Citation: Wang, L.; Shu, L.; Zhou, H.
Multi-Robot Collaborative Flexible
Manufacturing and Digital Twin
System Design of Circuit Breakers.
Appl. Sci. 2023, 13, 2721. https://
doi.org/10.3390/app13042721
Academic Editor: Yutaka Ishibashi
Received: 31 January 2023
Revised: 12 February 2023
Accepted: 16 February 2023
Published: 20 February 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
Article
Multi-Robot Collaborative Flexible Manufacturing and Digital
Twin System Design of Circuit Breakers
Linghao Wang
1
, Liang Shu
1,
* and Hao Zhou
2
1
Engineering Research Center of Low-Voltage Apparatus Technology of Zhejiang Province,
Wenzhou University, Wenzhou 325035, China
2
Technology Institute, Wenzhou University, Wenzhou 325699, China
* Correspondence: shu22@wzu.edu.cn; Tel.: +86-138-6887-9070
Abstract:
Circuit breakers (CBs) are mainly designed to interrupt current flow when faults are
detected and have been widely used in industrial applications. The existing CBs manufacturing
method is semi-automatic and requires a lot of labor. To realize flexible manufacturing, a multi-robot
cooperative CBs flexible manufacturing system (CBFMS) is presented in this study. Aiming at the
efficiency of the multi-robot cooperative CBFMS key units, a two-arm cooperation robot approach
is proposed. The reinforcement learning algorithm is developed to optimize the manufacturing
trajectory of the two-arm cooperation robot. To build and optimize the multi-robot cooperative
CBFMS, a digital twin (DT) system describing all physical properties of the physical manufacturing
plant is constructed for simulation. In the developed DT system, a kinematic control model of the
collaboration robot is established. A real-time display of the robot’s trajectory, manufacturing status,
and process manufacturing is provided by the data interaction with the physical cell flow between
the units. Following this design, a synchronous mapping between the flexible manufacturing DT
system of the CBs and the physical workshop is realized, which enables real-time monitoring and
management of the physical production line. The experiments’ results show that the manufacturing
efficiency, compared with traditional CBs production, is improved by 22%. Moreover, the multi-robot
cooperative CBFMS can make process changes according to the production requirements, which can
improve the stability of production.
Keywords:
circuit breaker (CB); digital twin (DT) system; multi-robot collaboration; deep
reinforcement
learning; motion control
1. Introduction
Circuit breaker [
1
,
2
] is an important component of the electrical industry, which plays
an important role in production and manufacturing. Most of the traditional CBs manufac-
turing is performed with semi-automated production. Most of the assembly operations
cannot be completed with robots. To achieve high manufacturing efficiency, the concept of
flexible CBs manufacturing has been developed. With the development of the Industry 4.0
era [3], industrial robots are developed for flexible manufacturing systems (FMS) because
of their high flexibility and operability [
4
]. At present, several problems still exist in CBs
manufacturing when assembly robots are incorporated: (1) a proper assembly process is
usually missing, which results in relatively low production efficiency; (2) collaborative
robots in motion control and trajectory optimization are still facing many challenges [
5
–
8
].
Digital twin (DT) technology is mainly applied in aerospace applications. In addition, the
DT system can be applied to the design, development, manufacturing, assembly, operation,
and maintenance of aircraft [
9
–
12
]. With the development of manufacturing, DT technology
is beginning to be integrated into intelligent manufacturing. It can effectively improve the
production conditions and intelligence level. To solve the problems of adaptability and
human dynamics, a DT system in the field of automation was proposed. By introducing
Appl. Sci. 2023, 13, 2721. https://doi.org/10.3390/app13042721 https://www.mdpi.com/journal/applsci
