Process Monitoring and Control of Laser Beam Welding

Kaierle, Stefan

doi:10.1002/latj.200890024

Cited by 16 publications

(8 citation statements)

References 2 publications

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“…Many sensor and quality assurance systems have been invented and introduced to industrial assembly lines, most of which use cameras and photodiodes for monitoring [136], [137]. Systems in industrial use today are set up manually and undergo many trials.…”

Section: ) Motivationmentioning

confidence: 99%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

101

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Abstract-Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years. This paper presents the general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems. Starting with an introduction on the historical context of different paradigms of production (e.g., evolution of production and planning systems), different approaches for the design, planning, and operation of production systems are lined out and future trends towards fully autonomous components of an production system as well as autonomous parts and products are discussed. In flexible production systems with manual and automatic assembly tasks, human-robot cooperation is an opportunity for an ergonomic and economic manufacturing system especially for low lot sizes. The state-of-the-art and a cognitive approach in this area are outlined. Furthermore, introducing self-optimizing and self-learning control systems is a crucial factor for cognitive systems. This principles are demonstrated by a quality assurance and process control in laser welding that is used to perform improved quality monitoring. Finally, as the integration of human workers into the workflow of a production system is of the highest priority for an efficient production, worker guidance systems for manual assembly with environmentally-and situationally dependent triggered paths on state-based graphs are described in this paper.Note to Practitioners-Today's manufacturing enterprises have to face a number of challenges in a turbulent environment that originates amongst other from saturated markets, unprecedented and abrupt changes in market demands, an ever increasing number of product variants and smaller lot sizes. A recent research trend in Germany is the so called Cognitive Factory, where artificial cognitive capabilities are introduced to the control of production systems. The applications range from production planning and control, human-robot-cooperation, automatic robot programming to intuitive worker guidance systems.The concept of fully automated production systems is no longer a viable vision, as it has been shown, that the conventional automa- tion is not able to deal with the ever-rising complexity of modern production systems. Especially, a high reactivity, agility and adaptivity that is required by modern production systems, can only be reached by human operators with their immense cognitive capabilities, which enable them to react to unpredictable situations, to plan their further actions, to learn and to gain experience and to communicate with others. Thus, new concepts are required, that apply these cognitive principles to the planning processes and control systems of pr...

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Section: ) Motivationmentioning

confidence: 99%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

101

View full text Add to dashboard Cite

show abstract

“…And it's found that the image of the latter was clearer. Through experimental measurement and demonstration, Zhang et al [20,24] found that the band range of plasma light intensity was mainly 430~480 nm and 630~650 nm, as shown in Figure 6. Zhang et al [28] selected a diode laser light source with a wavelength of 808 nm and a bandpass filter with a wavelength of 808±3 nm.…”

Section: Auxiliary Light Source and Filtermentioning

confidence: 99%

“…Through lots of experiments, it's proved that when the light source was shot in at an incident angle of 50°, the outline image of keyhole was the clearest, as shown in Figure 5. Zhang et al [24] found that when the welding area was irradiated by the point light source at about 72°, the images of molten pool and keyhole were the clearest. According to the irradiation angle of auxiliary light source, it could be divided into the coaxial light source and the paraxial light source.…”

Section: Auxiliary Light Source and Filtermentioning

confidence: 99%

The review of visual monitoring and recognition algorithm in laser welding

Wang

Shen

Zhang

et al. 2023

AOPC 2022: Advanced Laser Technology and Applications

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There is abundant information in molten pool and keyhole during laser deep penetration welding. Their stability and characteristics are closely related to welding quality. At present, visual monitoring is an important means to obtain the characteristics of molten pool and keyhole. However, how to obtain a clear image, and how to optimize or develop an accurate and efficient algorithm are two major problems facing the visual monitoring of molten pool and keyhole. In view of the above problems, the paper combs the factors affecting molten pool visual monitoring and molten pool recognition algorithm. Firstly, the effects of camera type, auxiliary light source and filter, image acquisition method, the shielding gas and the air pressure on the image clarity of molten pool and keyhole are emphatically analyzed, and a method conducive to visual monitoring of molten pool and keyhole is proposed. Secondly, the influence of different algorithms and models on the monitoring accuracy of the system is analyzed. It is found that image pre-processing can highlight molten pool image information, and DBN (Deep Belief Networks) model has higher prediction accuracy through the processed molten pool image. Pointed out in the end of this article, the development of a laser welding monitoring device with clear image, stable and high dynamic response, the integrated development of multi-sensor synchronization visual monitoring device, and the development of laser welding process of adaptive fusion image processing algorithms will be the focus in the future, which provides a research direction for monitoring of molten pool and keyhole.

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“…Monitoring and quality control is an essential tool in modern manufacturing systems and necessary in order for production results to be kept in deterministic boundaries [6]. The monitoring of a process, and consequently, the quality assessment, follows three categories:…”

Section: Introductionmentioning

confidence: 99%

Quality assessment in laser welding: a critical review

Stavridis

Papacharalampopoulos

Stavropoulos

2017

Int J Adv Manuf Technol

176

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Quality assessment methods and techniques for laser welding have been developed both in-and post-process. This paper summarizes and presents relevant studies being classified according to the technology implemented (vision, camera, acoustic emissions, ultrasonic testing (UT), eddy current technique (ECT)) for the quality inspection. Furthermore, the current review aims to map the existing modeling approaches used to correlating measured weld characteristics and defects with the process parameters. Research gaps and implications of the quality assessment in laser welding are also described, and a future outlook of the research in the particular field is provided.

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Process Monitoring and Control of Laser Beam Welding

Cited by 16 publications

References 2 publications

Artificial Cognition in Production Systems

Artificial Cognition in Production Systems

The review of visual monitoring and recognition algorithm in laser welding

Quality assessment in laser welding: a critical review

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