Nylon 66 microcomposites with various weight percentage of titanium dioxide (TiO 2 ) were prepared by a twin screw extruder and investigated for mechanical and tribological properties.Mechanical properties of the composite such as tensile strength/modulus, flexural strength/modulus, impact, and compressive strength first showed an increase up to 6 wt% TiO 2 followed by a decrease at higher filler loading. The value of heat deflection temperature increased with the increase in wt% of TiO 2 . Sliding wear tests were performed on pin-on-disk equipment under different loads, sliding velocity, and sliding distance combinations. It was found that micro-TiO 2 -Nylon 66 composite exhibited reduced wear and coefficient of friction up to 6 wt% TiO 2 .Micro-TiO 2 at 2 wt% was most effective in improving the tribological properties of plain nylon 66. The worn surfaces were examined by scanning electron microscopy to understand the wear mechanism. The optimal combination from 2 wt% to 6 wt% micro-TiO 2 -Nylon 66 can be used depending upon the application requiring improvement in tribological or mechanical properties, respectively.
Composite of Nylon 66 with different proportions of microparticle Al2O3 were made by compounding on a twin screw extruder. The sliding wear and mechanical properties of the resulting microcomposite of 2 to 8 wt.% Nylon 66–Al2O3 were investigated. The study of sliding wear under different loads, velocity and sliding distance combinations was done using pin-on-disk equipment. The results show that wear rate reduces with addition of microparticles and lowest wear is exhibited by 2 wt.% Al2O3–Nylon 66 composite. The lowest friction coefficient is also observed for 2 wt.% Al2O3-Nylon 66 composite and the value increases with increasing load, sliding velocity and sliding distance. The mechanical properties such as flexural strength and modulus, tensile strength and modulus, compressive and impact strength improved with the addition of alumina and maximum values are observed for 6 wt.% composite. The heat deflection temperature of the microcomposite increased with increasing weight % of alumina. Scanning electron microscopy images of the worn surfaces were examined to understand the wear mechanism. The improved mechanical and tribological properties of Nylon 66–Al2O3 composite will enhance the application of plain Nylon 66.
In injection moulding process, the productivity is largely dependent on the cycle time and its optimisation plays a vital role. Productivity improvement in injection moulding is possible by undertaking scientific moulding using the modern process improvement and statistical techniques. This paper describes the improvement in the productivity of injection moulded polycarbonate energy meter base wherein Moldflow software is used to predict the injection pressure, filling time, clamping force, etc. and the design of experiments is carried out to know the impact of various parameters on sink mark, cycle time and overall quality indexes. The experimentation is done using the predicted values obtained from Moldflow analysis and an orthogonal array is employed for optimising injection time followed by pack time and cooling time. Significant improvements are achieved in reducing the cycle time from 51.5 seconds to 42.0 seconds using the systematic optimised processing parameters and thus increasing productivity.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.