they occur the operator can then be notified and take action [Music] we hope to leverage our skills and expertise to make the best out of the Siemens r/t backside all right and let's bring them on stage now live here our Alexander pukowski and Cayetana been Zillah nice to have you so great to have you on stage I'm gonna take much of your time you're gonna get right into it and I'll be back afterwards all right let's go for it Industrial mixing is a complex process that depends on multiple parameters thus the result and the efficiency of the mixing process may be influenced by many factors in case something goes wrong it might take a lot of effort in a long time to hunt down the problem however we have new resources at our hand to assess the problem of process monitoring thanks to thanks to Siemens mind sphere we can collect the data store it and process it however you do not get the extra benefit from your data without proper analysis this is where our expertise comes in we propose the following frog flow which we measure machine sensor data at the place where it occurs then we transmit and store the sensor output in the cloud here we apply machine learning algorithms to analyze and process the data finally the result of our analysis is presented in an online dashboard to inform the human expert now let me dive in into the technology that we use so we use structural time series and to detect anomalies and to detect possible structural changes in the data and I'll explain to you briefly what this means so here's some simulated data and the blue band shows you and the normal the normal process and the blue band has been learned through machine learning by the machine it has not been specified by the user and then you have some points which are anomalies which are outside the blue band and the computer is able to detect them automatically and to compute an outlier score as you see on the upper panel the blue one and the computer correctly identifies these outliers and helps to find the anomaly in the process a second point is structural change detection what does it mean structural change well think about a machine which is either breaking or maybe overheating or something goes wrong outside the usual region of operation at this point the data contains information about the structural change but it's not so easy to spot it so our an approach which uses some Bayesian analysis and can compute the score for the structural change at point at the at region where the structural change has happened in the time series and so it helps the human expert detect exactly the point where something bad has happened and in the past so let me summarize our algorithm highlights structural changes and detects outliers by doing so it points the human expert into the right direction to hunt down the cause of the failure or to hunt down the cause of the problem this this empowers the human expert but we think it does not replace him thank you very much for your interest thank you very much for the presentation now I'd like to hand over to the jury open for questions one question from my side were you guys from by the way and we are from Berlin from Berlin all right from Berlin City to Hannover a nice to have you like I said before I'll hand it over to Daniel thank you thanks for the pitch gentlemen first question I would have is what's your current status where are you at in terms of this idea yes yeah so we have we have we have the simulated data and we have tested our method on the simulated data but the next step would be to take real-world data from a real machine and see how well it performs there because this is something that we did not have access to so far ok gentlemen any questions at this point I'll grab the microphone there we go please well first of all thank you very much what I understand is that you mainly focused now on analyzing the data you got generated by the minds fear the thing what we are looking for with Mia because it says mixing information and analytics is that we want to combined in the app additional information so customer names recipe data additional add in as we wrote in our challenge is that on your further mind and you just focused on the analyzing of the data points in the beginning so I would say our main expertise is in analyzing data and developing algorithms but we have in mind that an app would also include further information and then it would be up to understanding the specific needs if that would be presented through an online dashboard for example which would be which you could access through a computer or a tablet but to include this extra information and also to allow things like access rights so that you can have some sort of user management I mean this is all on our mind but again like our main expertise would be to help you to detect failures before they actually lead to a complete outage of the machine or so and that is the extra benefit which we might provide thank you thank you thank you for your presentation and my ass how big is your team - - okay no more in the background or no more people in the background at the moment No okay thank you what's the viewpoint of mine's fee on this baby yeah actually a couple of questions first of all you said you want to support humans by making decisions how about how many data points we really talking here because you have mentioned it would be probably hard to to detect anything what's the amount of data are you dealing in such a solution the so it such a solution and can deal with lots of data produced by by the usual censors let's say every second it doesn't matter so much if it's megabytes or data or even more than 100 megabytes of data because this algorithm is not dependent on the on the size of the data as long as there is at least some useful information it will detect it so data the size of the data is not an issue maybe as long as it's stored somewhere and can get retrieved okay thank you and one other question in terms of mine sphere how do you transfer the or what's your plan to transfer the time series data what type of solution or service for mine sphere are you going to use yeah we were thinking of like that to our knowledge there exists this framework of mind connect which connects the sensor to the cloud and I mean that would be something depending of course on the infrastructure which is present in the at the mixing machine however I guess that working with mine sphere that would be the appropriate way to go forward okay thank you Vikings for my understanding here you guys are quite early stage so basically you have a concept which is you need to deploy with a certain amount of data