Browse By Repository:

 
 
 
   

Prediction On The Reliability Of Glove Dipping Machine Using Weibull Distribution

Mohamad Nor, Dalila Basirah (2017) Prediction On The Reliability Of Glove Dipping Machine Using Weibull Distribution. Project Report. UTeM, Melaka, Malaysia. (Submitted)

[img] Text (24 Pages)
Prediction On The Reliability Of Glove Dipping Machine Using Weibull Distribution.pdf - Submitted Version

Download (631Kb)

Abstract

The aim of this research is to predict the reliability of the glove dipping machine using Weibull distribution. This investigation involved two type of machines which are 4/4 Gammex Pf (machine 4/4) and 4/3 Gammex Pf (machine 4/3). The data is collected from Ansell Sdn. Bhd, and then tabulated in Excel Software before analyse by using Minitab Software. The Minitab Software shows the graph plot probability and also hazard rate of two machines. From the result of the analysis, this study can predict the condition of the machine which is good to keep (do the maintenance) or not worth to keep. The MTTR and MTTF analysis is carried out to estimate the reliability of these two machine. In addition, the profit loss of the machine can be predict based on its breakdown time. The result shows that 4/3 Gammex Pf (machine 4/3) has the highest reliability compared to 4/4 Gammex pf. The mean time to failure for machine 4/3 Gammex pf (machine 4/3) is high and while the mean time to repair rate for 4/3 Gammex Pf (machine 4/3) is low. The total lost for 4/3 Gammex Pf (machine 4/3) is also low compare to 4/4 Gammex Pf (machine 4/4).

Item Type: Monograph (Project Report)
Uncontrolled Keywords: Industrial equipment - Maintenance and repair, Machinery - Maintenance and repair
Subjects: T Technology > T Technology (General)
T Technology > TJ Mechanical engineering and machinery
Divisions: Library > Projek Sarjana Muda > FTK
Depositing User: Mohd Hannif Jamaludin
Date Deposited: 30 Nov 2018 02:51
Last Modified: 30 Nov 2018 02:51
URI: http://eprints.utem.edu.my/id/eprint/22119

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year