Traceability

In any discrete manufacturing or assembly plant, product traceability is a key requirement to track all the relevant attributes and components that make up a product. This helps in process improvement, better quality, regulation compliance, defect resolution and brand integrity. Persistent’s Traceability application enables automated capture, storage, management and analysis of data collected directly from the various manufacturing and assembly systems during the different stages of production. The IoT-enabled application architecture is based on recent technology advances in Industrial IoT and data analytics that enables real-time and error-free capture of data directly from the SCADA systems and PLCS, while supporting high scalability and flexibility in its functionality.

The application can support a wide range of potential use cases in the following areas:

  • Production: Real time tracking and visualization of product and production tools with component-wise traceability. This enhances quality of products and results in better utilization of the assembly line.
  • Maintenance, Supply Chain & Logistics: Real-time visibility of raw material flow, inventory monitoring and optimization to deliver operational efficiency.
  • Sales & Customer Experience: End to end tracking of product availability, proactive monitoring, product recalls and reverse logistics to deliver an enhanced customer experience.

Key Functionality and Features

  • Demonstrated integration with a variety of manufacturing controllers such as PLCs and CNCs.
  • Captures product attributes digitally from the originating source at each step of the assembly line.
  • Provides a traceability report including all components for each assembled product providing details about the date and location of product assembly, batch details of components used, product attributes and worker details.
  • Detailed effort tracking & time spent by each worker, including re-works and quality fixes • Supports different levels of authorizations and workflows.
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