Periodic Reporting for period 3 - CAPRI (Cognitive Automation Platform for European PRocess Industry digital transformation)
Período documentado: 2022-10-01 hasta 2023-09-30
The main aim is to provide process industries with digital tools so people at different organization levels can cope with daily challenges. These include feedstock variations, higher energy efficiency, higher emissions restrictions and flexibility that requires complex synchronization among processes.
To increase understanding of the underlying data and processes, CAPRI uses the analogy of human cognition. that is extremely efficient in getting a big picture of a context, what is causing a situation and what can be the consequences before reacting. CAPRI envisions the process of monitoring/sensing and controlling/reacting in process industry plants to transform them as cognitive plants using advanced solutions inspired by this cognition analogy.
CAPRI project, has finalised in September 2023 and has achieved the main objectives set at the proposal stage. The goalsare driven by the need of the digital transformation of the European process industry by investigating, developing and testing a cognitive automation platform that integrates 18 different cognitive solutions defined in each one of the three project’s use cases. This platform has been designed to enable the cognitive solutions to obtain reductions of use of raw materials, reduction of energy consumptions and reductions in CO2 footprint, being replicable in other sectors. With the finalization of the project, it can be shown that the reductions have been achieved thanks to the strength collaboration of the thirtheen partners involved, from seven different countries. The project has been deployed in three important sectors belonging to the SPIRE ecosystem: Asphalt manufacturing, billets and bars of Steel production and the production of tablets in the pharma industry.
To increase understanding of the underlying data and processes, CAPRI uses the analogy of human cognition. that is extremely efficient in getting a big picture of a context, what is causing a situation and what can be the consequences before reacting. CAPRI envisions the process of monitoring/sensing and controlling/reacting in process industry plants to transform them as cognitive plants using advanced solutions inspired by this cognition analogy.
CAPRI project, has finalised in September 2023 and has achieved the main objectives set at the proposal stage. The goalsare driven by the need of the digital transformation of the European process industry by investigating, developing and testing a cognitive automation platform that integrates 18 different cognitive solutions defined in each one of the three project’s use cases. This platform has been designed to enable the cognitive solutions to obtain reductions of use of raw materials, reduction of energy consumptions and reductions in CO2 footprint, being replicable in other sectors. With the finalization of the project, it can be shown that the reductions have been achieved thanks to the strength collaboration of the thirtheen partners involved, from seven different countries. The project has been deployed in three important sectors belonging to the SPIRE ecosystem: Asphalt manufacturing, billets and bars of Steel production and the production of tablets in the pharma industry.
The specific objectives of the project were the Process Industry Digital Transformation enabled by Cognitive Solutions that provide these industries flexibility of operation, improvement of performance across different indicators (KPIs) and state of the art quality control of its products and intermediate flows and finally to develop a methodology that defines the steps for the transformation of an automated process industry plant into a cognitive process plant based on knowledge models that integrate the information from planning, control and operation management system. Based on a solid open source digital foundation like FIWARE, CAPRI has created an open source blueprint of a cognitive automation platform, the CAP, that integrates our cognitive solutions developed, most of them defined as Key Exploitable Results (KERs) of the project. Our KERs have been included in the Innovation Radar. The KERs includes different Cognitive Solutions (from new sensors to process planning algorithms), the CAP, the 6P’s digital transformation methodology and the open data generated. Those KERs constitute the main deliverables of the project and the partners has established their approach to exploit them and let the outside world take advantage of them like the public available CAP blueprints for each three industrial sectors involved.
The main challenge in all the use cases have been related with the acquisition of the data, moving the data into the cloud to be accessible for all, but once the step of the digitalization of a plant is achieved the rest of the work starts to run very easy.
The market analysis of the solutions to be developed inside the project was realized as a preliminary version to all, with the objective of identifying the KERs. After the KERs were defined, the market analysis was done completely for the different KERs of the project.
For the project, have been defined three general KPIs to measure the improvements with the project, reduction of the use of raw materials in 5-20%, reduction of use of energy of 5%, and the reduction of CO2 footprint in 5%.
In the asphalt use case, have been developed 5 cognitive solutions, three of them, declared as KERs, thanks to these five solutions, the results achieved in the use case have been a reduction of use of raw materials around 18%, savings in the use of energy and the reduction of CO2 footprint around 16%.
The steel use case, has their own cognitive solutions, 5 too, two included in the innovation radar has KERs, with the help of all, the improvements have been a reduction of raw materials of 10%, energy 3% and CO2 footprint 3%.
The pharma use case, the improvements depend a lot of the product produced, and the reduction of use of raw materials can oscillate from 10 to 20%, reduction of energy consumption from 7 to 8%, and the CO2 footprint have been of the 5%. In the pharma use, two of the solutions deployed, have been included in the innovation radar as KERs.
Each of one the solutions deployed can be improved as the most of them are prototypes, so the improvement would be respect the durability and the accuracy of the models in the hard conditions of the industries.
