CYCLE TIME EFFICIENCY AND TOTAL ENERGY CONSUMPTION IN ROBOTIC ASSEMBLY LINE SYSTEMS

An illustration of robotic arm showing thumbs up
Industrial robots speed up and automate a variety of manufacturing processes by assisting the workforce on the assembly line. This results in great success, in addition to being more flexible and affordable.

We are continually looking for improvements as researchers from the Wuhan University of Science and Technology and the University of Leicester have recently developed an improvement procedure that can help optimize the cost and efficiency of various robots running in lines.

Mounting Technology

The technology is based on a meta-heuristic algorithm based on the flight mode of migratory birds. Due to its simplicity and adaptability, it is well suited for troubleshooting upgrades. They are then tested in various situations, in which different types of robots are expected to work together to assemble products.

Tech Algorithm 

This algorithm can minimize the total cycle time of the assembly line and reduce the total purchase cost of a group of robots.The algorithm selects a solution from a set of possibilities that can optimize the total cost and reduce the total cycle time, and replace the outdated solution.

The team of researchers evaluated the performance of their algorithm comparing it to previous optimization techniques used by organizations. The techniques they compared included a multi-target non-dominated genetic classification algorithm II, a multi-target simulated annealing algorithm, and two multi-target artificial bee colony algorithms.

With this new technology, significant results have been achieved, equal to those proven with the latest generation technology. This solution improves the cost and efficiency of the assembly line, a group of robots was used to support the workforce.

Mukund Janardhanan one of the researchers who carried out the investigation, commented:

For many industries, buying robots is an expensive affair. The model developed in this work will help production managers to estimate and optimize costs involved in buying robots and cycle time simultaneously, and this will help them make decisions while designing or redesigning assembly lines.”

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