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BDVe Webinar Series - Politecnico di Milano - Big Data in the Smart Manufacturing Industry

Sergio Gusmeroli from the Politecnico di Milano

June 18

The BDVA Smart Manufacturing Industry group is going to present in this webinar, challenges and opportunities related to the adoption of Big Data-driven solutions in the manufacturing domain. Following the grand scenarios defined by EFFRA (Smart Factory, Smart Supply Chain, Smart Product), the discussion will make use of real cases and pilots from research projects to elaborate on the topic.

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BDVe Webinar Series - Politecnico di Milano - Big Data in the Smart Manufacturing Industry

  1. 1. The role of Data Sovereignty in European Commission communication “Towards a common European Data Space” Sergio Gusmeroli, Politecnico di Milano
  2. 2. 2 The Regulatory Context: Sharing Private Sector Data Models to B2B Data Exchange a) An Open Data approach: The data in question are made available by the data supplier to an in principle open range of (re-)users with as few restrictions as possible and against either no or very limited remuneration. b) Data monetization on a data marketplace: Data monetization or trading can take place through a data marketplace as an intermediary on the basis of bilateral contracts against remuneration. Suitable when either (1) there are limited risks of illicit use of the data in question, (2) the data supplier has grounds to trusts the (re-)user, or (3) the data supplier has technical mechanisms to prevent or identify illicit use. c) Data exchange in a closed platform: Data exchange may take place in a closed platform, either set up by one core player in a data sharing environment or by an independent intermediary. The data in this case may be supplied against monetary remuneration or against added-value services, provided e.g. inside the platform.
  3. 3. Open Data: the vision of a FIWARE for INDUSTRY DataLab I4.0LAB @ POLIMI Open Data in Manufacturing a) Open Data Models for SI entities (such as robots, AGVs, machines, conveyors) with Data in Motion and Data at Rest b) Network of open Didactic Factories producing and sharing their data thanks to standard protocols and data formats (e.g. OPC-UA, MQTT, ROS, AQMP). c) Data Transformation techniques for non- public Data such as Aggregation, Filtering, Anonymization, Pseudonymiz. d) One stop shop for search-discovery- selection, Distributed Repositories for Data Storage (iSpaces) e) Ecosystem of Innovators testing and experimenting their solutions on open data (Data-AI Community)
  4. 4. Data Marketplaces: FIWARE enabled Data Platform Access to Competencies COLLABORATION PLATFORM for DIGITAL INNOVATION HUBS Ideation Platform Wikis & Fora Search Engine Human Skills CV Manager Partner Search and Selection Access to Technology IT Assets & OSS Catalogue Reference Architectures Applications Marketplace Access to Experiments Industrial Experiments Best Practice Success Story KPIs Lessons Learned Access to Knowledge Maturity Model Training & Formation Brownfield Integration Access to Market Ideas Incubation Business Acceleration Capital & Funding Tangible Assets Manager Living Lab Innovation
  5. 5. Trusted B2B Data Exchange: Sovereignty on Access Broker App Store Data Source Connector Data Provider Data Consumer Dataset(s) transferred from Provider to Consumer Metadata Description of Datasets/Provider/Consumer Application for specific data manipulation Data exchange (active) App download Metadata exchange Data exchange (inactive) Connector Data Sink Connector Meta Meta Meta Meta Meta … App Data Meta App App App App Data Meta
  6. 6. Trusted B2B Data Sharing: Sovereignty on Usage Data Models Ontologies
  7. 7. IDSA-BDVA Towards a EU Data Sharing Space • Create the conditions for the development of a trusted European data sharing framework • Incorporate data sharing at the core of the data lifecycle to enable greater access to data. • Provide supportive measures for European businesses to safely embrace new technologies, practices and policies. • Assemble a European-wide digital skills strategy to equip the workforce for the new data economy.
  8. 8. @boost4_0 /groups/12075988
  9. 9. Big Data Value Spaces for Competitiveness of European Connected Smart Factories 4.0 G. Petrali (WHIR) Whirlpool Use Case
  10. 10. TIER 1 SUPPLY BASE TIER 1 SUPPLY BASE Raw material Change in Tier 2 Wrong Instructions SPARE PART CENTER Parts delivery PREDICTION TOOL Prod. Orders Request and wharehouse management suggestion Planning and Quality suggestion Warning alert, training and medium term planning PRODUCTION FACTORY Whirlpool Pilot : Cause and Effect Diagram
  11. 11. Whirlpool Pilot Architecture STATISTICAL DEMAND FORECAST GENERATION Spare Parts Consumption History INVENTORY & SUPPLY PLAN GENERATION PROCUREMENT PRODUCTION DISTRIBUTION AS IS NEW PREDICTION TOOL (FABRIC CARE) (in parallel with the current statistical demand forecast generation) Pre-elaboration 1: Factory Test Data Pre-elaboration 2: Sell-In / Demand Forecast Pre-elaboration 3: Service Order Confirmations Pre-elaboration 4: Smart Appliances Output 1 : Spare Parts Demand Forecast in Qty Output 2 : Spare Parts Demand Forecast in # of Order Lines Output 3 : Monitoring Tools & Demand Forecast Analysis Output 4 : Quality Reports for : - Factory and Product Engineers - Market and Service Partners Training - Smart Appliance Predictive Maintenance Approach TO BE Pre-elaboration 5: Service Incident Rate
  12. 12. From PoC to the Large Scale Data extractors ready and deployed Large scale data available and loaded Forecasting models tuning New forecasting reports and price analysis Operational KPIs monitoring activation Environment setup and activation for the large scale Forecasting analysis from monthly to weekly view TeraLab Big Data environment certification and activation KPIs calculation: demand forecast error, human effort for planning Integration with other information that can influence the forecasting, extention to other EMEA countries
  13. 13. BC expansion: IDS allow extending the benefit of forecasting tool to all Value Chain TIER 1 SUPPLY BASE Third party Field Service
  14. 14. @boost4_0 /groups/12075988