to see if it really works in reality what are your plans what do you want to do what are the next steps do you want to run a proof of concept do you want to start a company do you want to leave college what what do you guys want to do we finished college already and so the next step is to get real-world data and test this on the concept thus producing a real MVP because what we have here is an MVP in a sense but only with artificial data so from our point of view is not and is not yet sufficient and what have you done there have you talked to companies already to get there and no we haven't but we hope that this gives us the opportunity here at you to start working in this direction okay question for me what's your what's your personal expertise at this point what's your background bit more your background so yeah I'm coming from physics and worked a long time on on sequence data actually from biology and yeah so I have a lot of experience in the in the area of data science and machine learning algorithm also specifically in time series analysis so I work as a data scientist for data analysis at the moment working with some data smoothing the data filtering this is where I come from from also from mathematics and statistics and algorithm development so I'm understanding those of you as scientists would you be willing to make the transition to become entrepreneurs yes yes okay and why is the reason we are here pitching here and last question for me why are you the right ones to make it today because we have this great idea that nobody else I think has tried in this context I want to follow up why is no one tried that idea because you saw such geniuses or visits Ohio because and it's not the usual way to do outlier detection and usually when PayPal or Amazon or dude outlier detection on let's say financial transactions they usually do it in a different way and I can go in the day I think nobody does don't matter now but they usually have a different way of treating this and this one this one's the structural time series method and to my understanding has not been applied to this to this specific problem because it comes from comes from an econometric modeling point of view so you found something it's smarter than what Amazon does and yes Amazon has financial data and transactional data it doesn't have this kind of time series data which is machine generated it doesn't have sensors which are measuring temperature although I think you shouldn't compare I'm liking your humble approach I see this could go on and on but right now our time is up and I like the approach and I think we should give them a big round of applause ladies and gentlemen first presenters here on stage also congratulations and also my respect for going on stage first being first on stage is never easy so once again thank you very much all right let's keep it going with our next team same challenge MTE as our client and now there's no video to them so I'd like to bring them up right away from efficiency systems here is kilo Hefner [Music] [Applause] so Tino welcome to the stage you're gonna get hooked up there and then you're just about ready to go we got it can I help you there there you go now once again if you just happen to join us what are we doing here minds fear open space challenge developers ladies and gentlemen were invited to bring in their ideas their solutions to actual use cases to actual challenges our clients posed to us and this is what we're doing now presenting these to the client sitting in the jury with four other competent gentlemen and we're gonna get right into it so efficiency systems Tito where are you from I am coming from Lake of Constance thank you very much for being here today at the Siemens booth I'm glad I'm happy to present a small shop for now the stage thank you cool yeah ladies and gentlemen thank you very much for coming here when I discovered this challenge I said okay MTI is a typical client of efficiency systems because we already be already digitized your machines you only have to connect them they are still not connected but if you connect them they are digitized so what is our idea MDI has challenges like getting data out of the production of machines in order to run machines more efficient MTA wants to give their customers better machines not only good machines but also an if in product an efficient production reducing waste product a visible make process data visible and in on time and you want to provide weeks of countless emails follow to the determine the case so this is exactly a profile we like so our proposal is say goodbye to all of this say goodbye to floatation said say goodbye to waste and weeks of countless emails how do we do that smart shop floor is a system where you only have to connect and then immediately you get all the production data in self configurable baptists pots online you see all over the world any time what your machines are doing and we don't tell you which data you have to see how this is something you make by your own in the system so it could be possible that today you are looking for such kind of data for such kind of information and tomorrow you're looking for other information smart shop floor is system which is able to collect all this data and provides them in a database for you to make your own dashboard so we are featuring important system information of course we make handling recommendations always available via smartphone the only thing you need in smart shop floor is a browser you don't need any app you don't need any hardware we directly connect to Siemens mind for to the s7 control and then immediately immediately you have your data in a dish spot available you also see immediately if alerts and alarms are rising smart shopfloor informs you Papoose Boosh message that something is wrong so you don't have to have a look anytime on your smartphone you will be informed automatically the only thing you need is a web browser our second proposal is say goodbye to generate charts or manually just do it once do it pay drag-and-drop easy and without any programming so generate your own charts also export data to any further system we don't care what you are doing with this data we store them in a database and you are able to give them to other systems like your peer systems or whatever so how we do this smart shop floor has a connector interface to your machines we only have to connect it once and then we are able to collect this data we have customers with running machines where we collect every five seconds 3000 data variables so we collect this data and in the second step we store them in a database this database you