Home / Blog / DT evolution in Manufacturing – VIII

DT evolution in Manufacturing – VIII

Knowledge has become a crucial assets for companies. Each company has knowledge embedded, in terms of its operation processes and tools supporting operation. This embedded knowledge reach out to acquire the knowledge of its human resources. This knowledge is what makes the company competitive on the market. However, the overall knowledge, indicated as knowledge space in the graphic, is way larger and part of it may be needed to keep the company competitive. Today the issue is how to make sure that the needed knowledge is acquired by the human resources, through training, hiring, consultancy, tomorrow this additional knowledge may be used independently of the resource having it, by interacting directly with the CDT associated to the resource. Image credit: DRI IEEE

 The interest on Cognitive Digital Twins -CDT- is growing and companies are starting to look at that as a tool to effectively manage knowledge assets. As Digital Transformation -DX- is making knowledge a crucial component of business (DX shifts atoms into data but data as such are a commodity with very limited value. The value has to be leveraged through the “understanding of data and their implication in a specific context at a specific time), it becomes ever more important to manage the knowledge assets of a company. 

 A CDT can “capture” that knowledge asset and makes it an active operational component of the company, that is the company may use the CDT in place of the physical entity that has that knowledge. 

The first step, as shown in the graphic, is to use the CDT as a representation of a knowledge asset in the company. This can help in assessing what is the available knowledge with respect to the one needed. Notice that this is something that is already happening (even without the CDT): an HR department has a “map” of the company’s knowledge space, i.e. who knows what. This is essential to associate human resources to tasks (technical departments have a map of the available tools and what they can be used for, as an example what is the flexibility of a robot and how it can be used in a needed environment). A CDT would provide a sort of standardised way to represent the knowledge. In addition a CDT will have the capability to keep this representation up to date (through shadowing). It is also important, as mentioned, to identify gaps (usually it is a technical area that defines the needs and the HR looks for ways to meet those needs, identifying possible gaps).

The next step. shown in the graphic, is to identify the missing knowledge in the knowledge space outside the company (the IEEE knowledge ontology is a good reference point to navigate the knowledge space of technology, including the very latest of tech). Once this “missing” knowledge is identified it should be brought inside the company.

There are, of course, several ways to bring the needed knowledge “inside” the company:

  • Train some employees to acquire that knowledge (in this case one should also identify those employees that would be better suited for training -pre-existing competences, time availability…);
  • Hire a new employee with the desired knowledge;
  • Hire a consultant to support the project with the needed knowledge (makes good sense if that need is expected to be temporary…);
  • Partner with another company that can provide that knowledge and take care of the part of the project that requires that knowledge
  • Buy a machine/application embedding that knowledge (add to or upgrade existing resources).

The added knowledge will be reflected in the related CDT, the one associated to the trained employee, to the newly hired one, … to the machine/application.

Further down the lane we can imagine that the acquisition of knowledge can happen at the CDT level without having to involve the physical entity. Now, this might seem like science fiction but as a matter of fact is what happens with robots and sw applications where new software version can be installed “adding” knowledge. 

Could this be done for a person? we have clearly no way to download knowledge in a brain, it has to be acquired through “learning”. However, if we consider CDT at stage 4 and 5, where the CDT is an augmented set of the associated entity knowledge, we can well add knowledge to it.

The crucial point here is that this CDT will in part mirrors the existing knowledge of its associated person and in part will augment them. Notice that with a CDT the knowledge owned constitute a single “space”, hence the (AI) functions that are transforming the knowledge into an executable one take the whole knowledge space into account.

A new word has been coined to define this type of CDT that has an embedded augmented knowledge: and hybrid CDT (the same name applies to the compound CDT including a machine CDT and a person CDT cooperating in symbioses).

In this “future” (but not science fiction) scenario we face several tricky issues as previously mentioned. We are also entering into a new business space as I will discuss later.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the New Initiative Committee and co-chairs the Digital Reality Initiative. He is a member of the IEEE in 2050 Ad Hoc Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.