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PLC Virtuali & Cloud: tecnologie abiitanti per la nuova automazione (Software-as-a-Service)

(in lingua inglese)

- Simple routefrom data recordingto dashboard
- Corporates goals...how?
- Requirements
- Implementation Strategies
- Use case: local and edge computing
- Use case:Cloud-based services

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SAVE ottobre 2018 Realtà Aumentata e Virtualizzazione: soluzioni tecnologiche e applicative per l’industriadel futuro

Pubblicato
da Benedetta Rampini
SAVE 2018Segui aziendaSegui




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Estratto del testo
Veronafiere 17-18 ottobre 2018 Vi aspettiamo a mcT Petrolchimico Milano, 29 novembre 2018 Cogenerazione Termotecnica Industriale Pompe di Calore 27 ottobre Cogenerazione Termotecnica Industriale Pompe di Calore Alimentare Alimentare Petrolchimico Alimentare 28 ottobre Alimentare Petrolchimico Alimentare Alimentare Petrolchimico Visione e Tracciabilit 28 ottobre Luce Energia Domotica LED Luce Energia Domotica LED Petrolchimico Alimentare Petrolchimico Petr Realt Aumentata e Virtualizzazione: soluzioni tecnologiche e applicative per l'industria del futuro Ing. Giuseppe Lettere
Automation Product Specialist PLC VIRTUALI & CLOUD: TECNOLOGIE ABILITANTI PER
LA NUOVA AUTOMAZIONE (Software-as-a-Service)
Corporates goals End customers
' Reduce production costs
' Increase product quality
' Efficient production control
' Minimize production losses

