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Corrugated Box Production Process Optimization using Dimensional Analysis and Response Surface Method

机译:尺寸分析和响应面法优化瓦楞纸箱生产工艺

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The paper focuses on optimization of the manufacturing process of the corrugated sheet box using Dimensional Analysis (DA) and Response Surface Method (RSM). A mathematical model for five different box sizes in terms of Pi terms using Buckingham's Pi theorem and polynomial equation between independent and response parameters are obtained. RSM is the statistical method useful in the modeling and analysis of problems in which the response variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a corrugated box production process. The objective of this study is to minimize the root mean square error (RMS) between the experimental values and computed values of cycle time obtained from mathematical model using RSM. Studies carried out for corrugated sheet box manufacturing industries having man machine system revealed the contribution of many independent parameters like anthropometric data of workers, personal data, machine specification, workplace parameters, product specification, environmental conditions and mechanical properties of corrugated sheet on cycle time. Their effect on response parameter cycle time is totally unknown. The developed model was simulated and optimized with the aid of MATLAB R2011a data cursor tool. The results obtained showed that the correlation R towards linearity, adjusted R~2 upto 95% and RMS error less than 10% were valid.
机译:本文重点研究了使用尺寸分析(DA)和响应面方法(RSM)优化瓦楞纸箱制造工艺的方法。利用白金汉的Pi定理和独立参数与响应参数之间的多项式方程,获得了一个基于Pi项的五个不同盒子大小的数学模型。 RSM是一种统计方法,可用于问题的建模和分析,在这些问题中,响应变量会受到几个独立变量的影响,以确定哪些条件下应使用这些变量来优化瓦楞纸箱生产过程。本研究的目的是最小化使用RSM从数学模型获得的周期值的实验值和计算值之间的均方根误差(RMS)。对具有人机系统的瓦楞纸箱制造行业进行的研究表明,许多独立参数的贡献,例如工人的人体测量数据,个人数据,机器规格,工作场所参数,产品规格,环境条件和瓦楞纸在循环时间内的机械性能。它们对响应参数循环时间的影响是完全未知的。利用MATLAB R2011a数据光标工具对开发的模型进行了仿真和优化。得到的结果表明,线性相关性R,调整后的R〜2高达95%和RMS误差小于10%是有效的。

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