Digi­ta­li­sa­ti­on is chan­ging the working world. Indus­try 4.0 is on everybody’s lips and many peop­le see the ful­ly-digi­ti­sed com­pa­ny as the future. Yet, when dealing with the chal­len­ges and chan­ces of the fourth indus­tri­al revo­lu­ti­on, “poli­tics and socie­ty have hyped them­sel­ves up with a lot of terms from Indus­try 4.0”. Ulrich Grau­vo­gel is con­vin­ced: “Indus­try and socie­ty are well on the way towards a digi­ti­sed future, but are using a lot of dif­fe­rent means of trans­port and taking unsafe rou­tes to get the­re. Many com­pa­nies have dis­co­ve­r­ed that the beau­ti­ful cyber heli­cop­ter being adver­ti­sed by the IT sys­tem com­pa­nies sim­ply does not want to take off. Back on earth, in the real world, you have to go on foot and your maps are incom­ple­te.”

We spo­ke to the Chief Mar­ke­ting Offi­cer (CMO) of mem­ber com­pa­ny Data Ahead GmbH.

Ques­ti­on:
The flood of data is con­ti­nuous­ly increa­sing. More and more data are being pro­du­ced, inte­gra­ted into busi­ness pro­ces­ses and being uti­li­zed. Mass raw data, too, is expec­ted to be con­stant­ly avail­ab­le for com­pa­nies. To what extent is that fea­si­ble?

Ulrich Grau­vo­gel:
The all-digi­ti­sed com­pa­ny is being dis­cus­sed all the time nowa­days and being pro­mo­ted as a visi­on for the future. But ani­ma­ted pic­tures of machi­nes on tablet com­pu­ters with sta­tus indi­ca­tors or car­ry­ing out repairs using cyber gloves, which lots of ser­vice tech­ni­ci­ans might well be drea­ming of, are not as easy to rea­li­se as some sys­tem com­pa­nies’ adver­ti­sing sug­gests. Poli­tics and socie­ty “have hyped them­sel­ves up” with a lot of Indus­try 4.0 ter­mi­no­lo­gy in the past few mon­ths.

Ques­ti­on:
What do you think rea­li­ty is going to be like com­pa­red with the visi­on?

Ulrich Grau­vo­gel:
Many com­pa­nies that have tried, bey­ond expen­si­ve­ly pro­du­ced pro­to­ty­pes and case stu­dies, to sca­le solu­ti­ons have come down to earth with a bump. After all, the­re is a big dif­fe­rence bet­ween a team of deve­lo­pers vir­tua­li­sing a sin­gle pump or an assem­bly device for an extra­va­gant show or whe­ther the IT and IE team have to put a thousand pumps online in rea­li­ty.

Ques­ti­on:
Whe­re exac­t­ly are the dif­fi­cul­ties with respect to imple­men­ta­ti­on?

Ulrich Grau­vo­gel: 
If we con­ti­nue with this examp­le, access time grows expo­nen­ti­al­ly accord­ing to the amount of instan­ces that are invol­ved in a request and which are dyna­mi­cal­ly con­nec­ted to each other. If, on top of all that, mea­su­rement tech­no­lo­gy is used to try to keep the size of sin­gle sam­ples small, in order to save data volu­me by using all kinds of allo­ca­ti­on tables and dyna­mic rou­ting, then it gets real­ly inte­res­ting. Then, only radi­cal com­pu­ter tech­no­lo­gy and, hope­ful­ly, a sta­ble net­work can help. But that can only be illus­tra­ted eco­no­mi­c­al­ly up to a cer­tain total amount of data.

Ques­ti­on:
What could a rea­listic approach and suc­cess­ful imple­men­ta­ti­on actual­ly look like then?