Machine builders
' Reduce machine costs
' Smart machine optimization ' Optimize production cycle times
' Optimize energy consumption ' Efficient machine maintenance ' Dedicated and predictable ' Increase machine attractivity 'Increase competitiveness !!! Corporates goals Simple route from data recording to dashboard Corporates goals Simple route from data recording to dashboard: 1. Data logging: a number of different fieldbus systems can be used to record a machine's sensor data, with use of
existing cabling and different topologies. Corporates goals Simple route from data recording to dashboard: 2. Communication: the recorded sensor data can be communicated onward on the basis of communication
standards
, which can be integrated simply and securely into existing IT infrastructures. Corporates goals Simple route from data recording to dashboard: 3. Data historicisation: the entire communication data can be stored in a long-term archive. Corporates goals Simple route from data recording to dashboard: 3. Analysis: the user views data and configures his analyses in the runtime engineering. From this configuration,
completed PLC code can be generated. Corporates goals'how' Motion Automation IPC I/O 'implementing open automation technology' Corporates goals'how' 'based on PC Control technology! Requirements Vertical: SCADA / MES / ERP with PLC 'Access to process data in PLC Horizontal: PLC with PLC 'Protocol access for data exchange I/O: PLC with Fieldbus 'Access to data profiles in shop floor devices Cloud: PLC with Cloud 'Access to Cloud for Data Logging Implementation Strategies More and detailed data ' Metadata
' Easy and secure data access
' Infinite data storage
Powerful and scalable tools ' Location-independent availability
' High usability
' High uptime and reliability
' Easy integration into infrastructure
' Use of standards Implementation Strategies 'More detailed data' ' Capture more process data
' Data transport / exchange
' Data storage
' Data analysis
' Data security Implementation Strategies Vi b ra ti on / A cou sti cs Tempe ra tur e P ow er Moni tor in g Str ai n Gau ge Oil an al ysi s C ur ren t V el oc ity P osition P ow er M ea sur in g Monitoring Algorithms Example: Condition, Power Monitoring Implementation Strategies Current solution: central server High hard-/software costs
High know-how and staff required
High maintenance effort
Poor scalability
Good security Better solution: Cloud services Low hard-/software costs
Little know-how and staff required
Low maintenance effort
Great scalability
Good security The cloud breaks the classical structure Implementation Strategies MES ERP SCADA/HMI Factory Floor (Sensors, Actors) PLCs Implementation Strategies Factory Floor (Sensors, Actors) IoT Couplers (Sensors, Actors) PLCs MES ERP SCADA/HMI Analitycs Connectivity Runtimes Better solution: Cloud services Low hard-/software costs
Little know-how and staff required
Low maintenance effort
Great scalability
Good security The cloud breaks the classical structure Implementation Strategies Better solution: Cloud services
The cloud breaks the classical structure
IaaS: Infrastructure as a Service
PaaS: Platform as a Service
SaaS: Software as a Service Use case: local and edge computing Analytics, pre-processing' Aggregated analysis "at the edge" ''1('') '(''''('')) ''2('') Aggregated analysis "in the Cloud" F(' ''''('') ) Local real-time analysis Local real-time analysis Scenario Analytics as Local Application ' Cyclic data logging
' Local data storage
' Local analyses Controller Runtime Analytics Logger Scenario Analytics as Private Cloud Application
' Use private cloud computing within your network to analyze
and aggregate data ' Communication based on IoT technology ' Cyclic data logging of different machines Private Cloud Controller Runtime Logger Message Broker Analytics Analytics Scenario Analytics as Public Cloud Application ' Use public cloud computing within your network to analyze
and aggregate data ' Communication based on IoT technology ' Cyclic data logging of different machines Public Cloud Message Broker Analytics Controller Runtime Logger Use case: Cloud-based services Cloud services MES ERP SCADA/HMI Analitycs Connectivity Runtime Cloud-based services: ' Within the IoT everyone can communicate with everyone ' 'dehierarchization' ' Important informationen will be send directly from the source ' Complex analysis is available for the smallest devices / 'things' ' Machine independent data-aggregation ' Optimized of products, processes, machines and maintenance Use case: Cloud-based services Cloud services MES ERP SCADA/HMI Analitycs Connectivity Runtime Scenario Analytics as Public or Private Cloud Application ' Cloud computing enables easy global machine analysis Public or Private Cloud Message Broker Analytics Scenario Analytics as Public or Private Cloud Application
' Streaming of the data into the own IT infrastructure for analysis Public Cloud Message Broker Analytics Scenario Analytics as Public or Private Cloud Application
Give partial data access to specialized experts: ' Machine optimization
' Support
' Condition Monitoring
' Maintenance
' ' Public Cloud Message Broker 3rd Party Analyst Machine Builder / System Integrator Analytics 3rd Party Software 27 End Customer Eng in ee rin g Dashboard End Customer System Integrator Message Broker Analytics Runtime Analytics Workbench Logger Data Agent ' Gateway Challenge ' End Customer End Customer Machine Builder Logger Data Agent / Gateway Eng in ee rin g Dashboard Engineer Analytics Runtime Analytics Workbench Message Broker Challenge ' Machine Builder New Services Machine Builder Engineering Engineer Analytics Workbench Dashboard Machine Builder End Customer VM Analytics Runtime End Customer Logger Data Agent / Gateway Message Broker Challenge ' Scenario Cloud Virtual Machine Regio-IT Smart Metering (2014)
' Decentral measurement of energy data
' Data e.g. gathered via M-Bus
' Optional local buffering of data
' Central database for historical data
' Self-configuration on startup: ' Sampling rates
' Buffer size
' Endpoint URL
' ... ' Secure connection via OPC UA
' Central website as frontend
Success story Grundfos Living Lab (2015)
' 160 connected smart apartments in a student dormitrory in Aarhus, DK ' Every apartment equipped with PC-based PLC devices ' Cyclic logging of energy data
' Approximately 3200 data points
' Data send to Cloud
' Analytics and Machine Learning
' Data access for inhabitants Success story Data Agent CarHeal Smart Repair Cabins (2017)
' Special, patented painting technique
' Fast and low-priced paint jobs
' Cabins equipped with IoT technology
' Different data send to cloud: ' Services on Microsoft Azure
' Environmental data (pollution, ...)
' Cabin status info (cycles, ...) Success story IoT and Analytics: new opportunities, new business models! Simple IoT integration:
' system-integrated with IoT
' cloud connection based on open standard protocols: ' one engineering platform
' IoT Edge device, also for retrofits


Simple data analysis:
' system-integrated with Analytics
' easy data storage and analysis
' various simple and useful algorithms
' automatic code generation
' individual analysis dashboards Benefits for end users:
' lower production costs
' optimised product quality
' optimised overview/transparency in production
' fewer machine downtimes
' increased productivity and availability
' cloud-based services (predictive maintenance)

Benefits for machine builders:
' lower machine costs
' simple and fast diagnosis: predictive maintenance/ ' machine/process optimisation
' new business models Validation Grazie per l'attenzione


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