From High-Risk to High-Yield: AI Vision in Animal Feed Manufacturing

***Client name and identifying details have been anonymized for confidentiality.

Subject: AFM Feed Mill (A large-scale animal feed production facility)

Industry: Animal Feed Manufacturing

The Challenges It Faces

AFM Feed Mill faced significant challenges rooted in manual processes and critical gaps in real-time safety monitoring. These gaps prevented them from optimizing production flow and adequately mitigate severe environmental risks inherent to feed production. The primary pain points included:

1. Inefficient Logistics and Inaccurate Inventory at the Weighbridge: The facility’s critical choke point was the weighbridge, where two distinct workflows caused delays and data inconsistencies:

• Standardized Vehicles: Large trucks and containers with clear license plates but manual recording and cross-referencing of weight data.
• Non-Standardized Vehicles: Tractors and farm vehicles without license plates were processed using paper tickets, where random, handwritten codes and weight measurements were noted. Cameras could read the weight display but could not identify the vehicle, making real-time discrepancy reporting impossible.

2. High-Risk Methane (CH₄) Zone Safety: A core area of the plant contained high concentrations of Methane (CH4), posing a severe, explosive risk. This threat was compounded by the finished product warehouse, which contained combustible materials, located nearby. Critically, the factory lacked an instant, real-time warning system to prevent ignition events.

3. Sub-Optimal Worker Supervision in Automated Areas: The control area for automated machinery required continuous monitoring of gauges and indices, with human workers needing to check data every 5, 10, or 15 minutes. The management had no real-time to verify worker presence or alert supervisors when a critical post was left unattended, creating a gap in oversight and potential quality control failures.

4. Production Loss and Inaccurate Counting on the Conveyor: The product finishing area struggled with accurate inventory tracking due to movement complexity:

• Counting & Differentiation: Difficulty accurately counting finished product bags leaving the non-fixed conveyor and differentiating between product types (e.g., starter, grower, finisher).

The Solutions We Deliver

CXVIEW deployed its AI Video Analytics Platform combined with Real-time Intelligence to establish a digital nerve center for the facility, replacing manual checklists and delayed reporting with instant, actionable insights delivered via the All-in-one Intelligence Dashboard.

1. Supply Chain Traceability and Logistics Optimization: This solution digitized the entire inbound/outbound process, ensuring material accountability and speed at the first entry point.

• Intelligent Vehicle Identification: The AI Video Analytics model was trained to recognize non-plated vehicles (farm tractors) based on unique visual characteristics (Vehicle Recognition), while also utilizing OCR (Optical Character Recognition) to read license plates and the numerals displayed on the digital weigh scale screen.
• Real-time Discrepancy Alerting: All data is streamed directly to the Dashboard, immediately alerting to any mismatch between vehicle ID, cargo type, and weight, preventing fraud or errors during the weighing process.

2. Zero-Tolerance Behavioral and Environmental Safety: Our AI Video Analytics & real-time intelligence provides proactive safety monitoring in high-risk zones, eliminating reliance on slow-reacting sensors or manual reporting.

3. Precision Production and Inventory Integrity: The system provides real-time accountability for every product unit, AI Video Analytics precisely counts the number of bags and simultaneously classifies them by product type as they exit the conveyor. A secondary AI camera detects bags falling off the conveyor, automatically triggering instantaneous inventory deduction and identifying the lost product type, adjusting final stock quantity in real-time on the Intelligence Dashboard.

4. Critical Process Integrity and Oversight: AI Video Analytics (Loitering & Attendance) monitors the automated control rooms. If a worker is absent longer than the defined time window (e.g., 5 minutes), the Dashboard immediately alerts management, ensuring critical index checks are always performed.

The Results: Enhanced Safety, Traceability, and ROI via Real-time Intelligence

By moving from manual and anecdotal monitoring to CXVIEW’s data-driven platform, AFM Feed Mill achieved significant, measurable improvements in all critical areas, with management making informed decisions based on Real-time Intelligence.

• 100% Logistics Traceability and Loss Reduction
• Zero-Tolerance Safety Environment
• Guaranteed Process Oversight
• Enhanced Operational Discipline and Workforce Awareness

CXVIEW’s comprehensive platform, powered by AI Video Analytics and delivering Real-time Intelligence via the All-in-one Intelligence Dashboard, transformed AFM Feed Mill’s operations from reactive and manual to proactive and data centric.

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CXVIEW – WHERE VISION DRIVE IMPACTS

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