Pearson–Bravais correlation coefficient is estimated as the ratio between the covariance of the two variables and the product of their standard deviations as follows [75]:
(1.32)
The correlation coefficients are plotted in a correlation matrix with the structure shown in Table 1.9.
Table 1.9 Example of a correlation matrix for a model with five attributes (v1, v2, v3, v4, v5).
| v 1 | v 2 | v 3 | v 4 | v 5 | |
|---|---|---|---|---|---|
| v 1 | 1 | 0.4 | −0.8 | 0.6 | −0.3 |
| v 2 | 0.4 | 1 | 0.1 | 0.8 | −0.5 |
| v 3 | −0.8 | 0.1 | 1 | 0.2 | 0.1 |
| v 4 | 0.6 | 0.8 | 0.2 | 1 | −0.3 |
| v 5 | −0.3 | −0.5 | 0.1 | −0.3 | 1 |
1.6 Knowledge Upgrading in Industries
KG in industry is achieved by upgrading the information system [32] in different stages, as illustrated in Figure 1.26. The knowledge base (KB) is the starting point representing the industry knowhow provided by the digital information. A first increase of the knowledge is obtained by adding new applications concerning software and tools optimizing production such as:
RE tools.
Design and simulation tools.
Rapid prototyping tools.
Software managing IoT sensor network and monitoring production.
Building information models implemented in AR systems.
Digital sensors to be integrated in analogical machines.
HMI as data entry systems for data digitization according to the Industry 4.0 principle.
Figure 1.26 Knowledge gain in industry.
All digitized data are typically managed by a unique ERP collecting all data into DB systems. Digitized data travel through the ESB or LAN bus line linking all the software and the information of the industry network [32]. The KG is performed by reading the outputs of advanced analyses related mainly to big data analytics and AI results. The KG is fundamental for industry research. The information system upgrade involves the front‐office, the back‐office, and the whole network infrastructure, powering contact management, E‐commerce, customer relationship management (CRM), BPM, E‐learning, and BI algorithms providing association rules and cost predictions [76]. Big data and data mining are important for BI decision‐making processes, and are able to [77, 78]:
Find possible inefficiencies.
Define human resources KPIs.
Efficiently manage the scheduling of the activities.
Classify human resource skills.
Classify service typologies.
Define strategic marketing.
Classify industry locations based on efficiency estimation.
The innovative technology to be implemented in industrial sectors is listed in Table 1.10 (Horizon 2020 topics).
Table 1.10 Industrial sectors and advanced application fields.
| Industrial sectors | Application fields |
|---|---|
| Processes and industrial installationsManufacturing and advanced transformation | Methodologies and standards for the machine and system design in complex manufacturingTools for design and implementation of high‐quality productsAutomation and integration of complex manufacturing systems for real‐time productionsInformation technologies for the integration of supply chain and decision‐making processControl technologies, predictive, maintenance, diagnosis of manufacturing systems improving efficiency and life cyclesTechnologies and software solutions for real manufacturing and logisticsMechatronic components for efficiency production and productsNew machines and eco‐sustainable systems to optimize energy efficiency and the environmental impact of production systemsInnovative materials for components, machines, and systemsIntelligent adaptive production systems |
| Mobility and transport | Road/sea/rail transport technologies and solutions to reduce environmental impact, optimize safety, quality, performance, and energy efficiencyEnvironmentally transport technologies for sustainabilityIntelligent transport systemsIntelligent inspection systemsSmart road technologies |
| Aerospace and aeronautics |
New materials and production processesPredictive maintenance for aircraftEco‐friendly enginesTechnologies for reduction of environmental impactSimulation methodologies for integrated design in the aeronautical fieldTechnologies for autonomous systemsAdvanced air traffic managementIntegrated technologies for securitySpace transport technologiesSpace advance operational technologiesRemote sensing and data navigation technologies
|
