Implementation of Taguchi methodology in optimization of developed jigs and fixtures for production of paddy weeder

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• 作者：Ankitesh Shrivastava ; Ajay Verma
• 关键词：Paddy weeder ; Solid works ; Jigs and fixtures ; Design of experiments ; Taguchi method
• 刊名：Paddy and Water Environment
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：15
• 期：1
• 页码：1-9
• 全文大小：
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Agriculture; Hydrology/Water Resources; Hydrogeology; Geoecology/Natural Processes; Ecotoxicology; Soil Science & Conservation;
• 出版者：Springer Japan
• ISSN：1611-2504
• 卷排序：15

文摘

Chhattisgarh is one of the major rice growing states of India, and paddy is the main crop, cultivated in about 76 % of area under agriculture. Mechanical weed control helps reduce the drudgery involved in manual hoeing. Manufacturing process of paddy weeder involves several operations that are to be performed sequentially, repeatedly, effectively, and hence, emphasis is to perform all the operations more efficiently as well. Jigs were designed with the help of software Solid Works and were then developed at the Faculty of Agricultural Engineering, Raipur. The saving in cost of weeding was 60 %, and saving in time was 65 % compared to manual weeding. The improved jigs facilitated the production in 60 % of time taken by traditional jigs. Taguchi method was used to solve the problems related to improving the yield and productivity. Taguchi’s design of experiments (DOE) helped pin-point the source of yield and increase the yielding efficiency. The DOE based on L8-orthogonal array of Taguchi methodology were implemented. The paper outlines Taguchi methodology to optimize the control factors having high and low settings in the production of paddy weeder. The analysis of the results showed that the optimal combination for minimum time consumption in production process is maximum number of bending with minimum welding operation and minimum number of drilling operations. The optimized process by implementation of Taguchi methodology showed a reduction of 30 % in average production time.