Designing an Industrial Pick-and-Place Robot
A leading provider of packaging machines was experiencing repeated motor failures with their pick-and-place robots, facing substantial replacement costs on a regular basis. The company chose Maplesoft to develop a high-fidelity parameterized model of the robot. Using MapleSim, the company simulated the robot’s operation and used Maple to understand the exact cause of failure in hopes of finding a cost-effective solution.
The results from MapleSim showed the company a solution they were unaware of - instead of replacing motors in every robot, they could modify the robot motion profiles to reduce the moments of greatest motor torque. The company was able to essentially apply a software update to what was previously expected to be costly, on-site hardware replacements for larger motors. Going forward, they are using their MapleSim models for other robots, minimizing the high costs of over-engineered components and unexpected on-site repairs.
Industrial automation is on the rise, with machines performing more complicated tasks every day. Designing these complex industrial machines is a challenging process. Engineers need to ensure that the machine they design meets many different performance objectives for productivity, workspace, maneuverability, payload, and so on. At the same time, they also need to develop a design that will minimize both production and maintenance costs, such as using the smallest possible motors and the shortest links for robot arms, and minimizing loading to reduce the wear and tear that leads to expensive repairs and downtime. In light of so many complexities, organizations will over-engineer products, investing in more costly components to reduce unforeseen failures. Others will try to minimize costs, but are more likely to face expensive on-site repairs when unexpected failures occur. System-level modeling offers a third option, providing analysis and deep insight into product performance long before physical prototypes.
A leading provider of packaging machines approached the Maplesoft Engineering Solutions team looking to understand why they were experiencing reoccurring motor failures in their pick-and-place robots deployed in the field. They turned to Maplesoft to help them answer questions about the design of their product, including many questions that could prove beneficial for all of their future robot designs:
- What is the proper motor sizing for the robot in all operating conditions?
- What lengths should the links be to achieve the desired workspace?
- What effect will different combinations of link lengths have on the design?
- What is the required performance from the motor and gearbox in different use cases?
Model Development using MapleSim
Each of the link structures includes sensor components to provide force and torque information, which can later be used to determine radial force, axial force, and bending moments at each bearing. The model also includes probes embedded at strategic locations withi...
Each of the link structures includes sensor components to provide force and torque information, which can later be used to determine radial force, axial force, and bending moments at each bearing. The model also includes probes embedded at strategic locations within the design to monitor performance characteristics, such as required motor speed and torque, along with joint angle and constraints.
Initial simulations were run in MapleSim to observe the behavior of the system, with the probe information presented in various plots. The model was then loaded into Maple for in-depth analysis.
Design Analysis using Maple
This case study presents just one example of innovation in the industrial automation and packaging machinery sectors. As automated robot requirements become more complex, this company realized the huge role that system-level modeling can play in driving innovation. What started as the desire to fix a simple problem has radically transformed their design process, shortening design cycles and minimizing unnecessary costs every step of the way.
Published by Maplesoft, Inc. on May 11, 2017
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