PROJECT LEAD: G-W Process Optimization, Inc.
PROBLEM STATEMENT: Industrial cooling tunnels are intrinsically in need of sophisticated real-time adjustment since they are long – tens of feet – open containers influenced by both the external environment and the variable products passing through them via conveyor belt. NBC is challenged with manufacturing an increasingly wide variety of bars. As a result of uncorrected temperature variability, production is adversely affected, suffering from reduced throughput, off-spec product, and resultant energy losses.
PROJECT GOAL: The goal of this project is to utilize the CESMII SM Innovation Platform to collect and contextualize this data; create and implement a data-driven algorithm that predicts product quality based on operational performance all along the enclosed seventy-foot cooling tunnel; predicts when conditions are suboptimal, threatening product integrity; and advises what interventions are needed to assure on-spec product.
TECHNICAL APPROACH: Install sensors before the tunnel to characterize the product. Create an SM Profile. Generate a predictive algorithm, Utilize the CESMII SMIP collected data to verify the newly generated G-WPO predictive model. Create dashboards for visualization. Utilize predictor to manually intervene in real-time
KEY TASKS AND MILESTONES:
- Task 1: SM Profile Development
- Task 2: Install CESMII SMIP instance and connect to data sources
- Milestone 2.4: CESMII SMIP instance
- Task 3: Configure Dashboards
- Task 4: Prediction Model
- Milestone 4.4: Integrated demonstration, utilization and impact assessment
- Task 5: Recommend best fit of project deliverables within the Industrial Food Processing Industry at large
BENEFITS: A reusable SM Profile for Cooling Tunnel and the associated Kettle and Mixer that can be configured and/or adopted by other manufacturers, technology providers and researchers for development of SM solutions.
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