Optimization Control of Induction hardening Process

Ge, Yunwang; Rong-qiang, HU; Zong-jie, Zhang; Qing-tong, Shen

doi:10.1109/icma.2006.257783

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…By using the methodology developed in his research, a significant improvement in the process was achieved. Ge et al (2006) in their paper analysed relationship of hardening parameters like voltage and current control of power supply, heating time control and part speed control for scan induction hardening. Dynamic models for power supply current and part moving speed have been presented.…”

Section: Introductionmentioning

confidence: 99%

Optimization of processing parameters in induction hardening using response surface methodology

Kohli

Singh

2011

Sadhana

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In this paper, an effective procedure of response surface methodology (RSM) has been utilized for finding the optimal values of process parameters while induction hardening of AISI 1040 under two different conditions of the material i.e., rolled and normalized. Various process parameters, such as feed rate (speed at which the induction coil moves, which is measured in mm/sec), current, dwell time (time after which heat intensity starts to heat work piece in seconds) and gap between the work piece and induction coil have been explored by experiments. Hardness at two different conditions has been considered as performance characteristic. The experiment plan was based on rotatable, central composite design (CCD). The experimental results showed that the proposed mathematical models suggested could describe the performance indicators within the limits of the factors being investigated. The obtained optimal process parameters have been predicted and verified by confirmation experiments. Microstructure and SEM (scanning electron microscope) analyses were also done for justification of the work.

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Section: Introductionmentioning

confidence: 99%

Optimization of processing parameters in induction hardening using response surface methodology

Kohli

Singh

2011

Sadhana

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“…This is not a problem in nature, but it is the responsibility of the system operator to each time manually select which setting to use depending on the material to be brazed. In the case of constantly recurring operations, typical for serial production, errors are possible, leading to delay, poor results, and the need for corrections [12,13]. On the other hand, the peculiarities of these technological processes and the challenges related to ensuring the quality of products in their use in the industry are solved using artificial intelligence techniques.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Induction Brazing System Control Based on Artificial Intelligence

2021

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This paper considers the synthesis of control of an electro-technological system for induction brazing and its relationship with the guarantee of the parameters and the quality of this industrial process. Based on a created and verified 3D model of the electromagnetic system, the requirements to the system of power electronic converters for obtaining brazing between different common combinations of materials are determined. After processing and summarizing the results, an approach for automatic recognition of the type of material to be brazed is proposed and researched, as well as switching between different controller settings in order to achieve optimal performance and ease the operator. The advantages of using such an approach based on the use of artificial intelligence techniques are considered, including guidelines for its application and development in industrial systems with induction heating.

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