can decide where this database shall be located this can be on in a server environment it can be in your house it can be in customers house we don't care where the database is located and then we give you a free configurable web dashboard where can you have a look on this data we don't care what you want to see when you want it to see and how you wanted to see this is up to you today and also in the future and this is our third proposal we're smart shopfloor always with you okay let's have a look how this runs I go with you now online into the system as soon as the data have came from the network I show this to you here life in a in a example this is an example of a web dashboard where you can see this web web dashboard consists out of widgets so you have a widget catalog where you can say okay you wanna have a bar chart a line chart or let's say a progress chart or you want to have this nice or a widget you select this widget from the from the catalog you connect it directly to the machine and then you have your own dashboard here is an example of the catalog of widgets and these widgets this catalog is growing and growing with the time we are producing every time more and more widgets to that and then you can set up the system without any programming also your clients can set up the system without any programming just give them the access to the system and then your clients are able to do their own where their spot is as well as you can do that here you can see this drag and drop example I go back now I check if I have a network here ok I don't have a network don't mind so this means that the the design of the dashboards is drag and drop you can do this by your own we don't care what you want how to see and when ok alright one more thing one last thing please ok ok ok the next module we are coming up now is his is an answer to the question why your machines are not doing their own maintenance by themself organizing their own maintenance for himself thank you very much ladies and gentlemen Tito Hefner efficiency systems with his proposal and the jury I'm sure has some questions you look like you're gonna go for it Vikings my first one I did not see the word mine sphere anywhere where does it come it comes at the OPC UA interface we are able to connect minds fear does at that level so it must be just connected well first of all thank you very much for the presentation welcome but going and and you from Germany so you know how sensitive the Germans are on cloud-based data if I go to one of my clients with the idea that you say you do not care where the data is stored my pitch is at the end before I even started to sell my customers a piece of equipment the clear communication of MTI is that whatever is presented here today must be based on mine sphere and the security concept of mine sphere that's why we are here at the Siemens mind sphere area so I would be interested about security and like you cannot say that you're gonna collect your data on OPC UA which is a nice system by the way but if you're in the Siemens world and you're in the Profi net or proof you save base and you already have the minds fear connector on board with all the PLC's Siemens offering I don't catch it where you really start there that's very easy Siemens mind sphere will make the whole data collection and storing and we go with our dashboards and into Siemens mincer and show that the widgets in other spots so Siemens mind their minds fear can be the back-end for storing collecting data in the way you like it well if I'm not completely on the wrong picture and I would like to hand over to you - fear is just the communication layer the data is stored in an Amazon Web Services or in a Microsoft Azure and the Siemens mind sphere is not really the storage system at all it's the connector and the security of the idea which I'm sure that all the audience here is very sensitive on our security of the data we are providing and I'm sure you would like to add something to it first first of all - field is leveraging Amazon and Microsoft Azure data center but certainly there's our security our data storage on top of their infrastructure so we using certain services I still don't see I couldn't agree more before you have said how this sweety fits into the minds of your concept because I have not really really seen this in your concept so the OPC you is just which can be used on the field bus protocol but how is the data really now go with what how you get this to the minds for your pack and how it is then actually used in our back-end and how you want to get your dashboards on top of it I I'm missing all these pieces actually okay so the answer is that Siemens Minds here can do the whole level of data collection and pushing them in our database so when I say I don't care what a database is saying it's only a technical questions of course it can be Amazon Cloud it can be a Microsoft cloud it can be an extra clock we have client which says I want my I want to have my server in in my house and this is possible because we do not have technical requirements where the data are thought so we have these three levels the first level is collecting data this is Siemens mines for storing them in a database the database can be in a client-side then we go with web there spots with these nice with these nice pictures to analyze the data so the CMAs idea would be that the bottom layer for all the data collection I can still see you frowning if they are still wondering if this one stand for examine your own local database you need to make all the identification and everything work so this is not it's a little bit besides security concept you mentioned before and so it would really take a lot of efforts actually to convince and then clients to do something like this so one more answer is we have already one machine company in field with the system they are using our technique to collect data from the machine control it's not Simmons miles is another it's another system but as they have this machine control system of course we can also use Siemens mind sphere this is something which is difficult we have to do the connection once and then we have the complete system the complete security provided by Siemens into the system so it's the bottom layer we are talking about I don't know that that impressed at this point but I do have a very different question can you tell us a bit about your company your team yeah my company is one person standing in front of you and the team is a 15 person team which developed the software so we we are running out now the bootstrapping phase we are on the markets it's one and a half years and we