The project has increased their external visibility disseminating intermediate results (9), journal papers, articles at congresses, explanatory videos, interviews, web updates (23), open access sharing of (50) results. Additionally, the project intensified its outreach through participation in (33) events, (3) trade fairs and clustering activities (SPIRE06, ENGINE and AI-CUBE) and launching a network of DiHs specialized in process industry (PIHUB).
The main challenge in all the use cases have been related with the acquisition of the data, moving the data into the cloud to be accessible for all, but once the step of the digitalization of a plant is achieved the rest of the work starts to run very easy.
The market analysis of the solutions to be developed inside the project was realized as a preliminary version to all, with the objective of identifying the KERs. After the KERs were defined, the market analysis was done completely for the different KERs of the project.
For the project, have been defined three general KPIs to measure the improvements with the project, reduction of the use of raw materials in 5-20%, reduction of use of energy of 5%, and the reduction of CO2 footprint in 5%.
In the asphalt use case, have been developed 5 cognitive solutions, three of them, declared as KERs, thanks to these five solutions, the results achieved in the use case have been a reduction of use of raw materials around 18%, savings in the use of energy and the reduction of CO2 footprint around 16%.
The steel use case, has their own cognitive solutions, 5 too, two included in the innovation radar has KERs, with the help of all, the improvements have been a reduction of raw materials of 10%, energy 3% and CO2 footprint 3%.
The pharma use case, the improvements depend a lot of the product produced, and the reduction of use of raw materials can oscillate from 10 to 20%, reduction of energy consumption from 7 to 8%, and the CO2 footprint have been of the 5%. In the pharma use, two of the solutions deployed, have been included in the innovation radar as KERs.
Each of one the solutions deployed can be improved as the most of them are prototypes, so the improvement would be respect the durability and the accuracy of the models in the hard conditions of the industries.
The project has increased their external visibility disseminating intermediate results (9), journal papers, articles at congresses, explanatory videos, interviews, web updates (23), open access sharing of (50) results. Additionally, the project intensified its outreach through participation in (33) events, (3) trade fairs and clustering activities (SPIRE06, ENGINE and AI-CUBE) and launching a network of DiHs specialized in process industry (PIHUB).
The main objectives of the proposal of reduction of use of raw materials, use of energy and the CO2 footprint, summarizing the whole CAPRI project, the results for the first KPI have been from 10 to 20% of reduction, for the use of energy the reduction have been from 3% to 16%, depending of the product produced and the use case, and the reduction of the CO2 emissions have been from 3% to 16% too.
CAPRI has 4 main impacts as expressed in the section 2.1 of the DoA, where:
IMPACT1: Show potential for improved performance in cognitive production plants
IMPACT2: Increased production performance, energy and resource consumption, or waste or by-products production
IMPACT3: Project outcomes should demonstrate a positive environmental impact, by reducing CO2 emissions
IMPACT4: Effective dissemination of major innovation outcomes to the current next generation of employees of the SPIRE sectors
The four impacts have been covered with the development of the CAP, the cognitive automation platform, and the Cognitive solutions. The first impact it is associated to our first KPI, the second impact with the first and second KPI defined, the third, with the third KPI, and the las impact, related with the innovation radar, the KERs developed, and the attendant to the events to disseminate the results of the project.
Where it has been demonstrated that the project has achieved the objectives
The business model for the project was an analysis done that presents a comprehensive summary of CAPRI's value proposition, potential customers, customer channels, key stakeholders, and financial analysis pertaining to the potential revenue streams and cost structures of each identified KER.
All of these markets analysis appear highly attractive and show great potential for successful business and the exploitation of CAPRI solutions.
The financial analysis for the CAPRI solutions has been conducted collaboratively with the consortium, encompassing cost structures and revenue projections. These figures, in conjunction with market data, serve as inputs for the Profit Simulation Tool.
CAPRI has 4 main impacts as expressed in the section 2.1 of the DoA, where:
IMPACT1: Show potential for improved performance in cognitive production plants
IMPACT2: Increased production performance, energy and resource consumption, or waste or by-products production
IMPACT3: Project outcomes should demonstrate a positive environmental impact, by reducing CO2 emissions
IMPACT4: Effective dissemination of major innovation outcomes to the current next generation of employees of the SPIRE sectors
The four impacts have been covered with the development of the CAP, the cognitive automation platform, and the Cognitive solutions. The first impact it is associated to our first KPI, the second impact with the first and second KPI defined, the third, with the third KPI, and the las impact, related with the innovation radar, the KERs developed, and the attendant to the events to disseminate the results of the project.
Where it has been demonstrated that the project has achieved the objectives
The business model for the project was an analysis done that presents a comprehensive summary of CAPRI's value proposition, potential customers, customer channels, key stakeholders, and financial analysis pertaining to the potential revenue streams and cost structures of each identified KER.
All of these markets analysis appear highly attractive and show great potential for successful business and the exploitation of CAPRI solutions.
The financial analysis for the CAPRI solutions has been conducted collaboratively with the consortium, encompassing cost structures and revenue projections. These figures, in conjunction with market data, serve as inputs for the Profit Simulation Tool.