Technology Transfer

Artificial Intelligence (AI) is a cognitive science that has been little used in manufacturing processes. In this context, the IAsmin Platform will face these technological challenges through pre-competitive and competitive projects with the development of new technologies and methodologies. Therefore, there is a vast space that needs to be explored to take the industry to the “4.0” level.

There are also concerns that organizations may not be able to adapt, that governments may fail to employ and regulate new technologies as a form of revenue, that changes may create information security problems and even allow damage to industrial facilities, inequality and fragmentation of societies. According to Schwab in “The Fourth Industrial Revolution - World Economic Forum”, the most recent changes in the historical context drive this revolution, but there will be impacts on governments, businesses, civil society and individuals. At the center of his analysis is the conviction that the Fourth Industrial Revolution is under the control of all of us, as long as we can take advantage of the opportunities it presents.

Industrial applications of AI need to be systematized and methodologies need to be established to provide solutions for industrial applications. Therefore, there is a challenge in the application of AI in the industry. In this sense, Brazil has many natural and human resources, but there is still a technological gap in terms of the adoption of technologies used in industry compared to other countries in different continents. New technologies and developments in areas such as artificial intelligence emerge as a great opportunity for the growth of the industrial sector in Brazil, since AI approaches can be considered as a relatively low cost compared to other new products and disruptive process technologies. The next technologies, changes in lifestyle, organization of cities in relation to public transportation, health (recent problems caused by COVID 19), globalization and sustainability accelerate the demand for innovation.

Although disruptive technologies are essential, work on disruptive methodologies, such as AI, often requires additional infrastructure, such as that of Technical Schools and Universities. Studies (Matsumae et al., 2018; Wei et al. 2018; Lee et al., 2018) show the importance of a “heterogeneous network” (Chesbrough, 2003; Kelley, 2009) with a focus on different aspects of development. Therefore, the main objective of the IAsmin Platform will be to allow the interaction between industry and universities to create a platform where technology transfer can occur in a broad, transparent, systematic and secure way between participants. Different levels of technology transfer will be established, allowing from the foundations, related to the application of AI, to the manufacture of prototypes and product development. Consequently, the direction of the development of the AI Center follows not only incremental development, but also disruptive technologies and approaches for innovation.

The IAsmin Platform will face some challenges, such as the exchange of information between all participants, as industry partners can be from different sectors of the industry or, even more challenging, be competitors. Intellectual property agreements must be made to ensure the dissemination and transparency of research, as well as the integration of the research group of industry partners and partner ICTs.

Transparency as a backdrop will be very important to drive technology transfer. The integration will be led by Prof. Dr. Ronnie Rodrigo Rego, Instituto Tecnológico de Aeronáutica, in partnership with researcher Dr. Alessandro Santiago dos Santos, from IPT.

Technology Transfer Methodology

There is a growing demand for innovation. The work on disruptive ideas and models is possible through the sharing of experiences between industry, IPT, startups and universities to make innovation, which will be enabled by the IAsmin Platform, which will be a facilitator of the integration of industry and its challenges, with the IPT and the universities.

The technology transfer strategies will be based on different TRLs (Transference Readiness Levels). The development levels with lower TRLs will be those linked to scientific research. As advances are made based on TRLs, patents can be requested, for example, as detailed in the following text.

Technology transfer mechanisms and forms

  1. The Platform will contribute to applied research with a scientific and technological focus. The research developed at the AI Center will be open, in accordance with the Intellectual Property Policy and the definition of confidentiality levels, although they will be conducted in the direction of problem assessment and description of partner industries of the Center. This research will be developed at universities and will be published in journals or presented at conferences, as a result of the work of master's and doctoral students.
  2. The goal is to create an integration center with a database of the different projects, as well as evaluated between the different groups. This will provide an "external" environmental stimulus to the development process. Methodologies must be established and integrating all groups and research lines is important for the dissemination of knowledge developed on the Platform. The integration tools will be developed based on the knowledge of the research groups of the IPT, Universities and Industry and arbitrated by the Governance structure.
  3. Part of the technology transfer will be done directly by the industrial teams, as the human resources will be trained for the challenges within the disruptive approach of Artificial Intelligence. It is intended to promote national and international exchange of human resources, both researchers/students, and if necessary, obtain human resources from company collaborators, to share technologies. It will also be encouraged that industries host students to support the transfer of technology and knowledge.
  4. The promotion of a disruptive approach and innovation during workshops is also planned, allowing problems and / or shared approaches of the sector to define priorities to work on multidisciplinary and integrative solutions that require network development. Therefore, the workshops will allow the integration of industry and ICTs, as well as the identification of problems and challenges. For high-technology products, the transfer involves a whole range of technological knowledge, scientifically based on processes, knowledge and specific skills, using an interactive process in which the different specialized participants absorb, assimilate, emit and exchange knowledge.
  5. Knowledge mapping (research in industries, universities, patents) is an important initiative to guide and generate a baseline of the evolution of AI in industry and to work with innovation. Know-how is the key element of the following aspects: a) understand the problem and focus the power of industrial AI on its solution; b) understand the system so that correct data with the right quality can be collected; c) understand the physical meanings of the parameters and how they are associated with the physical characteristics of a system or process; and d) understand how these parameters vary from machine to machine. Evidence is also an essential element in the validation of industrial AI models and their incorporation with cumulative learning capacity. Collecting data patterns and the evidence associated with these patterns can improve the AI model to become more accurate, comprehensive and robust.
  6. Public financial systems should be used to improve funds and support innovative developments. It will also promote and show the government the importance of the center to build the AI approach. Additionally, it will encourage industries to become part of proposals.
  7. Research that has reached higher TRLs will allow technology transfer, including conceptual models for prototyping. This will enable a competitive approach and the generation of startups or spin-offs that will incorporate the results of research developed by the Platform into their products or services.
  8. Licensing covers a variety of contractual agreements by which an organization (owner) sells an intangible asset or property rights (patents, industrial secrets, know-how, trademark and company name) to a company (recipient). These transfer or intangible or property rights constitute the essence of a licensing contract. With this contract, the recipient company provides a limited range of rights to produce and market the licensed object in specific geographical regions. Results with higher TRLs and that can generate patents will have IPT support.
  9. The growing use of connected technologies makes the intelligent manufacturing system vulnerable to cyber risks. Currently, the scale of this vulnerability is underestimated and the sector is not prepared for the security threats that exist. This will be a theme present in the developments made and although it has no direct relation to technology transfer, it will be an aspect to be addressed at all levels of development. The Platform will deal with a lot of digital information and the correct protection and assurance that the information is safe and will not be misused, here including technology information such as databases, developed systems, programming code, reports, etc. is something that will be handled by the Technical Diffusion Coordination and other Governance bodies of the Center.
  10. The IAsmin Platform has a Governance that will monitor scientific and technological developments and legislate transparently on issues involving other aspects related to confidentiality problems in confidentiality, ethics and sustainability issues of the Platform's products.

The ethical and legal aspects of AI have been the subject of numerous academic studies. Two main problems are considered: the confusion between ethical and legal aspects and a certain disrespect for the law. Both problems require an analysis and a solution. The first prevents a real understanding of the role and function of ethics and law in the context of AI. The second reflects a lack of appreciation for the role of law as an instrument of social and political order. The law is necessary in relation to any subject or reality simply because it establishes rules of social behavior necessary for the coexistence of people in society. The law cannot be ignored, nor confused with ethics. Both are necessary parameters of social behavior in any field or context and, in particular, in areas of significant complexity, such as AI.


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