Operational Efficiencies & Traceability Improvement Initiative

Project Lead: Tyson Foods
Partners: ThinkIQ

Member % Cost Share: 50%
CESMII % Cost Share: 50%
Duration: 6 Months

Problem Statement

Operational Efficiencies & Product Innovation Traceability

Project Goal

The stated goals of Tyson Foods is to enhance yields in the Hanceville, AL rendering facility while optimizing available material streams to increase processing throughput and lower overall production costs per unit, while maintaining finished goods quality. The intent of this project is to provide the tools and analytics to enable Tyson to make smart manufacturing decisions based on facts in context of material flows and manufacturing operations. 

The project will leverage a baseline measurement for a fixed time period for each originating facility metrics, re: protein, moisture, and other attributes, such as: product weights (truck weights) product weighted into Hanceville, loss from the Hanceville processing facility, as Tyson pays suppliers for product, not additives, re: water, etc.

Technical Approach

This project will span 4 months and consist of 6 major tasks:

  • Governance
  • Cloud-based Infrastructure
  • Site Configuration
  • Reporting and Analysis
  • Empowerment

Deliverables/Outcomes/SM Marketplace

  • Complete platform setup including installing connectors to plant data sources and validating data integrity
  • Complete configuration of the SMIP and ThinkIQ system functionality
  • SMIP installed, configured and tested
  • Smart Manufacturing Profile for Rendering Manufacturing Operations developed and documented
  • Yield reporting and analysis functionality designed, implemented, and tested
  • Food processing equipment SM profiles
  • Energy consumption models

    Potential Impact

    This project provides validation of the CESMII Platform in a protein-based food processing environment at a line level to demonstrate viable operations, connected to the process w/ timely time-to-value based on variance reduction, yield, and throughput increases, as well as, creating profiles pertinent to the equipment (equipment types).


    The resulting model created with this project will create profiles pertinent to the equipment (equipment types) and is strongly aligned with CESMII’s mission.

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