Real-time process control of powder bed fusion by monitoring dynamic temperature field

Huang, Xiaokang; Tian, Xiaoyong; Zhong, Qi; He, Shun-Wen; Huo, Chun-Bao; Cao, Yi; Tong, Zhiqiang; Li, Dichen

doi:10.1007/s40436-020-00317-y

Cited by 12 publications

(2 citation statements)

References 12 publications

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“…At the same time, the quality of the ternary material is related to the temperature of the entire process, and the collected temperature variables have high dimensions, so it is difficult to measure whether the process state is in a normal state through a simple weighted average index. In addition, in order to compensate for the influence of environmental factors, there is more than one optimal sintering system for the sintering preparation process [ 25 ]. For example, the operating parameters in winter and summer are different, so a single evaluation criterion cannot be applied to the preparation process of ternary material.…”

Section: Description Of the Problem In Monitoring The Preparation Pro...mentioning

confidence: 99%

A Monitoring Method Based on FDALM and Its Application in the Sintering Process of Ternary Cathode Material

Chen

et al. 2022

Sensors

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In industrial processes, the composition of raw material and the production environment are complex and changeable, which makes the production process have multiple steady states. In this situation, it is difficult for the traditional single-mode monitoring methods to accurately detect the process abnormalities. To this end, a multimode monitoring method based on the factor dynamic autoregressive hidden variable model (FDALM) for industrial processes is proposed in this paper. First, an improved affine propagation clustering algorithm to learn the model modal factors is adopted, and the FDALM is constructed by combining multiple high-order hidden state Markov chains through the factor modeling technology. Secondly, a fusion algorithm based on Bayesian filtering, smoothing, and expectation-maximization is adopted to identify model parameters. The Lagrange multiplier formula is additionally constructed to update the factor coefficients by using the factor constraints in the solving. Moreover, the online Bayesian inference is adopted to fuse the information of different factor modes and obtain the fault posterior probability, which can improve the overall monitoring effect of the model. Finally, the proposed method is applied in the sintering process of ternary cathode material. The results show that the fault detection rate and false alarm rate of this method are improved obviously compared with the traditional methods.

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Section: Description Of the Problem In Monitoring The Preparation Pro...mentioning

confidence: 99%

A Monitoring Method Based on FDALM and Its Application in the Sintering Process of Ternary Cathode Material

Chen

et al. 2022

Sensors

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“…Fleming et al [ 13 ] monitored the morphology of each layer of the SLM process before and after processing by an inline coherent imaging system, identifying bumps and depressions, remelting the raised areas, and filling the depressed areas, enabling artificial closed-loop control of the surface quality of the solidified layer. Huang et al [ 14 ] used a thermal image to monitor the temperature distribution of the solidification layer of the SLM process, established the relationship between scanning speed and temperature distribution, and maintained a stable solidification layer temperature by adjusting the scanning rate in real time to achieve closed-loop control of the SLM process. Numerous researchers have conducted extensive research to improve the quality of forming products for additive manufacturing [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Z-Increments Online Supervisory System Based on Machine Vision for Laser Solid Forming

Wang

et al. 2023

Micromachines

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An improper Z-increment in laser solid forming can result in fluctuations in the off-focus amount during the manufacturing procedure, thereby exerting an influence on the precision and quality of the fabricated component. To solve this problem, this study proposes a closed-loop control system for a Z-increment based on machine vision monitoring. Real-time monitoring of the precise cladding height is accomplished by constructing a paraxial monitoring system, utilizing edge detection technology and an inverse perspective transformation model. This system enables the continuous assessment of the cladding height, which serves as a control signal for the regulation of the Z-increments in real-time. This ensures the maintenance of a constant off-focus amount throughout the manufacturing process. The experimental findings indicate that the proposed approach yields a maximum relative error of 1.664% in determining the cladding layer height, thereby enabling accurate detection of this parameter. Moreover, the real-time adjustment of the Z-increment quantities results in reduced standard deviations of individual cladding layer heights, and the height of the cladding layer increases. This proactive adjustment significantly enhances the stability of the manufacturing process and improves the utilization of powder material. This study can, therefore, provide effective guidance for process control and product optimization in laser solid forming.

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In-Situ Temperature Monitoring and Feedback Control in the Gas Tungsten Arc Welding Process

Khan

Patidar²,

Madhukar³

2022

Int. J. Precis. Eng. Manuf.

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Real-time process control of powder bed fusion by monitoring dynamic temperature field

Cited by 12 publications

References 12 publications

A Monitoring Method Based on FDALM and Its Application in the Sintering Process of Ternary Cathode Material

A Monitoring Method Based on FDALM and Its Application in the Sintering Process of Ternary Cathode Material

Z-Increments Online Supervisory System Based on Machine Vision for Laser Solid Forming

In-Situ Temperature Monitoring and Feedback Control in the Gas Tungsten Arc Welding Process

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