Process Diagnostics and Control in Thermal Spray

Mauer, Georg; Moreau, Christian

doi:10.1007/s11666-022-01341-z

Cited by 13 publications

(4 citation statements)

References 54 publications

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“…Another similar study looked into airborne aeroacoustics (AAE), by positioning a piezoelectric sensor near the torch [46], the data obtained proved that the AE contains measurable information related to the spraying parameters, such as the powder feed rate, the spraying distance, and the resulting micro-hardness of the coating. Both of these acoustic monitoring techniques have been implemented industrially, to detect and identify defects in materials or components before they become visible or cause failure, with the aid of machine learning algorithms [47].…”

Section: Use Of Diagnostic Tools For Reducing Iterationsmentioning

confidence: 99%

A Guiding Framework for Process Parameter Optimisation of Thermal Spraying

et al. 2023

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Currently, most thermal spray coating service providers expect original equipment manufacturers (OEMs) to suggest the coating recipe, comprising of the right coating equipment, starting process parameters, type of inert gases, and robot program. The microstructure and mechanical properties may not comply in the first few runs. Feedback from a competent material testing service provider forms the initial step to adjust the parameters in the development journey, toward identifying the processing parameters required to obtain an acceptable coating. With the surge of interest in sustainable manufacturing, the time spent on trials in the future will shrink, and a more rigorous process needs to be applied to achieve the “right-first-time manufacturing” approach in thermal spraying. However, a framework for the systematic development of thermal spray parameter optimisation is lacking. This article provides a framework, based on a logical acumen, in selecting the right process parameters, using available data and prior knowledge about the thermal spraying process. To that end, the article summarises the extant developmental journey of thermal spray process parameters, by covering the aspects of equipment choice, robot and spray parameters, and how to minimise iterations, using diagnostic tools to get to the end solution most efficiently. This article, in its current form, will serve as a good guide for early career engineers and scientists or workers, to minimise the time processing window, by avoiding endless iterations to deposit a certain type of coating using thermal spraying. Besides, this work is also aimed at transforming academic research innovations to a robust and repeatable industrial manufacturing process.

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Section: Use Of Diagnostic Tools For Reducing Iterationsmentioning

confidence: 99%

A Guiding Framework for Process Parameter Optimisation of Thermal Spraying

et al. 2023

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“…Therefore, further development of sensors, testing, modeling, and ML techniques are found in concerted action with other activities to improve the design and control of thermal spray processes. 236) Malamousi et al reviewed the readily available digital tools and methods for coating deposition optimization, equipment health monitoring, process control and metallographic analysis in the thermal spray technologies. The most promising ML methods are discussed for thermal and cold spray.…”

Section: Spray Coatingmentioning

confidence: 99%

Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies

Kambara

Kawaguchi

Lee

et al. 2022

Jpn. J. Appl. Phys.

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Low-temperature plasma processing technologies is essential for material synthesis, device fabrication, and surface treatment. The development of plasma-related products and services requires an understanding of the multiscale complex behaviors of plasma and the hierarchical integration of plasma generation, energy and mass transports through sheath region, surface reactions, and other processes. The importance of science-based and data-driven approaches to controlling systems is argued. The state-of-the-art of deep learning, machine learning, and artificial intelligence in low-temperature plasma science and technology is reviewed. In this review, the requirements and challenges for plasma parameter prediction and processing recipe discovery are asserted by researchers in the fields of material science and plasma processing. It also outlined a science-based, data-driven approach for development of virtual metrology in plasma processes.

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“…As can be seen from the diagram, the designed finite element model allows receiving the data at any point in the torch space. Depending on the ratio of the combustible substance and oxygen, the gas flame is divided into [12][13][14]:…”

Section: The Dependence Of the Heat Flow Density The Temperature Grad...mentioning

confidence: 99%

The impact of technological parameters of the torch to physical and chemical properties of a gas-thermal burner for spraying ultra-high molecular weight polyethylene

Skakov¹,

Ocheredko²,

Bayandinova³

et al. 2022

phst

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The values of the heat flux density, transverse and longitudinal temperature gradients of the gas-thermal burner torch, the type of reaction during the combustion in various modes (reducing, neutral, oxidizing) depending on the mass fractions of the fuel and oxidizer burning have been determined in this paper. The significant role of the torch temperature as one of the most important parameters determining the quality of polymer coatings obtained by the gas-thermal method has been established. A spatial model of a gas-thermal burner has been designed, which allows to obtain thermal modes at specified technological parameters. A physical model of the interactions "torch-polymer particle", "thermal jet -base" has been developed. The necessary density of the torch heat flux for the complete melting of ultrahigh molecular weight polyethylene (UHMWPE) particles not exceeding the temperature threshold of destruction has been determined. The required rate of introduction the UHMWPE powders into the burner flame has been also determined. Based on the calculations of the "torch-polymer particle interaction", the optimal geometry of the torch, the particles trajectory in the torch and the spraying distances have been determined.

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Process Diagnostics and Control in Thermal Spray

Cited by 13 publications

References 54 publications

A Guiding Framework for Process Parameter Optimisation of Thermal Spraying

A Guiding Framework for Process Parameter Optimisation of Thermal Spraying

Science-based, data-driven developments in plasma processing for material synthesis and device-integration technologies

The impact of technological parameters of the torch to physical and chemical properties of a gas-thermal burner for spraying ultra-high molecular weight polyethylene

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