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This page aims to translate the functional requirements into architecture tangible elements creating a engineering value perspective on the initiative - to assess business capabilities relevance versus architecture complexity.


Table of Contents

Architecture Requirements Assessment

Quality AttributeRequirement - Architecture ConcernsArchitectural ComplexityBusiness Criticality/RelevanceBusiness Requirement Item
InteroperabilityHow "AI system" gather info from public & internal sources for scientists real-time evaluation?

Status
colourRed
titleHIGH

Status
colourRed
titleHIGH

Understanding Experimental Requirements and Information Collection
Usability

How "AI system" filter and

´displays´ complex

displays complex data structure and diagrams?

Status
colourBlue
titleLOW

Status
colourRed
titleHIGH

Molecular Modeling and Simulation
UsabilityHow "AI system" supports/makes proposals to scientists on molecular modeling and simulation?

Status
colourYellow
titlemedium

Status
colourRed
titleHIGH

Molecular Modeling and Simulation
UsabilityHow "AI System" monitors digital reactor and formulation workstation processes to ensure accuracy/consistency of sample preparation?

Status
colourRed
titleHIGH

Status
colourRed
titleHIGH

Molecular Modeling and Simulation
ConsistencyHow "AI System" ensures accuracy/consistency of sample preparation?

Status
colourYellow
titlemedium

Status
colourBlue
titleLOW

Execution of Experimental Plan
UsabilityHow "scientists" monitor progress of digital reactor and formulation process in real time?
Performance

Status
colourBlue
titleLOW

Status
colourBlue
titleLOW

Execution of Experimental Plan
InteroperabilityHow "Central Control System" capture instrument data and promote it to Data Analysis System?

Status
colourYellow
titlemedium

Status
colourRed
titleHIGH

Sample Analysis and Data Processing
InteroperabilityHow "Central Control System" onboard/integrate new instruments? 

Status
colourBlue
titleLOW

Status
colourYellow
titlemedium

Sample Analysis and Data Processing
ConsistencyHow can "AI System" make recommendations for the experimental scheme to the scientists based on historical data and current results?

Status
colourRed
titleHIGH

Status
colourRed
titleHIGH

Experimental Optimization and Iteration
InteroperabilityWhat types of sensors "AI System" will connect and how it will monitor Environment and instrument parameters in real-time to schedule maintenance (to reduce downtime)?

Status
colourYellow
titlemedium

Status
colourBlue
titleLOW

Intelligent Management and Maintenance
SafetyHow "AI System" automatically checks existing group safety regulations/procedures and evaluates the safety of new instrument/processes/Management of Change to recommend additional safety monitoring parameters?

Status
colourYellow
titlemedium

Status
colourRed
titleHIGH

Safety and Compliance
UsabilityHow "AI System" allows scientists to access experiments database for evaluation?

Status
colourBlue
titleLOW

Status
colourBlue
titleLOW

Knowledge Management and Collaborative Work
UsabilityHow "Virtual Assistant" provides suggestions on best practices to scientists?

Status
colourBlue
titleLOW

Status
colourRed
titleHIGH

Safety and Compliance
Usability

How "AI System" enhances team collaboration, allows sharing data and offers personalized collaboration tips (recommendations)?

Status
colourBlue
titleLOW

Status
colourBlue
titleLOW

Knowledge Management and Collaborative Work
Usability

How "Reporting - Visualization System" keeps track on the regular work-flow to create analysis?

Status
colourBlue
titleLOW

Status
colourYellow
titlemedium

Automatic Report Generation and Environmental Control
Usability

How "AI System" automatically adjusts parameters based on experimental needs for optimal conditions?

Status
colourYellow
titlemedium

Status
colourBlue
titleLOW

Intelligent Management and Maintenance
Usability

How "Reporting - Visualization System" allows multi-project management?

Status
colourBlue
titleLOW

Status
colourYellow
titlemedium

Visualization System and Resource Scheduling
Interoperability

How "Voice User Interface (VUI)" allows personas in the lab to interact with Instruments and manage experiments?

Status
colourRed
titleHIGH

Status
colourBlue
titleLOW

Voice User Interface

Reference:

Google Drive Live Link
urlhttps://docs.google.com/spreadsheets/d/1LtjYpOJwncEfQGHTMPjn0brspZhHkBTtmNfPqVRk9os/edit?gid=295951970#gid=295951970

Architectural Concerns


Image Added

  • Wet-Lab
    1. The "Big Data Hub" should be compliant with CyberSec OT/IT constraints.
    2. The solution must provide extensible and resilient interfaces mechanism for integrating with Syensqo LIMS, ELN and AI systems.
    3. Foundational or Pre-trained AI/LLM models consumed by Edge or Regular computing must be validated from the Syensqo AI standpoint and CyberSec constraints (+AI Risk).
  1. Same applies for the fine-tuning processes. 
    1.   
    2. Local network capacity must be adequately dimensioned to support the throughput of the number of sensors and their potentially complex and large data types capturing.
  • Dry-Lab
    1. Interoperability between systems (Machine Learning, Modeling-Simulation and LIMS/ELN) becomes critical to achieve efficiently the target seamless workflow. 
    2. Data integration should be taken into consideration to ensure the lineage and data consistency across different systems where users will perform their activities.
    3. Computer power is also critical for fine-tunning, training and real-time suggestions (here also low-latency network is a sensitive aspect to take into account).

→ It is also a concern to consider that eventually the solution used for Shanghai may not be generalizable or reusable in other regions, outside of China, due to aspects related to:

  1. Contract and legal for having the same vendors
  2. Interoperability with Syensqo Application Platform for experiments (LIMS, ELN)
  3. Data classification and data exchanges between regions

Utility Tree

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The value engineering work on the user requirements allows to create such mind-map diagram so to visually capture the architectural significant requirement and its business criticality and complexity to be implementend.

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Personas - Profiles

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  • Syensqo Lab Expert
  • AI System
  • Scientists
  • Researchers
  • Lab Technicians
  • Virtual Assistant
  • Voice User Interface (VUI)

Environments

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  • Wet Lab
  • Dry Lab
  • OnPrem
  • Cloud Infra

Components

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- Building Blocks   

  • AI System
  • Digital Reactor
  • Formulation Workstation
  • Analytical Instruments
  • Data Analysis System
  • Central Control System
  • Reporting - Visualization System
  • Voice User Interface (VUI)

High Level Design Architecture

There are three different views to describe the laboratory environment and the application/infrastructure architecture to accomplish the business needs.  

  • Shanghai Lab Setup


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  • High Level Design (application and OT-IT network architecture: IEC 62443 - zones & conduits)

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  • High Level Design (application, OT/IT + workflow context)


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References

Functional Requirements

Google Drive Live Link
urlhttps://docs.google.com/spreadsheets/d/1LtjYpOJwncEfQGHTMPjn0brspZhHkBTtmNfPqVRk9os/edit?gid=295951970#gid=295951970

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