Periodic Reporting for period 2 - DIGIMAN (DIGItal MAterials CharacterisatioN proof-of-process auto assembly)
Período documentado: 2018-07-01 hasta 2020-06-30
DIGIMAN’s aim was to develop a blueprint design for next generation fully automated cell assembly & testing of Intelligent Energy’s air-cooled fuel cell stacks. The programme outcomes have demonstrated operational and supply chain cost reductions via seamless integration of digital manufacturing techniques (Industry 4.0 compliant) and advanced manufacturing technology, with a fully automated uplift to existing engineered assembly processes. The blueprint design allows build-to-print machine readiness with scalable production capacity to more than 50,000 fuel cell stacks per annum by 2020. The project has raised the manufacturing readiness level (MRL4 to MRL6) by introducing enhanced design for assembly, automated processes for assembly, inspection, and test, coupled with materials acceptance standards.
DIGIMAN’s key outputs have been:
• creation of a robust platform for PEM fuel cell stack production
• establishment of best practice requirements for automotive fuel cell stack production
• demonstration of operational and supply chain cost reduction
• to offer seamless integration of digital manufacturing techniques with advanced automated production technology
• to enable build-to-print machine configuration with ready to scale production capacity
• to supply a capability roadmap to meet requirement of more than 50,000 fuel cell stacks per annum by 2020
• Digitization of GDL surface homogeneity and export of machine-readable quality protocol.
• Case Study for line-side converting of GDL roll-stock and sorting for ready-to-use GDL sheets.
Main KPIs
• AC64 Stack weight: 2.9 kg
• AC64 Stack volume: 2.85 l
• AC64 Stack capacity: 2.1 s
DIGIMAN’s key outputs have been:
• creation of a robust platform for PEM fuel cell stack production
• establishment of best practice requirements for automotive fuel cell stack production
• demonstration of operational and supply chain cost reduction
• to offer seamless integration of digital manufacturing techniques with advanced automated production technology
• to enable build-to-print machine configuration with ready to scale production capacity
• to supply a capability roadmap to meet requirement of more than 50,000 fuel cell stacks per annum by 2020
• Digitization of GDL surface homogeneity and export of machine-readable quality protocol.
• Case Study for line-side converting of GDL roll-stock and sorting for ready-to-use GDL sheets.
Main KPIs
• AC64 Stack weight: 2.9 kg
• AC64 Stack volume: 2.85 l
• AC64 Stack capacity: 2.1 s
DIGIMAN has met all its key objectives including:
• Delivery of a blueprint design for a fully automated, build-to-print ready, production line capable of producing over 50 thousand stacks per annum.
• Validation of the build-to-print readiness of the blueprint design to the mandatory MRL6 – the EU’s definition of pre-production readiness – and one stage prior to pilot production.
• Development of a digital cause and effects model and tool constructs which was used to analyse the data which verified MRL6 attainment of the full auto stack assembly processes via the PoP demonstrator
• Validation of the cell assembly cycle time KPI of less than 5 seconds, meaning that the uplift to full automation from IE’s incumbent semi-automation has achieved a five-fold improvement.
• Validation via in–situ small and large stack test activities that the MRL advancement from WP3, WP4 and WP5, that any changes in cell architecture, materials characterisation and assembly / test processes have not been detrimental to the AC64’s performance, meeting KPI of 0.7 A/cm2 @ 0.7V BoL (Beginning of Life):
The KPIs for fully automated stack assembly and test were generated. Work was performed on the methods to reduce the duration of handover tests and conditioning cycles. Candidate automated handling systems to suit each stack transfer approach have been identified.
Non-destructive thermal diffusivity scanning methods were found to be highly sensitive to heterogeneities in GDLs materials. The digital quality control of GDLs has progressed with roll good optimization and digitalization for the digital mapping of ocular defects (via camera-based inspection) operational within FPM’s production line and structural scanning of structural heterogeneities (via thermal scan) qualified to MRL6. A case study was performed that resulted in the requirements necessary for a line-side converting step capable of singulating pre-screened GDL to deliver ready-to-use GDL sheets.
To correlate defects and performance, GDL samples with and without defects were generated, properties such as thickness, permeability, resistivity, and thermal diffusivity were measured, and in situ tested within stack. Results indicate a particular sensitivity of AC64 performance to the heterogeneities which impair in-plane permeability.
Based on IE’s operational experience, key technical requirements for the automation uplift were established for the Blueprint design and have been validated via the PoP Demonstrator.
Data links/harvesting capability has been established and fully validated. For data from nonautomated processes IE has developed a web-based application which allows the manual data input (by bespoke configured tablets) and is currently being trailed by said expert staff.
• Delivery of a blueprint design for a fully automated, build-to-print ready, production line capable of producing over 50 thousand stacks per annum.
• Validation of the build-to-print readiness of the blueprint design to the mandatory MRL6 – the EU’s definition of pre-production readiness – and one stage prior to pilot production.
• Development of a digital cause and effects model and tool constructs which was used to analyse the data which verified MRL6 attainment of the full auto stack assembly processes via the PoP demonstrator
• Validation of the cell assembly cycle time KPI of less than 5 seconds, meaning that the uplift to full automation from IE’s incumbent semi-automation has achieved a five-fold improvement.
• Validation via in–situ small and large stack test activities that the MRL advancement from WP3, WP4 and WP5, that any changes in cell architecture, materials characterisation and assembly / test processes have not been detrimental to the AC64’s performance, meeting KPI of 0.7 A/cm2 @ 0.7V BoL (Beginning of Life):
The KPIs for fully automated stack assembly and test were generated. Work was performed on the methods to reduce the duration of handover tests and conditioning cycles. Candidate automated handling systems to suit each stack transfer approach have been identified.
