Statistical analysis and optimization of milling parameters for better surface roughness with minimum cutting time in machining of Al7075 materials
Abstract
Machining of materials requires high temperature and pressure for chip removal to reproduce the raw surface. Fresh surface after machining determines the quality of the operation and give clues about the accuracy of the parameter selection. Aluminum materials used extensively in prominent sectors i.e. transportation, architecture, industrial areas, aviation, construction industry, electrical and electronics with their properties such as lightness, durability, high corrosion resistance machinability, electrical and thermal conductivity. 7075 materials are an aluminum alloy containing zinc as the primary alloying element. It has superior mechanical properties, exhibiting flexibility, good strength, toughness, and fatigue behavior. Current paper presents Al7075 milling tests were performed under varying cutting conditions (cutting speed, feed rate and cutting tool). During operations, milling times were recorded depending on the cutting parameters considering same cutting length. An average surface roughness (Ra) value was calculated after a series of measurements taken from the machined surfaces. Optimal surface quality and cutting time were determined using graphical and statistical analysis. This study aims to provide insights about overcoming the challenges in milling of aluminum alloys in terms of part quality and productivity.
Keywords
Al7075 Alloy, Surface roughness, Variance analysis, Cutting time, Cutting length
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