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Data Analytics for the Food & Beverage Industry

Tackle critical process challenges with dataPARC's food and beverage data analytics software
Trending & Analysis

Improve your decision-making and troubleshooting capabilities.

Exploratory Analytics Tools
Production Monitoring

Monitor manufacturing production KPIs & downtime events for enterprise-wide visibility.

Real-Time Production Monitoring
Quality Control

Real-time quality control tools for food & beverage manufacturing processes.

SQC / SPC Software
OEE Tracking

Analyze, calculate, & report production loss from downtime, lost opportunities, & process slowdowns.

OEE Tracking Tools

Amalgamated Sugar: A Clear View of Plant Operations

Amalgamated Sugar, a farmer-owned cooperative, knew that in order to optimize production and reduce costs, they needed to be making better, more efficient data-driven decisions. The problem was that they didn’t have easy access to plant data at the desktop level. Their control system had very limited graphic capabilities, and it was difficult to retrieve data from the network to create trends. Also, because there was a separate home-grown system for the lab, their lab data and process data could not be overlaid or easily compared. dataPARC was contacted to help provide a clearer picture of Amalgamated’s plant data.

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"We were trying to optimize the largest facility in our company and dataPARC allowed us to overlay data - both lab and process - to break down perceptive barriers and make data-driven decisions."

Stan Case, Plant Manager - Amalgamated Sugar
Featured Case Study
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Powering Food & Beverage Analytics Solutions for 25+ Years
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Applied Solutions

Our plant visualization tools will give you the insights needed to quickly optimize food & beverage manufacturing processes.

Batch Analysis
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Dashboards & KPIs
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Grade Troubleshooting
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Production Loss Tracking & OEE
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Amalgamated Sugar Case Study

Click the link below to see how dataPARC's data visualization and historian tools helped reduce Amalgamated Sugar's production cost by enabling them to make comprehensive data-driven decisions.

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