will found a GmbH until end of this year or middle of the year we are not really sure in cards and then we will have a 15 15 employee company which is doing support which is doing sales and which supports you worldwide with these issues and what's your background your personal background I am studied informatics in constants many years ago and I was many years ago in field of machine operations with earpiece systems ok any other questions gentlemen thank you welcome thank you very much thank you very much your applause cero Hefner from efficiency systems and once again if you would like to vote also for this proposal for this solution please go to the Siemens comm slash boat now website it is open already you can by the way you can vote for your favorite even if you haven't seen them yet just saying of course it makes more sense to see them all first but hey if you're watching out there and you know your friend your company your boss is standing here right now you can vote from already but let's move on to the next team and they are from Cote strike so let's watch a video first hey my name is Kai and I am one of the founders of cold strike weird call strikes tries to enable the benefits of the digitalization for customers we just found our company this year and currently building on a date technical solution to optimize processes and digital advertisement however most of our know-how lies on automation in manufacturing the three of us gained experience as a automation technician we're so happy to be a part of the my sphere of space challenge and now we want to show you some impressions of our Oberg hi I'm Patrick one of our previous projects was a 3d visualization of an industrial machine using data from a PLC it can be utilized to shard effective components right on your smartphone disraeli maintenance workers can easily find the location of a faulty component this allows a faster replacement of the part and keeps machine downtime to a million hey I have explained our submission to the minds beautiful space challenge 2018 we decided to work on the case of MTI the mixing company because process in transparency is a common problem which we personally faced by working with maintenance freaks our solution to the case includes connecting all people involved in the mixing process to machine data and to one another this includes machine operators from different shifts their superiors floor managers experts and of course people working in quality control if desired all these people can use our app to access the process data of our machines connect to mines view yeah can be set up to notify the right person if process parameter self in shape this prevents undesired alterations to the process in addition our solution will also provide a parameter time machine that historical changes of process parameters can be refuted and if necessary easily diverted to the last thought value ya can also be used and add comments through a process parameter change to explain what the objective of the parameter change was last but not least we also want to provide the ability to few traces of our process variables and to compare them to previous charges or to data from other machines the recorded data could be utilized to generate full plate brought across directly in the might spirit the Broncos then could be found Odin Expedia or Sharples customers and : this way the mixing process becomes fully transparent we think our solutions would make MTI makes us even better [Music] so that was basically an entire explanation already but let's give them on stage ladies and gentlemen with a big round of applause here Benedict Patrick and Caillou so the stage is yours enjoy hello my name is sky and I'm from cold strike together with Benedict and Patrick I won't present you our solution for the MTI mixing Technology case we have a fourth man here it's Philip he's our key account mature but let's start first of all I want to explain you some of our innovative features so usually the focus lies on connecting raw machine data with the cloud but in this way they're useful and now of machine operators or experts is just a wave of just available for a small group of people so this is why we implement social features to our app let's talk about our first feature it's the parameter feed the parameter feed is similar to the Twitter timeline so you have an overview for all changes that have made to the process this is so recent changes are displayed on the top so it is easy to figure out which which change may have break broke the process and the parameter feed is most most of the parameter feed is generated automatically and there's a manual part which is for comments so some of the users can explain why they have made this change I will not explain one of the most important features of our app which is the mixology analytics page here you can compare all machine data and also analyze it but you can also add comments to the data if you know more about what happened at a specific data point for example the machine operator can add a comment what may be the cause of a temperature spike was or how we could solve this problem you can also define thresholds and detailed set points to explain how normal data looks like so everyone can compare the actual later against the current data and yep also recognizes trends for easier assessment of the data another very exciting feature of our minds free app is the parameter time machine where you can basically time travel in your process at the top you have a list of all parameter changes a timeline and if you click on a specific date you can compare the parameter values from before with the current parameter values and the most important point of this is you can also revert the parameter values back to the old value of something broke the mixing process and you now want to go back to the old working value and if you select a specific parameter there's also a line chart which displays the time series data of this parameter but you can also set up different settings per parameter for example you can define thresholds if a parameters changed by maybe 10 to send you can notify an expert or if it's changed by more than 50% you can notify a supervisor guys you don't have to know the email address or telephone number of the supervisor it specified the role and the app has stored somewhere else who the supervisor for the current machine is you can also start what we call a parameter trail where you change the parameter by for example five degrees and the time period after which you can check back on the process if it's still working well so you change the parameter by five degrees