This research project maps AI and BD technologies in ten sectors of the process industry to evaluate their maturity level
AI Cube aims to analyse the usage and benefit of artificial intelligence within the process industry. Promoted and brought into life by the EU Horizon 2020 Research and Innovation Program, the AI CUBE projects above all is about building a road map for the usage of AI in process industries. We want to develop an understanding about which digital technologies with intersections to AI and Big Data are already used within process industries and which of those technologies can be transferred potentially well to other sectors. The main focus lies on the ten SPIRE-Sectors: steel, chemicals, minerals, non-ferrous metals, water, ceramics, cement, engineering, refining, pulp and paper.
Although generated and available data of supply chain networks have increased, this amount of data is not yet fully exploited by many enterprises of the process industry. For example, in many cases there is a lack of quantitively and qualitatively sufficient data pools for the use of high-profile machine learning methods in a suitable accuracy. Existing AI applications in several companies or sectors with a high maturity level are not transparent visible and can therefore not be used as a reference for other sectors.
The concept of AI CUBE is based on a three-dimensional model, consisting the levels of inserted technologies, the SPIRE sectors of the process industry and the main implementation processes. Concerning the diverse technologies, different basis technologies of artificial intelligence as well as necessary Big Data technologies are distinguished. The processes, in which artificial intelligence and Big Data are used, along the value-added processes reach from market analysis, trends and innovations, product configuration of management and supply chain handling, maintenance all the way to process monitoring and research.
The consideration of the three dimensions enables a picture of the current usage and particular maturity level of implemented applications in the different sectors. For this maturity related representation, the research project will develop its own maturity model for the evaluation of AI and Big Data applications.
First Target of the AI Cube project is the identification and maturity level assessment of AI-solutions, which are used in the different sectors and processes of the process industry. Moreover, present barriers in order to transfer existing technologies into other sectors or processes and the profound integration of solutions are going to be explored. The resulting road map serve as a guidance for researchers, managers and industry partners from process industry, to facilitate the implementation of AI and BD applications in the future and to provide an overview over the current state and maturity level of diverse technologies. An intense cooperation with partners from industries and technology providers is an important precondition for the fully understanding and insight into AI application usage as well as their maturity level. Therefore, in terms of this project the various stakeholders are intensively involved and integrated into the different project phases.
With the aim to develop and implement the cube-concept for maturity level assessment of AI and BD technologies into the european process industry, the following steps of the research project are:
The main aspect here is the development of proven AI and BD business models, that work across industry sectors and fit in line with the A.SPIRE 2050 vision.
Fraunhofer IML took over the leading role in the sector of identification of AI and BD technologies including the maturity level assessment. Part of this task is the classification of relevant AI and BD applications into the developed CUBE-concept while considering their current maturity level. This sector and process overlapping analysis enables a systematic identification of focal points and areas of implementation, that are so far little noticed. Moreover, subsequent improvement strategies and pathways can be developed.
CIAOTECH S.R.L / PNO GROUP B.V.
ZARAGOZA LOGISTICS CENTER
IRIS TECHNOLOGY SOLUTIONS S.L.