EFFRA Innovation Portal

Pathways

Pathways

Autonomous Smart Factories Pathway

General purpose software

Spreadsheet/texteditor ERP

Spreadsheet/texteditor MOM

Manual data acquisition

Dedicated software in silos

Dedicated ERP software implemented

Dedicated MOM Software Implemented

Data acquisition/monitoring/analysis (SCADA) implemented but isolated

Connected IT and OT

ERP-MOM systems connected

MOM-SCADA systems connected

IoT enabled SCADA, MOM-MES, ERP (…) connectivity

Humans actively connected

Off-line optimisation

Off-line Digital Manufacturing Process Optimisation on factory level

Off-line Digital Manufacturing Process Optimisation on machine level

Platform enabled optimisation

Realtime optimisation

Autonomous /online/realtime Manufacturing Process Optimisation on factory level

Autonomous /online/realtime Manufacturing Process Optimisation on machine level

Hyperconnected Factories Pathway

General purpose software

Spreadsheet and text editor based SCM, CRM

Spreadsheet/texteditor ERP

Administrative transactions digitalised

Dedicated software in silos

ERP implemented

SCM implemented

Basic internal connectivity

ERP and SCM connected

Dedicated IT connection to some supply chain partners

SCM - MES - ERP Software connected to SCM - MES - ERP software of suppliers or customers

Forecasting of required capabilities

High level planning using dedicated digital connections

Dynamic IT connections to new supply chain partners

Common digital platform used for tenders and bidding

Visibility of work in progress

Dynamic detailed scheduling and rescheduling

Collaborative Product-Service Factories Pathway

Product, no Service

Use of CAD systems

Use of PDM systems

Product and disjoint Service

PLM Systems (integrating CAD and PDM)

Use of CRM Systems

Service-enabled Product Design

Voice of suppliers Customers / Users

Service orient. Product Design (integration of PLM and CRM)

Product-Service Innovation

Closed loop PSS Design (Connected to users data)

Service Innovation and new Business Models

Product-Service Symbiotic Evolution

Digital Platforms for next generation PS Systems lifecycle management

Cybersecurity Pathway

Security level 1

Physical and logical password

Malware (including Ransomware, APT, Virus, ...) protection

Logging and monitoring, machine learning and AI - Cybersecurity Controls

(Systemic) Penetration Testing

Security level 2

Transmission data protection

Password policy

Physical security

Multi-factor authentication

Security level 3

Security training and awareness

Personnel vetting procedures

User account management

Token management

Security level 4

Privileged account control

Database integrity

Software integrity

Back Office data flow security

Intrusion detection

Security level 5

Digital platform environment segregation

CyberSecurity incident response capability - CSIRT

User session integrity

Critical activity outsourcing

Transaction controls

Data Space Pathway

DS Pathway - Maturity Levels

No Data Control

No Data Management Culture in the company

No specific Data Protection measures in place regarding storage, computation and transfer of data

Data not processed or processed by default procedures out of control for the company

Data analytics not performed or performed by third parties out of control of the company

Data visualisation tools not implemented or implemented by third parties out of control of the company

Data Sharing not implemented or implemented without any control

Data stored in Enterprise Application and managed from there

Each single Enterprise Application (ERP SCM PLM) is responsible for Data Protection

Data processed inside Enterprise Applications (ERP SCM PLM) according to architectures and tools predefined by them

Data Analytics procedures implemented (and replicated) from inside Enterprise Applications only

Data visualisation tools embedded in Enterprise Applications on top of predefined sets of Data

Data Sharing allowed from inside Enterprise Applications to a predefined value ecosystem

Secure Data Bridges between silos implemented on a case-by-case basis

Data Processing architectures (embedded, edge, cloud) implemented for ad-hoc data bridges in Enterprise Applications

Data Analytics procedures implemented across silos in an ad-hoc fashion

Data visualisation applications are developed ad-hoc cross-silos to show data coming from different sources

Data Sharing from different sources implemented for specific suppliers and customers

Cross application Data Management Bridges

Data Interoperability

Common set of data management application applied to data Source and Enterprise Application

Common Data Protection mechanisms and tools are shared at company level and used in every application

Common Data Processing architecture adopted for all Enterprise Applications, both Data at Rest and Data in Motion

Common repository of Data Analytics tools is shared in the company, at disposal for any application

Common agreed repository of Data Visualisation tools is shared in the company, at disposal for any application

A common and agreed architecture for secure and sovereign Data Sharing implemented

Data Valorisation

Data Management Application used to assign a value to data

Data Protection mechanisms associated to Data Spaces increase the value of Data

Data Processing tools associated as a service to Data Sets, increasing value in the Data Space and implementing Data Economy services

Data Analytics tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services

Data Visualisation tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services

Data Sharing applications associated as a service to available Data Sets, increasing value in the Data Space and implementing Data Economy services

Data Space Pathway - Data oriented challenge dimensions

DS Pathway - Data management levels

No Data Management Culture in the company

Data stored in Enterprise Application and managed from there

Cross application Data Management Bridges

Common set of data management application applied to data Source and Enterprise Application

Data Management Application used to assign a value to data

DS Pathway - Data protection levels

No specific Data Protection measures in place regarding storage, computation and transfer of data

Each single Enterprise Application (ERP SCM PLM) is responsible for Data Protection

Secure Data Bridges between silos implemented on a case-by-case basis

Common Data Protection mechanisms and tools are shared at company level and used in every application

Data Protection mechanisms associated to Data Spaces increase the value of Data

DS Pathway - Data Processing Architecture Implementation Levels

Data not processed or processed by default procedures out of control for the company