and after two weeks process expert gets a notification to check back if the parameter has worked and then he can confirm that the parameter is working well and he also within the app the parameters flagged as working and smart green we also implemented our powerful reporting feature if this feature you can generate reporting templates with which can be filled with your machine process data to a generate detailed report of your mixing process the reports can be trail protocols or protection protocols or can be even a configurated in any way you like report consists out of multiple elements the which can be for example pie line or bar charts or even description text or data tables as another very important feature we implemented the possibility to add that reports can be scheduled to run daily weekly or monthly so you always stay up to date what is going on in your mixing process additionally reports can be shared as PDF with your co-workers now I want to highlight some of our previous work which will help us to realize this dashboard solution we already realized the similar dashboard solution which helps to optimize processing digital advertising it analyzes billions of data points to display or requested KPIs like mine sphere it runs on Amazon Web Services to provide maximum availability and security we also did a little 3d visualization of 3d and physics visualization of a little industrial plant which can be connected to a peer system or even s7 CPUs this were the highlights of our solution and we are happy to provide more information during the QA session all right that was nice thank you very much gentlemen now just watching the jury while they were performing and and presenting when they came to the mixology analytics chart I saw some of you nodding your heads like they thought of something there are they on to something what are your questions please well first of all thank you very much that was very refreshing and you really hit it on the head I could really find our machines exactly in your dashboard as you showed it and I appreciate the efforts because you used our data data set points you use PVC and all the other stuff it gives us a great impression basically what could be behind that app let me please understand the structure of your company you said the beginning it was founded this year is that correct yes where is it based how many people are you who owns it so we are free developer in the company and it is based in the south of Germany and we have a fourth man he is our key Account Manager he managed the whole process and we gather firt developer which more than 10 years experience which I wish support us to to realize these projects well looking at your presentation I can tell that you put a lot of time into it too to basically use the data to show us something which I wants to say one more time was very refreshing what's your personal background on on studying and yes we of us worked three years as automation technicians in our in the industry and so we gained a lot of experience how the process and in the industry works I have a question how did how did you get started in this because you see the industry background with just some a certain point of frustration you reached or after we finished our training we worked for a few months and then we decided to leave the company and chase our own projects okay that's the humble way of putting it and it was also one question you didn't answer how's your company financed who owns the company it's bootstrap so it doesn't have any investors and it's owned by us four evenly okay for loving that gentleman any other questions please I have a question regarding mine sphere what we have seen what you have shown here are this in terms of minds furious is still like mock-ups or is do you have any proof of concepts and bps already realized in mind sphere this is only but the dashboard you have seen is a real product so we did the for front-end but it was an advertising project so it had didn't have the minds free connection but we of course want to lose mine sphere and make this or know JSF which then connects to mine through ap ice and reads the data and visualizes within the front-end and have you already discussed between all three of you how you want to store I mean how you want to deal of the data obviously we talked about recipe data if you already decided what database you might want to use or laptops the technical that you already have identified your technical concept in in more details I think most of the concepts in the case that was specified that there are s7 1500 CPUs in the machines and mine connect nano see pcs which already connect the data to mine sphere and there it's thought as time series data and then we can read it using nodejs from the AP is and for a user system and the comments we also want to use cloud foundries and posh professed SQL component okay thank you any other questions just one one short and again thank you for the presentation to us very good one question should today when you look at the reports basically that's a picture from the past are you already in a situation where you can make some predictions out of the data that are there are you applying concepts which I'll allow you for example just say based on the data which is here I can see a machine breaking in three days for now I think this is not really from the case we read it that this is not a an application that should do predictive maintenance or something only that focuses mainly it was just an example I mean can you Kenny can you run predictions any sort of prediction out of the data you are working on this is something is this something you're planning to eat you have in your platform if it's decided by the customer we of course can integrate this via native AWS services kinases or something like that okay last question for me what's your company's next milestone what's the next thing you're working towards we want to gain customers in the industry and build basically as a service company for industry data and mines view if you gentlemen are happy I'm happy all right thank you thank you for the questions and thank you for the presentation once again our gentlemen from Cote strike by the way if you wish to speak to any of our teams afterwards they are here for you the entire day we have everybody here from Team fast forward who presented first efficiency systems code strike we just had right now and once again go to the online voting sites to vote for your team for the team you think has the best solution once again steam is calm / vote now you can also do this I think we have some QR codes laying out here all you