Periodic Reporting for period 2 - VIMS (Virtual IoT Maintenance System)
Okres sprawozdawczy: 2021-02-01 do 2022-04-30
The term Industry 4.0 was coined in 2011 as part of a strategic roadmap to promote the digitalization of manufacturing. Industry 4.0 which is considered to be the fourth Industrial Revolution, is led by intelligent manufacturing. The concept of Industry 4.0 is based on the integration of digital innovations such as Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing and Big Data analysis, and is mainly dependent on building a Cyber-Physical system (CPS) to realize a digital and intelligent factory, in order to promote manufacturing to become more digital, information-led, customized, and green.
Currently, Industry 4.0 is the vision for the future, because it involves many aspects, and faces many of challenges, including industrial, economic and social ones. The CPS is the core foundation of Industry 4.0 since it connects all physical devices to the Internet, and allows to incorporate five functions: computing, communications, precision control, coordination and autonomy . Through integration of the virtual and physical worlds, smart production is made possible, so Industry 4.0 is equivalent to CPS. Nevertheless, how to converge the physical and cyber worlds of manufacturing is still one big industrial challenge within the Industry 4.0 . Referring to the economic challenge, the implementation of Industry 4.0 in general poses threats regarding large investments required and uncertain profitability. Furthermore, SMEs manufacturers perceive the transformation towards Industry 4.0 as challenging, due to their low degree of process standardization and less automated production equipment. Finally, and as to social challenges, it is worth mentioning the actual employee’s fears and concerns regarding: the need to be qualified, dependency on technical assistance systems and workplace safety in human-machine interaction systems. By overcoming the aforementioned challenges of Industry 4.0 the future of European manufacturing will see industrial production systems become more intelligent, which will greatly improve industrial productivity up to 30%, enhancing competitiveness, and socio-economic sustainability in European factories. In fact, European Industry 4.0 market is projected to account for more than a third of global Industry 4.0 investment by 2020. This market is expected to grow at an impressive average annual growth rate of 22%. Reaching a value of €287 billion in 2020 . Taking these premises into account, it can be concluded that developing new advanced solutions based on ICTs is a great market opportunity within the manufacturing sector.
In thise sense,the VIMS project aims to develop and industrialise a new, complete, and integrated digital ecosystem (VIMS system/platform) for industrial and manufacturing environments. The core of the VIMS system combines an IIoT (Industrial Internet of Things) platform (along with all its data collected from smart instrumentation, advanced analysis techniques and AI models) with a Digital Twin (DT) of the factory or production line.
Currently, Industry 4.0 is the vision for the future, because it involves many aspects, and faces many of challenges, including industrial, economic and social ones. The CPS is the core foundation of Industry 4.0 since it connects all physical devices to the Internet, and allows to incorporate five functions: computing, communications, precision control, coordination and autonomy . Through integration of the virtual and physical worlds, smart production is made possible, so Industry 4.0 is equivalent to CPS. Nevertheless, how to converge the physical and cyber worlds of manufacturing is still one big industrial challenge within the Industry 4.0 . Referring to the economic challenge, the implementation of Industry 4.0 in general poses threats regarding large investments required and uncertain profitability. Furthermore, SMEs manufacturers perceive the transformation towards Industry 4.0 as challenging, due to their low degree of process standardization and less automated production equipment. Finally, and as to social challenges, it is worth mentioning the actual employee’s fears and concerns regarding: the need to be qualified, dependency on technical assistance systems and workplace safety in human-machine interaction systems. By overcoming the aforementioned challenges of Industry 4.0 the future of European manufacturing will see industrial production systems become more intelligent, which will greatly improve industrial productivity up to 30%, enhancing competitiveness, and socio-economic sustainability in European factories. In fact, European Industry 4.0 market is projected to account for more than a third of global Industry 4.0 investment by 2020. This market is expected to grow at an impressive average annual growth rate of 22%. Reaching a value of €287 billion in 2020 . Taking these premises into account, it can be concluded that developing new advanced solutions based on ICTs is a great market opportunity within the manufacturing sector.
In thise sense,the VIMS project aims to develop and industrialise a new, complete, and integrated digital ecosystem (VIMS system/platform) for industrial and manufacturing environments. The core of the VIMS system combines an IIoT (Industrial Internet of Things) platform (along with all its data collected from smart instrumentation, advanced analysis techniques and AI models) with a Digital Twin (DT) of the factory or production line.
During this second reporting period, all the implemented actions have been aimed at:
- Deployment of the IoT platform and the modules needed, the Azure Digital Twin Graph, the storage modules, and the connectivity between the different modules to meet the architecture of the aeronautical use cases and design and development of each of the different data acquisition and processing systems.
- Development of applications related to vertical business: Airbus, Roche Kaiseraugst and Roche Mannheim.