Non-destructive thermal diffusivity scanning methods were found to be highly sensitive to heterogeneities in GDLs materials. The digital quality control of GDLs has progressed with roll good optimization and digitalization for the digital mapping of ocular defects (via camera-based inspection) operational within FPM’s production line and structural scanning of structural heterogeneities (via thermal scan) qualified to MRL6. A case study was performed that resulted in the requirements necessary for a line-side converting step capable of singulating pre-screened GDL to deliver ready-to-use GDL sheets.
To correlate defects and performance, GDL samples with and without defects were generated, properties such as thickness, permeability, resistivity, and thermal diffusivity were measured, and in situ tested within stack. Results indicate a particular sensitivity of AC64 performance to the heterogeneities which impair in-plane permeability.
Based on IE’s operational experience, key technical requirements for the automation uplift were established for the Blueprint design and have been validated via the PoP Demonstrator.
Data links/harvesting capability has been established and fully validated. For data from nonautomated processes IE has developed a web-based application which allows the manual data input (by bespoke configured tablets) and is currently being trailed by said expert staff.
Progress beyond SoA
• Innovative floatation methods for pick and place handling and mechanical pre-alignment of none rigid and (90%) porous materials such as GDLs have been developed with untethered vacuum carriers capable of smart ‘fire and forget’ motion and positioning control allowing direct lamination of liner mounted adhesive film eliminating gasket-to-gasket or plate-to-plate pitch errors.
• Automated defect inspection resulting in a machine-readable digital QC protocol have been developed to guide the singulation and sorting processes for the GDL.
• PoP Demo design and development activities have been completed for Static and Dynamic Process Modules; with the equipment installed and commissioned, dry cycle tested and MRL6 validated. Discrete event simulation work involving PoP demo modules and track, fuel cell test, stack assembly and test. PoP production relevant environment facility established at IE with cell, stack build and validation testing programme leading to the MRL6 validation.
• Via a Digiman developed digital process engineering methodology, virtual engineering simulations and discrete event simulations have delivered a digital twin of a blueprint design which is ‘build to print’ ready. A fully cost proposal via a conventional procured approach has been elicited and is 50% less costly in terms of capital expenditure and 66% more efficient in terms operational costs the Blueprint design.
• To support Digiman initiatives in digital QC a Digital Defect Protocol has been developed The protocol provide the defect classifications and location within the roll-stock to allow “singulation” and “sorting” via the concept of lineside conversion A case study with provisional trials identified an Italian supplier capable of engineering a line side converting and sorting module.
• The innovation floatation handling and untethered vacuum clamping methods will offer assemble-ability for light-weighted fuel cell stacks and future ultra-light weight materials. Incorporated automotive best practices offer drop-in compatible production lines or direct ship to line delivery of fuel cell stacks and systems. The developed schemas for cause data / effects data harvesting via emerging Industry 4.0 compatible methods will enable mining of ‘big data’, from which, the to be developed digital cause & effects modelling tool will be able to detect previously undetectable data trends and unforeseen causations of fuel cell stack performance and durability degradation.
• Data from first product stack at handover analysed via digital C&E tools and techniques. Regression analysis suggested correlation between GDL position and in-situ cell performance. A plan for more in-depth study to confirm this data was curtailed by COVID-19 and supply chain issues, but, the developed data mining and digital cause and effects analysis techniques will allow this to be continued after the project completes and lockdown restrictions are lifted.
• Innovative floatation methods for pick and place handling and mechanical pre-alignment of none rigid and (90%) porous materials such as GDLs have been developed with untethered vacuum carriers capable of smart ‘fire and forget’ motion and positioning control allowing direct lamination of liner mounted adhesive film eliminating gasket-to-gasket or plate-to-plate pitch errors.
• Automated defect inspection resulting in a machine-readable digital QC protocol have been developed to guide the singulation and sorting processes for the GDL.
• PoP Demo design and development activities have been completed for Static and Dynamic Process Modules; with the equipment installed and commissioned, dry cycle tested and MRL6 validated. Discrete event simulation work involving PoP demo modules and track, fuel cell test, stack assembly and test. PoP production relevant environment facility established at IE with cell, stack build and validation testing programme leading to the MRL6 validation.
• Via a Digiman developed digital process engineering methodology, virtual engineering simulations and discrete event simulations have delivered a digital twin of a blueprint design which is ‘build to print’ ready. A fully cost proposal via a conventional procured approach has been elicited and is 50% less costly in terms of capital expenditure and 66% more efficient in terms operational costs the Blueprint design.
• To support Digiman initiatives in digital QC a Digital Defect Protocol has been developed The protocol provide the defect classifications and location within the roll-stock to allow “singulation” and “sorting” via the concept of lineside conversion A case study with provisional trials identified an Italian supplier capable of engineering a line side converting and sorting module.
• The innovation floatation handling and untethered vacuum clamping methods will offer assemble-ability for light-weighted fuel cell stacks and future ultra-light weight materials. Incorporated automotive best practices offer drop-in compatible production lines or direct ship to line delivery of fuel cell stacks and systems. The developed schemas for cause data / effects data harvesting via emerging Industry 4.0 compatible methods will enable mining of ‘big data’, from which, the to be developed digital cause & effects modelling tool will be able to detect previously undetectable data trends and unforeseen causations of fuel cell stack performance and durability degradation.
• Data from first product stack at handover analysed via digital C&E tools and techniques. Regression analysis suggested correlation between GDL position and in-situ cell performance. A plan for more in-depth study to confirm this data was curtailed by COVID-19 and supply chain issues, but, the developed data mining and digital cause and effects analysis techniques will allow this to be continued after the project completes and lockdown restrictions are lifted.