Optimisation process for robotic assembly of electronic components

Abstract

Adoption of robots in the manufacturing environment is a way to improve productivity, and the assembly of electronic components has benefited from the adoption of highly dedicated automation equipment. Traditionally, articulated 6-axis robots have not been used in electronic surface mount assembly. However, the need for more flexible production systems that can be used for low to medium production builds means that these robots can be used due to their high degrees of flexibility, excellent repeatability and increasingly lower investment costs. This research investigated the application of an articulated robot with six degrees of freedom to assemble a multi-component printed circuit board (PCB) for an electronic product. A heuristic methodology using a genetic algorithm was used to plan the optimal sequence and identify the best location of the parts to the assembly positions on the PCB. Using the optimised paths, a condition monitoring method for cycle time evaluation was conducted using a KUKA KR16 assembly cell together with four different robot path motions. The genetic algorithm approach together with different assembly position iterations identified an optimisation method for improved production throughput using a non-traditional but highly flexible assembly method. The application of optimised articulated robots for PCB assembly can bridge the gap between manual assembly and the high-throughput automation equipment.

Comparison of a Bat and Genetic Algorithm Generated Sequence Against Lead Through Programming When Assembling a PCB Using a Six-Axis Robot With Multiple Motions and Speeds

“…To solve this allocation problem, two different heuristic strategies were proposed and detailed numerical experiments were carried out to evaluate the performances of the proposed GAs. Li et al [24] modelled the sequencing placing problem for a multi-head surface mounting machine as a travel salesmen problem and used a GA to find the optimal feeder allocation [17].…”

“…Motivated by previous results showing efficiency of the BA algorithm over other optimisation methods, this research presents a novel adaptation of a hybrid BA discrete algorithms to solve the placement sequence problems in electronic component assembly when using a 6-axis articulated robot for prototype assembly processes. Results of the algorithms are compared with the state of the art GA approach described in [17].…”

“…In a recent paper, a novel methodology using an articulated 6axis robot for assembly of PCB components has been proposed [17]. The authors employ a genetic algorithm (GA) to reduce cycle time for robot path motions.…”

Printed circuit board assembly time minimisation using a novel Bees Algorithm

“…Alkaya and Duman (2015) tested different combinations of optimisers, and obtained the best results iterating cycles of SA for component placement search and ABC for feeder layout optimisation. In addition, intelligent techniques like EAs and Artificial Bee Colony optimisation were applied to time minimisation problems involving different PCB assembly devices like multi-head gantry machines (Lin and Huang 2017;Guo et al 2018) or a Kuka robot (Andrzejewski et al 2018). In the following sections of the paper, the performance of the new Bees Algorithm implementation will be compared with the performance of three different kinds of EAs (Leu et al 1993;Nelson and Wille, 1995;Ong and Tan, 2002), one hybrid GA (Ho and Ji, 2007), two implementations of the standard Bees Algorithm (Pham, Otri.…”

A Hydraulic Soft Microhand with an Application of Live Insect Manipulation

“…The evolution in robotics in the past several decades opened new opportunities in various fields like the fields of surgery, biological studies, and small objects manipulation in industry [1], [2], [3], [4], [5], [6]. Minimally Invasive surgery (MIS) is highly depending on robotic technology to minimize patient trauma and improve clinical outcomes [7].…”