Data processed inside Enterprise Applications (ERP SCM PLM) according to architectures and tools predefined by them

Data Processing architectures (embedded, edge, cloud) implemented for ad-hoc data bridges in Enterprise Applications

Common Data Processing architecture adopted for all Enterprise Applications, both Data at Rest and Data in Motion

Data Processing tools associated as a service to Data Sets, increasing value in the Data Space and implementing Data Economy services

DS Pathway - Data Visualisation and User Interaction

Data visualisation tools not implemented or implemented by third parties out of control of the company

Data visualisation tools embedded in Enterprise Applications on top of predefined sets of Data

Data visualisation applications are developed ad-hoc cross-silos to show data coming from different sources

Common agreed repository of Data Visualisation tools is shared in the company, at disposal for any application

Data Visualisation tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services

DS Pathway - Ecosystems for Data Sharing

A common and agreed architecture for secure and sovereign Data Sharing implemented

Data Sharing applications associated as a service to available Data Sets, increasing value in the Data Space and implementing Data Economy services

Data Sharing not implemented or implemented without any control

Data Sharing allowed from inside Enterprise Applications to a predefined value ecosystem

Data Sharing from different sources implemented for specific suppliers and customers

DS Pathway - Data Analytics Implementation Levels

Data analytics not performed or performed by third parties out of control of the company

Data Analytics procedures implemented (and replicated) from inside Enterprise Applications only

Data Analytics procedures implemented across silos in an ad-hoc fashion

Common repository of Data Analytics tools is shared in the company, at disposal for any application

Data Analytics tools associated as a service to available Data Sets, increasing their value in the Data Space and implementing Data Economy services

Circular Economy Pathway

CE Pathway - Maturity Levels

CE Pathway - Maturity Level 1 - Linearity

Any toxic substances should not be used to create products

Quality monitoring to avoid unnecessary scraps

Information technologies to gather processes data

Ad-hoc engagement of individuals, not comprehensive engagement

Contractual obligations based on regulations

Reporting and measuring only the legal responsibilities related to recycling and other environmental obligations

CE Pathway - Maturity Level 2 - Industrial Circular Economy Piloting

Material used should be the minimum amount required to respect product functionalities and design (resource sufficiency)

Production processes must require limited amount of energy

Company systems integration (e.g. ERP, MRP, PDM, PLM…)

Engagement and awareness raising, systemic empowering through champions

Code of conduct guideline for circularity/sustainability of materials.

Targets and KPIs set up for circularity pilots

CE Pathway - Maturity Level 3 - Systemic Material Management

Systematic identification of possibilities to reuse, refurbish and remanufacture

Transportation modes (reverse logistics), internal recycling of materials

Disassembly and remanufacturing enabling technologies introduced on the shop-floor

Cultural transformation and qualified people (skills)

Circularity objectives discussed at value chain level. Stakeholder engagement systematically considered.

Operative KPIs for resourcesufficiency/ decrease of waste etc.

CE Pathway - Maturity Level 4 - Circular Economy Thinking

Eco-design of products

Building industrial synergies/closed loop models

Digital platform integration enabling the interaction among value chain actors

Circular suppliers selection and value network level indicators

Capabilities to dynamic collaboration new partners ,research and innovation partnerships launched

LCA analysis over the product lifecycle, KPIs for foot print.

CE Pathway - Maturity Level 5 - Circularity

Changing business model towards product-service-systems and X as service approaches at ecosystem level

Circular systems and process at value network/ecosystem level

Collaborative business processes and workflows are used over the product life cycle

Sustainable government requirements and European Green Deal

Digital ecosystems enabling circularity, partnering with customers making use of knowledge

Circularity indicators (based on the forthcoming standard)

Circular Economy Pathway - Dimensions

Circular Economy Pathway - Products Dimension

Any toxic substances should not be used to create products

Material used should be the minimum amount required to respect product functionalities and design (resource sufficiency)

Systematic identification of possibilities to reuse, refurbish and remanufacture

Eco-design of products

Changing business model towards product-service-systems and X as service approaches at ecosystem level

Circular Economy Pathway - Process Dimension

Quality monitoring to avoid unnecessary scraps

Production processes must require limited amount of energy

Transportation modes (reverse logistics), internal recycling of materials

Building industrial synergies/closed loop models

Circular systems and process at value network/ecosystem level

Circular Economy Pathway - Platform Dimension

Information technologies to gather processes data

Company systems integration (e.g. ERP, MRP, PDM, PLM…)

Disassembly and remanufacturing enabling technologies introduced on the shop-floor

Digital platform integration enabling the interaction among value chain actors

Collaborative business processes and workflows are used over the product life cycle

Circular Economy Pathway - People Dimension

Ad-hoc engagement of individuals, not comprehensive engagement

Engagement and awareness raising, systemic empowering through champions

Cultural transformation and qualified people (skills)

Circular suppliers selection and value network level indicators

Sustainable government requirements and European Green Deal

Circular Economy Pathway - Partnership Dimension

Contractual obligations based on regulations

Code of conduct guideline for circularity/sustainability of materials.

Circularity objectives discussed at value chain level. Stakeholder engagement systematically considered.

Capabilities to dynamic collaboration new partners ,research and innovation partnerships launched

Digital ecosystems enabling circularity, partnering with customers making use of knowledge

Circular Economy Pathway - Performance Dimension

Reporting and measuring only the legal responsibilities related to recycling and other environmental obligations

Targets and KPIs set up for circularity pilots

Operative KPIs for resourcesufficiency/ decrease of waste etc.

LCA analysis over the product lifecycle, KPIs for foot print.

Circularity indicators (based on the forthcoming standard)