A Costing Analysis For Decision Making Grid Model In Failure-Based Maintenance
In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful de...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Advances in Decision Sciences
2011
|
| Subjects: | |
| Online Access: | http://eprints.utem.edu.my/id/eprint/11587/1/Burhanuddin2011_A_Costing_Analysis_for_Decision_Making_Grid_Model_in_Failure-Based_Maintenance.PDF http://eprints.utem.edu.my/id/eprint/11587/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In current economic downturn, industries have to set good control on production cost,
to maintain their profit margin. Maintenance department as an imperative unit in industries should
attain all maintenance data, process information instantaneously, and subsequently transform it
into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid
model is used to identify strategies for maintenance decision. However, the model has limitation
as it consider two factors only, that is, downtime and frequency of failures. We consider third
factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce
the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa
model and Decision Making Grid methods are used in this study to reveal some underlying risk
factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that
is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two
variables, frequency of failure and downtime in the analysis. This paper introduces third variable,
repair cost for Decision Making Grid model. This approaches give better result to categorize the
machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected
data from one of the food processing factories in Malaysia. From our empirical result, Machine C,
Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though
their frequency of failures and downtime are less than Machine B and Machine N, based on the
costing analysis. The case study and experimental results show that the cost analysis in Decision
Making Grid model gives more promising strategies in failure-based maintenance. Conclusions.
The improvement of Decision Making Grid model for decision analysis with costing analysis is
our contribution in this paper for computerized maintenance management system. |
|---|