Agboola, O.O. and Ikubanni, P.P. and OGUNSEMI, B.T. and IBIKUNLE, R.A. and Adediran, A.A and Kareem, B. and Akinnuli, B.O. and Osueke, C.O. (2018) Dataset for the development of a diagnostic schedule for a defective LC-195V5 CNC milling machine at FUTA central workshop. Data in Brief, 21. 1496 -1503.
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Abstract
The dataset represented in this article describe a diagnostic schedule for a defective LC-195V5 CNC milling machine using PERT. The efficiency of the technicians who repaired the CNC machine tools was measured based on fault location within the shortest possible time. A diagnostic schedule was developed which showed the sequential means of trouble shooting within a possible shortest time. Two approaches were employed. Forward Pass(FP), which involved the diagnosis from electrical parts through Computer(CNC) to mechanical components and BackwardPass(BP) which involved the diagnosis from computer component through electrical parts to mechanical parts. Three different levels of expertise (trials) were used for each of the mode of diagnosis and the time to diagnose each component part was recorded. Two separate PERT network diagrams were drawn based on the interrelationship of the component parts of the machine and their Critical Paths were determined.
Item Type: | Article |
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Subjects: | T Technology > T Technology (General) T Technology > TJ Mechanical engineering and machinery |
Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
Depositing User: | Engr. Peter Ikubanni |
Date Deposited: | 07 Dec 2018 04:05 |
Last Modified: | 07 Dec 2018 04:05 |
URI: | https://eprints.lmu.edu.ng/id/eprint/1697 |
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