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Wear Analysis of Iron Slag Reinforced Polyester Composites with Taguchi Optimization

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Języki publikacji
EN
Abstrakty
EN
In this paper, the dry sliding wear behaviour of the polyester composite reinforced with iron slag as filler was studied experimentally. The Taguchi method-based experiments were carried on pin-on-disk wear test set-up. The control factors considered for studying wear rate were sliding velocity, slag percentage and normal load applied on the member with constant sliding distance. The output performance parameters considered were coefficient of friction and weight loss. From the analysis of variance (ANOVA), it was observed that coefficient of friction is significantly affected by normal load then followed by slag content and sliding velocity. Sliding velocity plays a vital role on the weight loss, then followed by slag content and normal load. The optimal factor combination obtained was sliding velocity = 50 cm/s, slag percentage = 30 % and normal load = 4 kg. The model was validated using the set of optimal factor combinations to conduct a confirmation experiment.
Twórcy
  • Department of Mechanical Engineering, V.R. Siddhartha Engineering College, Kanuru, Vijayawada, 520007, India
  • Department of Mechanical Engineering, Rajiv Gandhi University of Knowledge Technologies, Nuzvid, Andhra Pradesh, 521202, India
  • Department of Mechanical Engineering, Rajiv Gandhi University of Knowledge Technologies, Nuzvid, Andhra Pradesh, 521202, India
  • Department of Mechanical Engineering, Rajiv Gandhi University of Knowledge Technologies, Nuzvid, Andhra Pradesh, 521202, India
  • Department of Mechanical Engineering, Rajiv Gandhi University of Knowledge Technologies, Nuzvid, Andhra Pradesh, 521202, India
  • Department of Mechanical Engineering, A.I.T.S. Tirupati, Andhra Pradesh, 517520, India
  • Department of Mechanical Engineering, GMR Institute of Technology, GMR Nagar, Rajam, Andhra Pradesh, 532127, India
Bibliografia
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b668ad96-328c-4f5d-923a-416d81bccc12
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