A Rcm Strategy
Content
Computersind.EngngVoL 31,No. I/2,pp. 241-244, 1996
CopyrightO 1996ElsevierScienceLtd
Printedin GreatBritaia.All fightsreserved
]Pergamon
S0360-8352(96) 00121-0
o36o-~52/~ $15.00+0.00
A RELIABILITY CENTERED MAINTENANCE STRATEGY
FOR A DISCRETE PART MANUFACTURING FACILITY
W. Pujadas and F. Frank Chen
Dept. of Industrial & Systems Engineering
Florida International University
University Park, ECS 442 Miami Florida 33199
Abstract- A specialized maintenance decision support system based on Reliability Centered Maintenance (RCM) and the US
dept. Of Defense's Failure Mode, Effect and Criticality Analysis (FMECA) has been developed. It was constructed using a
modular approach which uniquely integrates the virtues of RCM and FMECA to perform the failure analysis function. A
Logic Tree Analysis (LTA) module supports the decision process by performing Cost and Maintainability evaluation to
promote the most appropriate maintenance tasks. The Maintenance Planning Module applies "Theory of Constraints" to fit
tasks into the production schedule. Apart from a conventional focus on addressing operational failure modes, it takes
environmental impact and human safety concerns into perspective in developing tasks directed at achieving higher levels of
equipment availability and effectiveness. Ultimately, it contributes to higher quality product manufactured at a significantly
lower overall cost. Initial field test results for Miami, Florida based manufacturing system are reviewed.
Keywords: Reliability Centered Maintenance (RCM); Maintenance Planning; Performance Measures; Failure Analysis.
I INTRODUCTION
here has been a rekindling of interest in
maintenance practice over the last twenty
years [1]. The "F/x it when it breaks"
philosophy was common through the pre-World
War II era. It was in fact an adequate
maintenance strategy for the robust, overdesigned, and simply constructed equipment
which inherently possessed high reliability [2].
Following this era, the well-known Preventive
Maintenance (PM) practice proliferated. As the
name infers, PM aims at performing maintenance
before failure occurs.
There are at least six factors which identify
the unique requirements of today's Discrete Part
Manufacturing System (DPMS). These have been
translated into design objectives for the
development of a superior maintenance strategy.
A. Performance Measurement
This class of inter-dependent and
synchronized production systems require a range
of quantitative performance measures such as
Reliability Availability and Effectiveness to track
the impact of the new strategy. Flexible
Manufacturing Systems (FMS), and other
advanced or automated manufacturing systems
are characteristic of this class.
B. "Just In Time" Environments
Today's manufacturing sector is characterized
by separate groups of discrete part manufacturers
T
241
and downstream assembly plants. The majority of
the entire industry now employ the modern "Just
In Time" (JIT) inventory management systems.
Consequently, maintenance strategies must adjust
for this closer production control.
C. Focus on Functionality not Operability
A misdirected interest merely in keeping
equipment operational, has neglected functional
requirements [3]. The result has been
maintenance efforts which fail to maximize plant
effectiveness. A new maintenance design focus on
functionality, aims at producing high quality and
low scrap at a production rate which matches the
equipment design capability.
D. Environmental Impact & Human SafeO"
The US Department of Labor Occupational
Safety and Health Administration (OSHA) are
now more actively enforcing adherence of
industry to environmental and human safety
regulations. An increased awareness to this new
dimension must be reflected in task generation.
E. Systematic Documentation for Auditing
Most PM task lists are still being developed in
an ad hoc way using historical failures and
intuitive guidance [3]. The new strategy must
incorporate a lucid documentation system to
support an audit mechanism for review, query
and justification of tasks.
242
19th International Conference on Computers and Industrial Engineering
F. Cost Effectiveness
The advent of world-wide open market
policies has resulted in stronger economic
competition among modem DPMS.
Correspondingly, newly developed maintenance
strategies must be more cost effective than
before.
Research towards the solution of the
multifaceted maintenance problem has led to the
proposed model of the Decision Support System.
