Purpose

The current research work presents the application of fuzzy logic modeling for electric discharge coating (EDC) process for predicting the material transfer rate (MTR), which has the capability of producing thick and thin films on the conductive substrate material.

Design/methodology/approach

Thirty-two real-time experiments were conducted, and fuzzy rules were framed from the inference made from this experimental data. Validating experiments were carried out to check the feasibility of the developed model in prediction.

Findings

A fair agreement has been observed between experimental results and the outcomes of fuzzy model. This was supported by a goodness of fit value of 0.917. The values of adjusted R² and standard error were 0.914 and 19.112, respectively.

Research limitations/implications

Current research deals with the prediction of MTR at various parameter grouping conditions, which majorly influence the response parameters. However, other parameters such as quality of the dielectric fluid, flushing pressure and purity of the electrode and work material and so on that influence the response parameters could be further investigated and stand as a future scope of the current work.

Practical implications

MTR is a response parameter that accounts the actual material transfer to the workpiece during the deposition process. This parameter supports/alters the hardness, adhesion, wear resistance and other mechanical properties of the work material. The current modeling work helps to take an optimum decision without conducting large number of experiments at the industrial scale. Due to the nature of fuzzy logic, this method has a potential advantage in dealing with real-time data for various industrial applications.

Originality/value

Developing a fuzzy model for EDC process is not yet addressed, and to attain the economic objective of the process, optimal deposition conditions must be determined, which help the industries to reduce the operation costs. The current study outcomes substantiate the effectiveness of the fuzzy logic in decision-making and prediction of response parameters.

中文翻译：

---

利用粉末冶金工具开发EDC工艺中MTR预测的智能系统

目的

当前的研究工作提出了用于放电涂层（EDC）过程的模糊逻辑建模在预测材料传输速率（MTR）中的应用，该材料具有在导电基板材料上产生厚膜和薄膜的能力。

设计/方法/方法

进行了32个实时实验，并根据从该实验数据得出的推论构造了模糊规则。进行了验证实验，以检验开发的模型在预测中的可行性。

发现

实验结果与模糊模型的结果之间已观察到公平的协议。拟合优度为0.917支持了这一点。调整后的R ²和标准误的值分别为0.914和19.112。

研究局限/意义

当前的研究涉及在各种参数分组条件下对地铁运输的预测，这主要影响响应参数。但是，可以进一步研究影响响应参数的其他参数，例如介电液的质量，冲洗压力以及电极和工作材料的纯度等，可以作为当前工作的未来范围。

实际影响

MTR是一个响应参数，用于说明在沉积过程中实际材料向工件的转移。该参数支持/改变工作材料的硬度，附着力，耐磨性和其他机械性能。当前的建模工作有助于做出最佳决策，而无需在工业规模上进行大量实验。由于模糊逻辑的性质，该方法在处理各种工业应用的实时数据方面具有潜在的优势。

创意/价值

为EDC工艺开发模糊模型尚未解决，为了达到工艺的经济目的，必须确定最佳的沉积条件，这有助于工业降低运营成本。当前的研究结果证实了模糊逻辑在决策和响应参数预测中的有效性。