02371nmm a2200313 a 4500 vtls000098461 KUKTEM 20251117113333.0 161214s2016 my fq d 001 0 eng d THE0005124(Local) 201905131525 hanafiah 201712150934 fateeha 201612141239 saini UMP FKP .S46 2016 r Bc. CD 10455 Seow, Xiang Yuan Prediction of remaining useful life of an end mill cutter [electronic resource] / Seow Xiang Yuan Kuantan, Pahang : UMP, 2016 1 computer disc : digital data ; 12 cm. Faculty of Manufacturing Engineering Theses Gred A Project Paper (Bachelor of Engineering in Manufacturing Engineering (Hons.)) -- Universiti Malaysia Pahang – 2016 This thesis presents a comparison between methods for tool life prediction. The main objective of the thesis is to have an accurate prediction of the RUL and select the best method for prediction. An experiment has been conducted using Kistler dynamometer and Olympus metallurgical microscope on a HASS VF-6 milling machine to acquire the sensor force signals and actual tool wear respectively. The force signal gives the significant statistical features of the data. The features are extracted using statistical measure and reduced using a stepwise regression model. The prediction methods are Support Vector Regression and Neural Network. Both the models are trained using the MATLAB software. The results of the models are compared against each other to select the best method. Moreover, the methods are also applied on data taken from PHM Society. This data serves as a preliminary result and fundamental knowledge for my own experiment. The models trained in this project are compared with the existing models. These results show that the proposed methods are suitable for predicting the remaining useful life. Item in PDF format Faculty of Manufacturing Engineering Dissertations Universities and Colleges Dissertations Theses http://ecollib.ump.edu.my/id/eprint/4031 Access in library only 0 0 0 1 20000 20000 2019-09-04 0 FKP .S46 2016 r Bc. | CD 10455 0000115970 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 6960 6966 VTLSSORT0080*0200*0400*0900*0901*1000*2450*2600*3000*5000*5001*5020*5200*5380*6100*6500*6501*8560*9992