An Efficient Failure-Based Maintenance Decision Support System for Smalland Medium Industries - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 201

provides tremendous benefit to maintenance. She identified salient characteristics of CMMS
by showing that information technology investment has a positive correlation to company
profitability and competitiveness. She also developed information technology tools based on
a company's factors of goal and purpose.
Despite providing significant characteristics of CMMS, which may fit in with the needs of
the industries, Labib (2004) also discovered that the majority of available CMMS in the
market lack decision support for management. Last but not least, the fourth crucial review,
highlighted by Sherif et al. (2008). They managed to embed DSS into CMMS as an advanced
software engineering approach. DSS constitutes a class of computer-based information
systems, including knowledge-based systems that support decision-making activities. A
computer program is written using available maintenance techniques to automate the
analysis and results. The program is executed in sub-procedures in CMMS as a DSS module.
Sherif et al. (2008) synthesized DSS with problem-solving in concrete bridge decks
maintenance activities. They proposed different decisions for different types of repair, i.e.
shallow repair, deep repair, protective repair, non-protective repair, and deck replacement.
All decision-makers must consider the cost of repair when making any recommendation.
Sherif et al. (2008) also deliberated on how DSS is used to model human reasoning and the
decision-making process for concrete bridge decks. At the end of the study, they concluded
that buying sophisticated hardware or software is not the complete answer. However,
justification on middleware software, and an object-oriented system by integrating some
maintenance techniques into the DSS, is another potential area to consider. There are
various available techniques in maintenance that can be programmed into CMMS and can
measure maintenance activities. The techniques are elaborated on in the next section.

4.3 Decision support system and optimization techniques
DSS gathers and presents data from a wide range of sources in a way that can be interpreted
by humans. Important features of DSS are given as follows (Williams and Sawyer, 2006):
i. lnputs and outputs;
ii. Assist tactical-level managers in making tactical decisions; and
iii. Produce analytical models, such as mathematical representation of a real system.
A quantitative approach in the DSS model allows maintenance manager to play a simulation
what-if game to reach decisions. They can simulate certain aspect of the organization's
environment in order to decide how to react to a change in the conditions affecting it. By
changing the hypothetical inputs to the maximum and minimum levels, the managers can
see how the model's outputs are affected. There are four aspects to maintenance
optimization models, as follows (Amik and Deshmukh (2006)):
i. Description of a technical system, its function and importance;
ii. Modeling of the deterioration of the system in time and possible consequences for this
system,
iii. Description of the available information about the system and action open to
management and
iv. Objective function and an optimization technique, which helps in finding the best
practice.
An efficient DSS for SMI should have some real time data analysis capabilities, and be able
to query from the database, perform the calculation and provide decisions such as:
i. Which machines should go for FBM, fixed time maintenance, design-out maintenance,

condition-based maintenance, preventive maintenance, etc.