have to do is scan that in and we'll lead you right to the site so let's move on to our next and also last team to present for our client here MTE so we're gonna start it off with the video once again here is team IO hi I'm University with specialization in technology innovation marketing and entrepreneurship I'm representing team IO and participated with Surat war who is also studying management and engineering inheritor hikakin University with specialization in computer-aided mechanical engineering my strengths are database management working collaboratively in a team and being innovative while being a tableau developer I thought of participating in this competition as it gives me with an opportunity to put into practice my learnings and increase my knowledge with the current competitive technologies I believe it is one of the best solutions as it gives managers with an opportunity to view the live data from the machines in a clear and understandable method the visual representation of data can help them easily and quickly detect issues in the process which get which help the organization optimize their productivity and will reduce the delays to determine the cause of a problem as the interactive nature of table dashboards can also help them drill down into the exact issue and my new details of a particular process which will help them overcome the challenge at the earliest possible the dashboard also allows the managers to view the trend of last one month or even more which is customizable and also provides them with an opportunity of predictive analysis thereby giving them an option of predictive maintenance of their mixers and add value to their productivity thank you ok so let's welcome from Team IO Suraj avatar [Music] [Applause] Suraj nice to have you know I bet some of you were surprised that was I guess your to your team member yeah she's my team member and she could not be here today because she's in writing an exam at the university right now what university are you at are WTHR can university nice alright so this is your time make the most of it here's your audience thank you Chris ok let's go to the team you already met Chris - on the video she's studying management and engineering in technology innovation entrepreneurship and marketing and I'm studying the same course with a specialization in computer aided mechanical engineering so we our concept is that we wanted to turn large amount of process data into understandable insightful and interactive kind of a visual communication and for this we use tableau tool so let's go directly how we approach this project so it was a six step process where it involve acquisition of data since the machines are already connected through a decentralized periphery to the mine sphere so we can access the data directly from the mine sphere then the second step is passing the data because once we have the data we need to give it a structure we need to know what kind of data we have and the third which is kind of an important step is filtering the data because we generate data faster than the speed of light today so we need to know which data is of importance to us and which data is not of importance to us and we have to retain the data which gives value and fourth is choosing the mathematical models for representing our data so as to it can communicate itself in a good way first is once we have represented all the data we would like to refine it and rearrange it to make it more interactive leading to the final step so let's go how we started off we started off with a dummy data set that we made created it has some values of talk torque temperature material density and we have connected it through the tableau dashboard to an excel file which can also be connected to any other data force such as SQL or even to the mine sphere if we have an API for that and the connection type here is a live connection so tableau gives us a flexibility that we the data will be refreshed in every 15 minutes by 15 seconds by default but we can bring this up to 3 seconds with the help of other API s-- also we have the option of having extract data in case we do not want to track the real-time data and we want that ok at the end of the day we want the data to present to be present at the dashboard then we can use the extract type ok let's go to the next this is the three these are the three of screens that we have right now it's also working there so you can come to my desk and I can show you how it works the leftmost is the home screen which would I which gives you an option to either go to the dashboard directly and have an overview of the process and the second is just to see the trend line directly if you do not want to see the process so this is how the dashboard looks like right now on the right hand upper corner you have the option of selecting the date for which you want to see the data and on the left side after you have selected the date you get a pie chart which shows how many unique processes happened in that day which are represented here by the mixing IDs and also the number of processes that happened that happened for example we can see that mixing ID happened just only once in a day whereas mixing ID D happened thrice and on the right-hand side for now we haven't have a bar plot a bar graph which is showing the average value of the mix the parameters that we use for different mixing IDs here we use a bar graph because we have mocked up our data and it's not the real data but in case we when we have the real data we can shift from a bar plot to a bar graph to a bar plot where we have the tolerances of data and it can be easily visualized at which data or which parameter is falling outside the tolerance limits and when you come down to the parameters the bottom most part it is showing us the trend of the past one year for the parameter that we over of sorry not for the one year for one month of the parameter that we have selected for example here we select a torque and we can observe that somewhere from Fort April to 29th April there was a slight increase in the torque value for a particular mixer but it dropped suddenly between 4th May so we can figure out what's happening so this is how this is the overview but in case we just want to see it for one mixing ID and not for the whole we can just click on the by pie chart and it shows us the data for that particular mixing ID in that particular day and also for that particular process over the whole month so this is how we also get the individual train and similarly we can do it for any other data so now finally moving to the impact and the scope of this concept it's a single graphical