Name

Description

WS 1

System and Data Architecture (IT/OT)

●    Scalable, modular and phase appropriate data architecture: data flows from sensor to manufacturing network to secured IoT cloud solution

●   Consideration for data integration and data quality

●    Integration of sensors to comply with plug and produce

●    Establishment of bi-directional communication between sensors and information system

WS 2

Operations and workflows (Manufacturing and Analytics)

●    Revise standard operating procedures from static to dynamic approach

●    Design automated workflows for batch monitoring, and real-time release (e.g. release by exception)

●    Using No-Code and Low-Code Platform to implement digital workflows and EBR data collection (Data created by workstream 3 via OPC UA)

●    Control recipe and batch record optimization – where to automate and where not

●    Stepwise implementation from classical eBR to dynamic recipe management

WS 3

Shopfloor integration (Sensors and Equipment)

●    Identification of optimal data standards for sensors and equipment to enable plug and produce

●    Design of structure for universal data availability and connectivity of IoT devices

●    Using Siemens Integration Platform to establish OPC UA Connectivity to Equipment

●    MSI Interface connection (message-based communication)

●    Admin shell framework and concept

WS 4

Quality and validation

●    Validation strategy – beyond classical CSV (Concept and Sample implementation for computer system assurance to self-validating systems(?)) 

●    Design and establishment novel workflows for (real-time) e-validation & risk assessment of process (CSA)

●    Closed loop optimization framework aligned with the future quality requirements and regulatory needs within the business environment (real-time-release and process change)

WS 5

Simulation and Data analytics

●    Simulation of end-to-end quality and manufacturing outputs (for prediction of certificate of analysis)

●    Evaluate sophisticated modeling approaches using sensor live data and mechanistic process models for prediction of final product parameters – yield & COGS & sustainability

●    LES laboratory execution system feed with information àvirtual certificate of analysis

●    Process & analyze data out of the different work-streams

●    Visualization of real-time collected data