Product Traceability






Product Traceability

Example of a traceability flowIn the pharmaceutical industry, many implemented processes are both automated and continuous.  The types of manufacturing involve complex sequences of steps and operations as raw materials move through each step.  After the process is completed final drug quality will be determined by the sometimes complex interactions between upstream and downstream processing, raw materials, media, and instrumentation.  In order to perform meaningful reporting, process monitoring, root cause analyses, and process optimization based on data collected at each step, it is necessary to manage views across processing steps, and across time.

Measurements collected at different steps must be related to key process parameters.  Interactions between process parameters at different stages, and their effect on final product quality, need to be assessed.  Clusters and batches of materials that shared common processing steps, tools and equipment need to be identified.  Process data at every stage in the process need to be aggregated.  Moreover, personnel responsible for monitoring these processes need to be able to link together diverse data sources and data historians, and integrate data from a variety of sources.

High quality manufacturing processes require that the quality assurance professionals and managers have access to the Hierarchical Process Cube that contains all information about how the material moved through the sequence of steps, so that meaningful monitoring, qc-charting, reporting, and root cause and other analyses can be performed.   The ability to have a complete view of such data is a required prerequisite for modern PAT and QbD initiatives and approaches.  Also, maintaining the records describing the complete manufacturing process that accurately reflects the process itself is mandated by regulatory reporting requirements in many industries.

StatSoft’s Product Traceability solution for the manufacturing industry empowers engineers and analysts to select the relevant process and easily gain access to the necessary data, and to analyze the movement of materials and batches through the production process.

Screenshot of product setupScreenshot of the process data explorer

STATISTICA presents the data in the most relevant and meaningful way, handling the connections to the existing data historians, LIMS, and other systems, and aggregating and aligning discrete and continuous data to prepare it for review and analyses.  Engineers simply interact with STATISTICA in a natural way, following exactly the sequence of steps defining the complete process.


  • Leading-Edge Predictive Analytics: Sophisticated algorithms to build models that provide the highest accuracy for product traceability.
  • Enterprise-Wide Solution: A multi-user, role-based, secure STATISTICA Enterprise platform allows for a truly collaborative environment to build, test, and deploy the best possible models for analytics.
  • Integrated Workflow: STATISTICA Decisioning Platform provides a streamlined workflow for powerful, rules-based predictive analytics where business rules and industry regulations are used in conjunction with advanced analytics to build the best models.
  • Open architecture and easiest to integrate and connect. STATISTICA is built with modern software tools and compliant with modern software standards; it is the easiest to integrate with existing IT assets, databases, LIMS systems, and data entry and gathering devices and tools, as well as existing reporting tools.

About statsoftsa

StatSoft, Inc. was founded in 1984 and is now one of the largest global providers of analytic software worldwide. StatSoft is also the largest manufacturer of enterprise-wide quality control and improvement software systems in the world, and the only company capable of supporting its QC products worldwide, with wholly owned subsidiaries in all major markets (StatSoft has 23 full-service offices, on all continents), and its software is available in more than 10 languages.

Posted on October 2, 2013, in Uncategorized. Bookmark the permalink. Leave a comment.

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