Maintenance Cost Minimization for an Agricultural Harvesting Gripper

Area of Science:

• Robotics
• Agricultural Engineering
• Maintenance Engineering

Background:

• Maintenance is critical in smart farming, with costs arising from both under- and over-maintenance.
• Achieving a balance in maintenance strategies is essential for system longevity and cost-effectiveness.
• Harvesting robotic systems require optimized maintenance for actuators to ensure economic viability.

Purpose of the Study:

• To present an optimal maintenance policy for minimizing costs in smart farming.
• To determine the ideal preventive replacement time for actuators in a harvesting robotic system.
• To apply a nature-inspired optimization algorithm for actuator maintenance.

Main Methods:

• A novel gripper utilizing Festo fluidic muscles as actuators was presented.
• A nature-inspired optimization algorithm was employed to define the maintenance policy.
• The optimal maintenance policy was developed and applied to the Festo fluidic muscles.

Main Results:

• The developed optimal maintenance policy demonstrated a significant reduction in overall costs.
• Preventive replacement of actuators a few days prior to their estimated lifetime proved most cost-effective.
• Comparison of manufacturer-provided lifetime and Weibull distribution estimates informed the optimal replacement strategy.

Conclusions:

• The optimal maintenance policy effectively minimizes costs associated with actuator replacement in smart farming robotics.
• Preventive replacement strategies, informed by data-driven lifetime estimations, are crucial for economic efficiency.
• This study highlights the importance of tailored maintenance schedules for robotic components in advanced agricultural applications.