RP2U

Repositori Publikasi Penelitian Universitas Syiah Kuala

Data Publikasi Buku Belum Ada!!

1. TRIZ Approach for Designing a New Assisted Tooling for Dimple Structure Fabrication . https://jmeche.uitm.edu.my/index.php/home/journal/special-issues/frontiers-in-sustainable-energy-research-for-humanity2017
2. A Review of the Milling Process to Fabricate a Dimple Structure . https://jmeche.uitm.edu.my/index.php/home/journal/special-issues/frontiers-in-sustainable-energy-research-for-humanity2017
3. Cutting tool wear classification and detection using multi-sensor signals and Mahalanobis-Taguchi System. http://www.sciencedirect.com/science/article/pii/S00431648173030952017
4. Monitoring the Flank Wear using Piezoelectric of Rotating Tool of Main Cutting Force in End Milling. http://library.utm.my/digital-resources-2/utm-open-e-journals/2016
5. Development and testing of an integrated rotating dynamometer and tool holder for milling process. http://www.sciencedirect.com/science/article/pii/S0888327014003069.2015
6. Parameters affecting the extraction process of Jatropha curcas oil using a single screw extruder. http://journals.itb.ac.id/index.php/jets/article/view/389.2015
7. Performance of uncoated and coated carbide tools in turning FCD700 using fem simulation. http://w.ijsimm.com/Full_Papers/Fulltext2015/text14-3_416-425.pdf.2015
8. Flank wear and I-kaz 3D correlation in ball end milling process of Inconel 718. http://jmes.ump.edu.my/images/Volume_9/7_tahir%20et%20al.pdf2015
9. A Comparative Study of I-kaz Based Signal Analysis Techniques: Application to Detect Tool Wear during Turning Process. http://www.jurnalteknologi.utm.my/index.php/jurnalteknologi/article/view/2704.2014
10. Prediction of Tool Wear for Ball End Nose in Milling Inconel 718 Using a Feed Forward Back Propagation Neural Network . www.ajbasweb.com 2014
11. I-kazTM-Based Analysis of Cutting Force Signals for Tool Condition Monitoring in Turning Process. http://www.ttp.net/1660-9336/EditorialBoard.html2014
12. A Review of Sensor System and Application in Milling Process for Tool Condition Monitoring. http://maxwellsci.com/jp/abstract.php?jid=RJASET&no=411&abs=20.2014
13. Design and Analysis of Single Screw Extruder for Jatropha Seeds Using Finite Element Method. http://maxwellsci.com/jp/abstract.php?jid=RJASET&no=411&abs=21.2014
14. A Wireless System and Embedded Sensors on Spindle Rotating Tool for Condition Monitoring. http://www.ingentaconnect.com/content/asp/asl/2014/00000020/F0030010/art00020?token=003b17f066952ed41333c4a2f7a6c6a4d574067477a6b34734f6d4e2224.2014
15. Performance of green machining: a comparative study of turning ductile cast iron FCD700. http://www.sciencedirect.com/science/article/pii/S0959652614001759.2014
16. The Application of I-kazTM-Based Method for Tool Wear Monitoring using Cutting Force Signal . http://www.sciencedirect.com/science/article/pii/S18777058130206142013
17. Online tool wear prediction system in the turning process using an adaptive neuro-fuzzy inference system. http://www.sciencedirect.com/science/article/pii/S1568494612005273.2013
18. Development of an Adequate Online Tool Wear Monitoring System in Turning Process Using Low Cost Sensor. http://www.ingentaconnect.com/content/asp/asl/2012/00000013/00000001/art00133.2012
19. Relationship Between Measurement of Cutting Force and Sensor Location in Turning Process. http://www.penerbit.utm.my/cgi-bin/bi/jt/index.cgi?id=se59k_2.2012
20. Monitoring online cutting tool wear using low-cost technique and user-friendly GUI. http://www.sciencedirect.com/science/article/pii/S00431648110008712011
21. Online tool wear monitoring using portable digital assistant (PDA). http://www.academicjournals.org/IJPS/index.htm.2011
22. Determination of sensor location for cutting tool deflection using finite element method simulation. http://pic.sagepub.com/content/226/9/2373.abstract.2011
23. Online Cutting Tool Wear Monitoring using I-kaz Method and New Regression Model. http://www.scientific.net/AMR.126-128.7382010

Data Publikasi Paten Belum Ada!!