1- Introduction

2- Online process analysis and quality estimation of the system

3- Welding process control

4- Conclusion

References

Abstract

Resistance spot welding (RSW) is frequently employed in current industrial occasions. However, the process is multi-field coupled and highly nonlinear, and full of uncertainties and disturbances. This paper presents recent primary advances and progress in process analysis and quality control of the RSW operations. Online welding process analysis, and relative online quality estimation for the welding products, are very important because they can help to save energy and improve the efficiency during actual production. It should deeply interpret the process characteristics, and then reasonable relations between selected monitoring process variables, such as dynamic resistance or electrode displacement, and quality criteria, such as nugget size or tensile-shear strength, can be established. Apart from online process analysis using mathematical tools, using different kinds of auxiliary measuring signals from external sensors and intrinsic process variables to monitor the process and obtain the quality information of the weld is presented and discussed. Then various process control works are reviewed. Besides the various parameters optimization methods, kinds of controllers, including feedback controllers, intelligent controllers and comprehensive controllers which combined the online quality estimation and control strategy application together, for obtaining welds with satisfactory quality, are respectively discussed. It can be seen that the establishment of general models to online process analysis, quality estimation and real time control system design for obtaining welds with satisfactory quality still remains a big challenge in reality. This work can provide references and enlightens for current academic researches or actual production in RSW relative area.

Introduction

Resistance spot welding (RSW) is extensively employed in joining sheet metal components, such as in the manufacturing of automobiles, trucks trailers, buses, recreational vehicles, office furniture and appliances, railway vehicles, airplane structures, aeronautical and space applications and many other products [1–5]. Especially in the automobile industry, over 90% of assembly work in a car body is completed by RSW [6]. The automotive structural assemblies use groups of spot welds to transfer load through the structure during a crash. Typically, a modern vehicle includes 2000–5000 spot welds [7]. These are the main reasons that the RSW is employed extensively currently. The main advantage of the RSW is that the process can be automated and robotized in high volume for high production rate operations. However, RSW process involves interactions between electromagnetic, thermal, mechanical, fluid flow and metallurgical phenomena across faying interfaces and so that is very complicated [8]. The process is difficult to properly control because the final weld quality is determined by interaction between various operational parameters and mechanical/electrical characteristics of the machine and equipment involved. In general, a modern automotive production line of high volume models produces approximately 7 million welds per day [9]. Hence, to ensure the integrity of the welded structure and improve the efficiency of the welding production, the recent advances of some important aspects during the RSW process, including online process analysis and monitoring, online non-destructive weld quality estimation and control system design to guarantee the high quality, are considered in this paper. During the traditional RSW working process, two or more parent metal sheets are pressed together by electrode force, which is usually controlled by air pressure in the pneumatic cylinder, or servo actuator. After the parent metal sheets are fixed, external electrical energy is delivered into the welding system and the welding current goes through the parent metal sheets, then heat energy is initially generated at the interface of the metal energy due to contaminations and surface asperities, so that the interface has the largest resistances at the beginning of the process [10,11].