席子加工去毛刺过程的实验研究及模型的建立

P. Damle, V. P. Wani, I. D. Patil, A. Nikalje
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引用次数: 0

摘要

这项工作的目的是提高工人的生产率。考察了垫子去毛刺过程中BMI、臀膝长度、腘窝高度、座底高度、靠背支撑高度、室温等各独立参数对工人生产效率的影响。考虑到这些参数,要考虑的两个重要方面是人类工人的生产率以及工人的舒适度。我们想找出哪一个参数对提高生产率最重要。本文的重点是建立一个多变量线性回归和人工神经网络模型,以准确地预测实验证据。结果表明,人工神经网络模型预测生产率的相关系数(R)为0.9412。该模型得到的期望输出作为实测值与模拟值之间的预测均方误差为0.5009。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experimental Investigation and Formulation of Model of Deburring Process of Mat Manufacturing
The aim of the work was to increase the productivity of workers. The various independent parameters like BMI, Buttock-Knee length, Popliteal Height, Seat base height, back rest support height, and room temperature during deburring process of mat was investigated and also finds out influence parameter on productivity of worker. Considering these parameters the two important aspects to be considered are productivity of human workers along with the comforts to the workers. We would like to find out which parameter is most important for increasing the productivity. The focus of this paper is to develop a Multivariable Linear Regression and Artificial Neural Network models which will predict the experimental evidences accurately. It was observed that the ANN model predict the productivity with correlation coefficient (R) 0.9412. The prediction Mean Square Error was between the desired outputs as measured values and the simulated values were obtained as 0.5009 by the model.
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