interface so the managers or the shop flow people can visualize everything in a single graphical screen it's highly scalable because and it's got also plug in place so once we have created the framework we just need to have the similar data source and a similar data structure and we can plug it play it into any data source and it also helps us to measure the compliance and traceability of at the Machine level that which machine is going a is not following the tolerance limits also we can relate the machine efficiency with the impact on the finances of the company since we will meet knowing which machine performs when a which machine has good efficiency and the fifth part is more towards the predictive or the preventive maintenance since tableau gives us a flexibility of using our packages directly into the calculated values so we can also go for predictive maintenance since like we saw the trend of the top decline going up and then declining declining then we can also give it a predictive range for the next five days what's going to happen and also in case we want to implement this solution into any mobile app or any other mobile development platform arab development platform its mobile app bootstrap is readily available which can embed all the tableau servers and application into any mobile app thank you all right thank you all so that was Suraj from Team IO garage so the jury I'm pretty sure has has some questions how was it for you yeah all good you feeling good all right so please gentlemen okay thank you look that come right now you know University correct right so are you willing to take this matrix into a company or what you what's your thought on that yeah I mean I can if given an opportunity we can develop this project and it would also give us an experience to get into the Entrepreneurship yeah and and I was unsure did you did you did you run any test cases or was purely dummies yeah I mean this was the the data set was dummy but the application that we made on pub tableau it's working and it's running yeah and once you guess how long would you require how much time would you need until you'd have a version one zero well that depends on the compact complexity of data and what are the requirements if it's exactly the same model that we need then we might just need to change the data source and the data base but in the I'm pretty sure that we would want something more comprehensive and exhaustive so for that it be depending on what are the requirements and yeah rough guess how long a week a month a year okay that's a tough I would say a month to develop yeah with two people yeah with two people okay thank you anyone else Thank You first of all for your nice presentation I was quite impressed to see how you actually structured the entire port including the data interest parsing the data data cleansing et cetera and also very pleased that you're using like tableau which is tightly integrated in in mind sphere however I think for us the solution which is probably really supportive to to a machine operator I think you cannot jump right away in such a data exploration tools or what I was a little bit missing is more so transparency part so that you get an overview and the tableau is as I said it's really more for for taking really into data maybe make some analysis but it's not so what you probably typically do right away so that there should be other stages have you something like this in your mind or is it blend somehow as part of the solution in get I mean we can also develop the similar platform using javascript or node.js which is also very compatible with simens fine sphere but yeah for this particular concept we chose tableau because of ease of using and developing faster and how did you actually get familiar with Siemens mind sphere what type of how was someone helping you or did you just use our developer documentation how did you actually get started with well I read a bit of the developer documentation but apart from that I'm also working with simens as a working student in Aachen at the R&D facility where they are now just recently inaugurated the Siemens - the law so yeah getting to know a lot from around is yeah thank you how about any other questions here from our jury but seemingly there's no other questions then my last question would be for you what what are your next steps going to be will you follow up on this no matter what happens well we can develop something similar to this if we have the requirement for it in case we have the requirement for this product we would definitely go for it okay thank you alright so that concludes our session here and thank you very much thank you once again and let's give all our developers a big round of applause here one time for participating and maybe we can get you guys back on stage because now ladies and gentlemen our jury will take their time about five minutes huh maybe we can have you back in five minutes to evaluate which idea they think is best and once again this is your call also go to Siemens comm slash vote now to vote for the team you think has the best solution for our client here MTA so can we get everybody back on stage here exactly all teams just for a quick round maybe one or two questions I can I have the microphone that'd be fantastic thank you very much so welcome back welcome back [Music] [Applause] so like I said before we're gonna take the time now let's say their jury is gonna take their time to see who is who has in their eyes the best idea how was this for you now to present here you was we've done this before yes I did some presentations before this presentation of course was in a tremendous frame such a booth such a such an environment I have noticed have never seen this before and I thank you very much to that I could be to be here to be today that's I see you to say and I think this is also a chance for a fir for everybody for all developers to present themselves you guys have a nice table over there the entire day also once again for you alright if you're interested in the different applications and the solutions they had just presented please feel free to ask and they'll I think they'll be willing to answer any questions so was this your first try at a at a pitch session it was my first pitch at a trade fair but he used to pitch in other locations the smaller ones so it's a different level of course here I liked it so what was the main reason you actually participated like what was your why was it because the challenge was a something you were very interested in or was it also to be able to present yourself so Y on the one side it was a chance to apply our expertise to a