A Simulation-Based Approach for Evaluating the Effectiveness of Robotic Automation Systems in HMR Product Loading

Area of Science:

• Food Science and Technology
• Industrial Engineering
• Robotics and Automation

Background:

• Increasing demand for safe, high-quality Home Meal Replacement (HMR) products necessitates enhanced food production processes.
• Robotic automation offers potential efficiency gains but faces accessibility challenges for small and medium-sized enterprises (SMEs) due to high costs and risks.

Purpose of the Study:

• To evaluate the feasibility and impact of robotic automation on HMR production through a simulation-based approach.
• To identify bottlenecks, optimize worker utilization, and quantify throughput improvements in different production scenarios.

Main Methods:

• Modeling two distinct HMR production cases (large-scale and order-based) using simulation software.
• Comparing simulated results with actual implementation data to validate the simulation approach.
• Assessing the operational requirements and effectiveness of robotic systems for SME environments.

Main Results:

• Robotic automation increased throughput by 31.2% in large-scale production (Case A) and 12.0% in order-based production (Case B).
• Simulation results closely matched actual implementation outcomes, validating the predictive power of the modeling approach.
• A single worker was confirmed to be capable of effectively operating the robotic system, demonstrating its practicality for SMEs.

Conclusions:

• Robotic automation is a viable strategy for enhancing productivity and reducing labor dependency in HMR manufacturing.
• The simulation-based evaluation provides critical insights for SMEs seeking to integrate robotics and drive digital transformation.
• This research validates the effectiveness of robotics in improving efficiency and throughput within the food industry.