- Test plan definition for both uses cases: pharmaceutical and aeronautical. Test plan campaign and results gathering with the aim to validate the applications running in the real environment and identify improvements.
- Definition of the scaling up design basis considering the developed demonstrators and the results obtained per use case.
- Perform the feasibility study, quantifying the system benefits and establishing the business case for VIMS. Detailing: a planning depicting resources and effort (in the best case), cost structure analysis as general approximation, creation of materials (videos, web publications, media…) to promote the project results.
- Design and development of an educational programme will foster a faster welcome to VIMS vertical business applications.
- Identify market volume that the developed solution could reach in the short/medium term (SOM), the platforms or solutions with similar functionalities that could compete with VIMS and analyse the weaknesses and strengths of the platform, as well as the opportunities and challenges it could face in the short/medium term.
- Draw up a marketing plan through which it is possible to scale the solution to different factories, customers and sectors.
- Identify main interesting result with a high potential to be "exploited" – Exploitable results-.
- Analyse IPR (Intellectual Property Rights) for all outcomes of the VIMS Project.
- Deployment of the IoT platform and the modules needed, the Azure Digital Twin Graph, the storage modules, and the connectivity between the different modules to meet the architecture of the aeronautical use cases and design and development of each of the different data acquisition and processing systems.
- Development of applications related to vertical business: Airbus, Roche Kaiseraugst and Roche Mannheim.
- Test plan definition for both uses cases: pharmaceutical and aeronautical. Test plan campaign and results gathering with the aim to validate the applications running in the real environment and identify improvements.
- Definition of the scaling up design basis considering the developed demonstrators and the results obtained per use case.
- Perform the feasibility study, quantifying the system benefits and establishing the business case for VIMS. Detailing: a planning depicting resources and effort (in the best case), cost structure analysis as general approximation, creation of materials (videos, web publications, media…) to promote the project results.
- Design and development of an educational programme will foster a faster welcome to VIMS vertical business applications.
- Identify market volume that the developed solution could reach in the short/medium term (SOM), the platforms or solutions with similar functionalities that could compete with VIMS and analyse the weaknesses and strengths of the platform, as well as the opportunities and challenges it could face in the short/medium term.
- Draw up a marketing plan through which it is possible to scale the solution to different factories, customers and sectors.
- Identify main interesting result with a high potential to be "exploited" – Exploitable results-.
- Analyse IPR (Intellectual Property Rights) for all outcomes of the VIMS Project.
The literature proposes a classification of DTs into three subcategories, according to their level of data integration: Digital Model (DM), Digital Shadow (DS) and Digital Twin. In a DM all data exchange is done in a manual way, while in a DS a change in state of the physical object leads to a change of state in the digital object, but no vice versa. Instead, in a DT the data flows between an existing physical object and a digital object are fully integrated in both directions. Taking this classification into consideration, Kritzinger et al., (2018) found that most of the publications (within the topic DT and with a publication date latter than 2014) were classified as DS and DM with only one case-study concerning a DT, which was implemented within a laboratory environment . There is further research needed for case-studies industrial environments in order to evaluate the possible benefit of the DT, since research that describes the DT in the production industry is still in the early stages.
Combining advanced technologies such as DT with AR and/or VR through the development of new business applications can improve the future of manufacturing. With this regard, in the literature it can only be found a Proof-Of-Concept that introduces a protocol of an DT and AR industrial solution within the framework of predictive maintenance.
The main expected outputs of the project can be summarized as follows:
- A general customizable and scalable VIMS system architecture.
- Return of Investment for manufacturing companies estimated to be achieved in 1-2 years and increase of 5-15% industrial productivity in factories, as well as increasing high-skills jobs, by increasing 60% workforce performance and reducing by 66% factory safety incidents by developing both the virtual training and guided assistance business applications.
- Obtaining more energy-efficient factories by reducing 10% energy consumption and 8% wastes by means of the cyber-physical integration of factories (Factory Digital Twin).
- Decreasing 20% maintenance costs of manufacturing plants, by reducing machinery downtimes by 15-20%.
Combining advanced technologies such as DT with AR and/or VR through the development of new business applications can improve the future of manufacturing. With this regard, in the literature it can only be found a Proof-Of-Concept that introduces a protocol of an DT and AR industrial solution within the framework of predictive maintenance.
The main expected outputs of the project can be summarized as follows:
- A general customizable and scalable VIMS system architecture.
- Return of Investment for manufacturing companies estimated to be achieved in 1-2 years and increase of 5-15% industrial productivity in factories, as well as increasing high-skills jobs, by increasing 60% workforce performance and reducing by 66% factory safety incidents by developing both the virtual training and guided assistance business applications.
- Obtaining more energy-efficient factories by reducing 10% energy consumption and 8% wastes by means of the cyber-physical integration of factories (Factory Digital Twin).
- Decreasing 20% maintenance costs of manufacturing plants, by reducing machinery downtimes by 15-20%.