real-world problem and on the other side yeah I never participated in a pitch before and it is great to be here thanks a lot so how about you gentlemen you guys I suppose also first try at least on a stage like this how did you experience it how was it when the jury started asking questions yeah was that a good feeling or wasn't more like I'd like to get off stage now no it was an awesome feeling I feel like Steve Jobs for the first iPhone pitch so yeah it was really cool and we enjoy it so what are you hoping from your presentation here now so we can promote ourselves to show the people what we can and yes so maybe I'll pass the you have a microphone on yeah all right do you know if your your colleague here was her name who's boom which whoo yeah was she watching I don't know actually she would be at the same time giving a presentation yeah at the Uni I'm not very sure if she was watching but I'm sure that she would watch it if she didn't so since when are you in in and where are you actually originally from I'm from India and I'm in Aachen for the past one and a half year I'm doing my Master's there all right and khushboo she just arrived six or seven months back oh wow and you guys started working on this project when when did you guys hear about this project in the first place it's not so long ago right yeah this is also important for our audience to know when did you hear about the project hmm I'm not very sure about which date was it probably it was in February or March so just about a few weeks ago basically you only had a few weeks time how about you how was that was that like a quick shot I mean yes it was really a quick shot I heard 14 days before this fair oh wow from this challenge and I put my data into the entry into the web and then I could present today so this was very very tough time but I hope also a time full of X well good experiences and also once again the chance to present yourselves here I think you won't get a better chance than this right here today so once again if you're watching now please go to SEMA accomplish a vote now to vote for your favorite team I think once again you guys were all fantastic here on stage it takes guts to get on stage to present your idea this is exactly what we've been looking for here all right real solutions to real challenges in front of real clients and you can say what you want but that is not an easy task so we're gonna wait another couple of minutes until our jury gets back in the meantime once again to our people watching now everything you see here is being streamed live by the way so you can also go to the YouTube channel to check out the different presentations right after all challenge will get into another presentation talking about Amazon Web Services and how they work together with mine sphere so we're gonna keep it going here throughout the entire day so once again gentlemen thank you I think a jury will be here in just a couple of moments and maybe we have one or two videos oh that's that's what we need to do now you got it already okay so I'm gonna get this this is the yes exactly so we had an online voting like I said before just a couple of minutes ago my last announcement you were able to vote for your favorite team online I hope some of you in the audience did it and I hope a lot of you at home also and we have the results okay so the winner ladies and gentlemen from the online voting is and this has nothing to do with the jury voting later on just so you know the winner will receive a voucher for the next mine sphere conference which will be taking place in Berlin in September and they will this team winner of the online voting would be going straight to this conference then afterwards so the winner of the online voting is team code strike a petite consequence innovation if it could similar not to op newsmen Nelson cinema Newton David so congratulations these are three vouchers one for you one for you and one for you congratulations to that already so the viewers at home in the audience they liked it now the question is though what did the jury like best and why so Daniel you want to come on stage I do energy results with us thank you first of all I'm loving the way you're saying hi to me can have a bit of an applause yeah I'm loving the energy in the room thank you very much so it was fun it was it was very strong all participants pitched hard pitched a little thank you so much to them from us as jury but at the end it was quite a clear result it was pretty straightforward because there was one team that really took the whole thing a level further okay a level four further that drove it forwards was so much more passion and a lot of love and detail and as a team we strongly believe in we're quite curious to see what's going to happen sure announce the winner yeah I think we want to know who yeah who's gonna take home the prize yes so let me just kind of stand here that no one looks into my cards because by the way now is the right time for me to invest them because evaluation is going to go up in about ten seconds you know what we should do we should we should we should kind of get the right out yeah we should so we need it we need it and the winner cold strike congratulations code strike that's right team coats right come along stand here and maybe we could also have our clients to join us so thank you once again Daniel also for supporting us here once again I think the interesting thing here is to see what's gonna happen next yeah so what is basically the next step now Kristiana well first of all we're gonna let it go for a couple of minutes and then use the stuff what you showed us and then I'm sure that if you are available that we're gonna have a further discussion right here at the booth if there is an opportunity to get to the companies together once again thank you very much for your efforts you put in and for your presentation it was very fantastic and I hope that this is going to be a start for you as well in the big Siemens community and giving your company additional projects in the future so congratulations gentlemen thank you very much also for participating Christian be challenged that was our first open space challenge here we'll be back again tomorrow with another one actually to a challenges will be hosting tomorrow and now we're gonna take a quick break and we'll be back at let me see 2:30 I think right 2:30 with our next presentation talking about Amazon Web Services how this goes together with mine sphere and we'd love to see you again then so thank you for joining us you've been a fantastic audience also at home and have fun here at Siemens thank you guys you [Music]