Ulrich Grau­vo­gel:
Have you ever asked yours­elf how it is pos­si­ble, for you to get seman­ti­cal­ly rea­son­ab­le sug­ges­ti­ons which sup­ple­ment your ent­ry wit­hin split seconds when you are ent­e­ring a search term in the inter­net? We can learn a lot from this with regard to the mass data in pro­duc­tion faci­li­ties: the Inter­net is gro­wing dai­ly, as is the amount of data pro­du­ced during pro­duc­tion. New SaaS pro­duc­ts are being deve­lo­ped in the Inter­net all the time, and new pro­ces­ses are being deve­lo­ped in our fac­to­ries, new faci­li­ties are being instal­led and new pro­duc­ts are being laun­ched as well. Ana­lo­gies are more dis­tinc­tive and solu­ti­ons more obvious than many a tech­no­crat may think.

Full inde­xa­ti­on, ful­ly seman­tic and pro­fes­sio­nal mes­sa­ge bro­ke­ring are some of the key terms behind the archi­tec­tu­re we deve­lo­ped for this pur­po­se. This can con­trol cumu­la­ted data amounts at peta­byte level. If you play by a few of the rules when homo­ge­ni­sing the par­ti­ci­pa­ting data sup­pliers, and, first of all, do wit­hout refor­mat­ting the raw data, they can sur­vi­ve both per­man­ent­ly and resi­li­ent­ly and can also be acces­sed via stan­dar­di­zed web-enab­led inter­faces.

Ques­ti­on:
How is this archi­tec­tu­re accep­ted and imple­men­ted in prac­tice?

Ulrich Grau­vo­gel:
So far, we have instal­led this archi­tec­tu­re suc­cess­ful­ly more than 50 times in the DACH regi­on (Ger­ma­ny, Aus­tria and Switz­er­land). And now some cor­po­ra­ti­ons are begin­ning to inclu­de it as a uni­ver­sal tool in their eco­sys­tems. The pos­si­bi­li­ty of get­ting a spon­ta­ne­ous syn­op­sis of all their raw data gives com­pa­nies a stra­te­gic and eco­no­mic bene­fit. And on top of that, employees feel moti­va­ted rather than frus­tra­ted if they can ana­ly­se their pro­ces­ses them­sel­ves wit­hout having to cope some­whe­re bet­ween their inter­nal IT, pro­prie­ta­ry machi­ne con­trols and sys­tem com­pa­ny con­sul­tants.

Ques­ti­on:
As an IDSA mem­ber, whe­re do you see inter­faces and the advan­ta­ges of Indus­tri­al Data Space?

Ulrich Grau­vo­gel:
The IDSA has unders­tood, in an exem­pla­ry man­ner, how to vir­tual­ly con­nect renow­ned sta­ke­hol­ders and their respec­tive best-in-class com­pe­ten­ci­es to beco­me effec­tive IIOT value chains. We have noti­ced a real dif­fe­rence in com­pa­ri­son to other such bodies. The­re is a desi­re to quick­ly imple­ment real use cases, to think them through to the end and to trans­fer them rapidly into use­ab­le and tru­ly scala­b­le archi­tec­tures. Prac­ti­cal rele­van­ce and expe­ri­ence do not gua­ran­tee suc­cess on their own, but they are necessa­ry pre­re­qui­si­tes. Asi­de from the many theo­re­ti­cal approa­ches con­cer­ning the Indus­tri­al Inter­net of Things (IIOT), suc­cess will come to tho­se who are fast enough to set smart de fac­to stan­dards to pro­vi­de real bene­fits in prac­tice.

Info box Data Ahead GmbH
Over the years, Data Ahead has deve­lo­ped from being a sys­tem com­pa­ny pure­ly for mea­su­rement and test tech­no­lo­gy and data manage­ment to beco­me a spe­cia­list pro­vi­der for indus­tri­al mass data logistics. The 25-strong team does not com­pe­te with sys­tem inte­gra­tors and app­li­ca­ti­on com­pa­nies, but rather pro­vi­des them with spe­ci­fi­cal­ly con­fi­gu­red gate­ways, edge com­pu­ting and high-speed archi­tec­tures.