research centers


Search results: Found 1

Listing 1 - 1 of 1
Sort by

Article
Enhancement of Maintenance Downtime using Poisson Motivated-Taguchi Optimisation Method

Authors: Akinwale Olusegun Raji --- Sunday Ayoola Oke
Journal: AL-NAHRAIN JOURNAL FOR ENGINEERING SCIENCES مجلة النهرين للعلوم الهندسية ISSN: 25219154 / eISSN 25219162 Year: 2019 Volume: 22 Issue: 4 Pages: 294-306
Publisher: Al-Nahrain University جامعة النهرين

Loading...
Loading...
Abstract

In an original article, an addition was made to the well-known Taguchi’s methodical design literature by proposing how Poisson distribution may be incorporated into the Taguchi method for enhanced performance analysis in optimisation. While the article is recent, it was found compelling enough to apply this novel concept of Poisson distribution to a growing area of maintenance research known as maintenance downtime analysis. Consequently, this paper contributes to the expanding research neighbourhood through a Taguchi optimisation method based on Poisson distribution related to the maintenance process optimisation. A valuable method to optimise maintenance downtime was developed wherein the Poisson distribution was used to achieve the probability of maintenance downtime. An important foundation of the method is the Taguchi scheme. These elements were transformed into the factor-level design of the Poisson enhanced Taguchi scheme while the framework was tested using data from a process industry for validation. Interesting, the Taguchi's signal-to-noise quotient led to an enhanced set of limiting factors for better reliability of the system as G1H1I1J1K3. By interpretation, the following was found: downtime (204.61 mins), probability density function (0.00187), and cumulative density function (0.00776). The combination of these factors and levels will enhance maintenance downtime in the process industry as a result of their contributions. The outcome revealed the competence of the model to optimisation schemes.

Listing 1 - 1 of 1
Sort by
Narrow your search

Resource type

article (1)


Language

English (1)


Year
From To Submit

2019 (1)