International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
www.irjet.net
Simulation and Experimental Evaluation of a Robotic Handling Arm for Operational Optimization in Cold-Chain Industries Veena Anilkumar Lalvani1, Jatin R Makwana2 1U.G. Student, 2Professor, Department of Production Engineering, BVM Engineering College, Vallabh Vidyanagar,
Anand, Gujarat, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - This study explores the development of a semi-
the role of simulation and prototyping in optimizing robotic systems for specialized tasks.
automated robotic arm designed to address inefficiencies observed in frozen food industries where manual pick-andplace tasks dominate operations. These repetitive tasks contribute to early fatigue and inconsistency in worker performance, particularly during the initial hours of shifts. To tackle this issue, a simulation-centric robotic model was created using MATLAB and Simulink, leveraging the Simscape Multibody Toolbox to replicate the mechanical behavior of a manipulator. The simulated environment facilitated precise analysis of motion dynamics, actuator control, and trajectory optimization. Complementing the simulation, a physical prototype—constructed as a non-integrated black-box model using Arduino Nano—validates the basic control mechanism through joystick inputs and servo motion. While not a fully realized Digital Twin, the system enables experimentation with its core principles, establishing the groundwork for realtime predictive modeling and performance tuning. The projected outcome would indicate improved handling stability and productivity, demonstrating the potential of simulationaugmented automation in enhancing cold storage operational efficiency.
One body of research focuses on simulation-based modelling using tools such as MATLAB and Simulink. A 3-DOF robotic manipulator was modelled using computed torque control (CTC) to ensure accurate trajectory tracking, showcasing the significance of dynamic modelling in control optimization. Another study employed the Denavit-Hartenberg convention for kinematic analysis, integrating MATLAB simulations with Arduino-driven actuators for effective joint coordination and motion control. The use of inverse kinematics further validated motion accuracy and system reliability. Prototyping efforts have demonstrated practical feasibility through microcontroller-based systems. Lightweight pickand-place robotic arms utilizing servo motors, Arduino platforms, and joystick inputs were shown to deliver accurate object manipulation. Some implementations incorporated pneumatic circuits and revolute joints to handle larger payloads or reduce operational cycle time, with applications in palletizing, sorting, and automotive assembly.
Key Words: Manipulator, simulation, Arduino nano, kinematics, cold chain automation, prototyping, productivity, trajectory control.
In domain-specific contexts such as the food industry, robotic automation has contributed to productivity gains, improved hygiene, and reduced manual effort. Technologies like SCARA robots and vision-assisted mechanisms have been deployed in packaging and processing, although high initial costs remain a challenge.
1.INTRODUCTION In frozen food processing units, maintaining consistent performance in sub-zero environments poses challenges due to worker fatigue and reduced dexterity during repetitive tasks. These inefficiencies lower throughput and increase the risk of human error, highlighting the need for automation. This study addresses these issues by developing a robotic arm for automated pick-and-place operations. A MATLABSimulink simulation models kinematics and control logic, while a microcontroller-based black-box prototype validates physical feasibility. The combined virtual and physical approaches support scalable automation in cold storage settings.
Colour-sorting robotic systems have also been explored, where robotic arms use sensor input to classify and sort objects, indicating strong potential in laboratory automation and quality control scenarios. Collectively, these studies underscore the importance of combining simulation environments with physical prototyping to create efficient, adaptable, and applicationspecific robotic systems.
3. RESEARCH PROBLEM AND DATA COLLECTION
2. LITERATURE REVIEW
Manual pick-and-place operations in cold storage facilities are inefficient, error-prone, and time-consuming. These operations are hindered by labor costs, low throughput, and the challenges of working in sub-zero temperatures. This research addresses the need for an affordable, efficient
Recent advancements in industrial automation highlight the growing relevance of robotic arms in enhancing operational efficiency, precision, and safety. Various studies emphasize
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