Attempts to develop a model of maintenance decision making using the analytic hierarchy (AHP). Describes problems in maintenance arising from not having clear criteria and not having robust decisions with which to maintain failing equipment. The objective being to develop a dynamic and adaptable maintenance system that utilises existing data and supports decisions accordingly. Proposes a three-stage system that can handle multiple criteria decision analysis, conflicting objectives, and subjective judgements. Moreover, the methodology facilitates and supports a group decision-making process. This systematic, and adaptable, approach will determine what specific actions to perform given current working conditions. The first stage involves identifying the criteria upon which engineering personnel wish to formulate a maintenance decision, or action. The second stage is to prioritise the different criteria by implementing a multiplecriteria evaluation method. Finally, based on different criteria, machines are ranked according to criticality. This is followed by an analysis of failures in a graphical and a hierarchical format.
In order to be competitive and progress to a state of excellence in
manufacture, companies are currently experiencing change. Decisions
have to be made about the best way forward, and some insight into the
possible outcomes is desirable. There is a small but growing awareness
among British manufacturing companies that simulation could aid this
insight, but potential users face the problem of evaluating and
selecting from the many proprietary systems, the one which best matches
their requirements at some preferred cost. Selection is made more
difficult by continual updates and modifications to systems and by new
software suppliers entering the market. Uses a research case study as
the vehicle for proposing a framework for assessment and selection of
simulation systems involving the use of the Analytic Hierarchy Process
(AHP). Illustrates how this technique was used to make a system
selection which matched a company′s selection criteria.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.