Sustainable design manufacturing to the needs of Industry 4.0

Halim, Asmira (2017) Sustainable design manufacturing to the needs of Industry 4.0. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

	Text (24 Pages) Sustainable Design Manufacturing To The Needs Of Industry 4.0.pdf - Submitted Version Download (292kB)
	Text (Full Text) Sustainable design manufacturing to the needs of Industry 4.0.pdf - Submitted Version Restricted to Repository staff only Download (31MB)

Abstract

Nowadays, the growth of economy and increases of competitiveness in order to boost quality, flexibility, speed and productivity created significant demand of the digitization of manufacturing technologies. These technological advances have driven increases in demand for computer-based tools or computer-aided tools to facilitate the manufacturing processes and increase the industrial productivity. One of the problems in manufacturing processes is the recognition or extraction of product features. The study of feature recognition method is vital to facilitate the recognition of part feature and improve the design of product model. In addition, this method is significant for the integration between computer-aided design (CAD) and computer-aided manufacturing (CAM) in manufacturing industries. In this research study, interactive feature recognition method is used to improve the design of mobile phone housing (back cover). Furthermore, the implementation of feature recognition will enable the recreation of imported feature from different file formats into feature model that can be altered. Besides that, the use of feature recognition helps to improve the design of the product model as feature problems of the product model can be corrected directly. The improvement of mobile phone’s back cover will influence the design features, structural safety and performance of the back cover. Linear Static Analysis using SolidWorks SimulationXpress and Drop Test Analysis in ANSYS Explicit Dynamic packages have been utilized for both existing and improvement designs in this research study. The results obtained from linear static analysis demonstrated the decrement in Von Mises Stress and displacement consequently, contribute of a good value of safety factor. The prediction of fatigue mode can be attained by applying the computation of Newton interpolation polynomial, which showed that the improvement design can withstand higher initial pressure and will experience slower failure condition. Meanwhile, results from the dynamic analysis (drop test analysis) depicts that improvement design has lower values for total deformation, maximum stress and linearized stress intensity compared to existing design. Validation of both design models are done based on the computation of Design Efficiency (DE) and Coefficient of Variation (CV). Based on the results, design efficiency (DE) of both models exceeds 85% which indicate that the designs are acceptable. In addition, coefficient of variation (CV) is used to validate the consistency of mobile phone housing (back cover) design. Based on the computed CV, improvement design has the lower percentage compared to the existing design, hence improvement design has better stability, reliability and quality. Therefore, this research indicates that the utilization of feature recognition in redesigning the mobile phone’s back cover has improved the surface appearance, structural safety, product quality and performance of mobile phone’s back cover.

Actions (login required)

View Item