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Process Criticality Assessment

Criticality-based process data evaluation: a tool for instant access to process knowledge and data-driven communication

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CARBOGEN AMCIS introduces a tool called the Criticality Based Process Data Evaluation This tool leverages the concept of risk quantification to provide users with access to comprehensive process insights through both high level visualization and in depth data analysis.

  • Criticality-based process data evaluation substantially accelerates exploration of large process datasets, by directing the attention towards the most significant process risks and opportunities.
  • A criticality dashboard paired with advanced filters supports the communication of the most relevant results by visualizing the complete extent of the underlying process data
  • while instantly highlighting the most essential points to an audience that may not be familiar with the intricate details of a particular process.

To gain additional insights into the criticality concept, please refer to the following article addressing the topic in more detail.

Read the article

A Tool for Instant Access to Process Knowledge, Risk Quantification, and Data-Driven Communication

  • Is based on the criticality concept to support process understanding by highlighting the most relevant process risks in the context of the full extent of underlying data and specifications
  • Assists in the navigation of the analytical data in the context of process data and specifications
  • Automatically extracts PAR-ranges or successfully tested parameter ranges based on the available process parameter data and criticality
  • Extracts IPC purge factors and IPC criticality for assessment of potential risks based on IPC purity results
  • Warns in case of inconsistencies or gaps within the data or metadata

Added value

  • Streamlined Process Data Package
  • Process and analytical data in one place (minimal search times)
  • Advanced filters for dynamic access to specific information
  • Interactive visualization of results based on the complete extent of available data (dashboard/dynamic plots)
  • Fast Access to Relevant Information
  • Automated extraction of PAR-ranges and metrics for quality risk assessments (probability of failure, severity)
  • Data-driven Communication & Decisions
  • Decisions based on the full extent of data
  • Discussions focused on the relevant data (by criticality, severity, probability of failure)
  • In-Depth Data Exploration
  • Consistent Metadata: Merge and compare data between single experiments or across multiple projects
  • Data ready for statistical evaluations
  • Interactions between outliers to support root cause analyses

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