I!. RELIABILITY CENTERED MAINTENANCE
Reliability Centered Maintenance (RCM)
refers to a scheduled maintenance program
designed to realize the inherent reliability
capabilities of equipment [2]. It originated in the
Air Transport Industry in 1974. By its inherent
emphasis on reliability, interest in its application
soon spread to the other areas.
Four basic scheduled maintenance tasks are
defined by RCM to avert functional failures,
usually evident to operating crews, potential
failures, usually discovered by maintenance
crews, and hidden failures of redundant systems,
only evident under test conditions.
1. On-condition inspection of items to find and
correct any potential failures.
2. Rework at or before some specified age limit.
3. Discard at or before some specified life limit.
4. Failure finding inspections of a hidden function
items to correct functional failures.
The strategy is complemented by a yes/no
decision diagram termed The RCMII Decision
Diagram which guides the analyst through the
dominant failure modes towards one or more
appropriate scheduled maintenance tasks.
Two fundamental attributes qualify RCM as a
superior alternative for DPMS maintenance.
* It aims to address the maintainability of the
integrated system's function rather than
operation of individual equipment items [2_].
o A contradiction of the traditional theory
behind generation of P M tasks which were
premised on the false notion that scheduled
overhaul or replacement was sufficient to
prevent most of, if not all, failure modes.
The latter stems from the fundamental
conclusion of MIL-STD-756, [7] which revealed
that 89% of manufacturing equipment cannot
benefit from a limit on their operating age.
Therefore overhaul or replacement time control
could not form the basis of an effective
maintenance strategy.
HI. OVERVIEW OF THE DECISION
SUPPORT SYSTEM
Five basic modules shown in Figure 1 contribute
to the maintenance decision support system.
A. System Decomposition Module.
B. System Evaluation Module.
C. Failure Analysis Module.
D. Logic Tree Analysis Module.
E. Maintenance Planning Module.
LEGEND
[
~
BLOCK
/ ( ~ DECISION.LOCK
FIGURE 1
PROPOSED MAINTENANCE DECISION
SUPPORT SYSTEM MODEL
The output of the system is a prioritized
maintenance task list and schedule of activities.
A Maintenance Information System (MIS)
supports the basic function of the modules.
A. System Decomposition Module:
The system decomposition module executes
the first stage of the analysis. Figure 2 illustrates
the hierarchical structure resulting from the
decomposition. The functionally independent
subsystems of each unit are identified, and this
sets the framework for system evaluation.
svsvwa~wt
1
r/j
¢ ~ A L EXECUTIONSTEPS:
2
i n d e n t subsystemsof eachitemof equipment
UsemaJntemmcepiddims andfiJure himo~to decompose
3.
funcdonM subsystem imo iu key opersdnll dements
Begine~cutionof die SystemEv~umionmodule.
FIGURE 2
AN EXAMPLE SYSTEM DECOMPOSITION MODULE
=!
19th International Conference on Computers and Industrial Engineering
B.
System Evaluation Module:
This module generates a series of meaningful
operational and maintenance system performance
measures. The procedure is repeated at regular
intervals to focus the improvement process, and
trend improvements derived from the application
of the strategy. This module serves a major role
in the continuous improvement feedback loop.
A combination of quantifiable business and
functional performance measures are applied:
•
EFFECTIVENESS= (Availability) x
(Performance rate) x (Quality rate).
where:
Performance rate = (Theoretical cycle time x
processed amount/~__.,~_~iproduction time) x 1 0 0 ~
Quality rate = Actual prime production/total
productto& x 100%
According to Nakajima [9], effectiveness is an
operating performance measure which combines
availability, productivity, and quality rate, into a
single quantitative measure in order to evaluate a
system's performance.
Availability (system/equipment) is the
probability that the system or individual item of
equipment is operational so that it will achieve
the objectives for which it was developed.
There are several commonly used measures of
availability. "Achieved Availability [8]" most
realistically matches this production
environment where support conditions exist, and
the logistic and administrative downtimes are
minimal.
Aa=
MTBM
MTBM + M
where MTBM = Mean Time Before Maintenance, and
M = Mean downtime considotng both Mean Time To
Repair (MTTR) and Preventive Maintenance Time.
•
•
•
•
•
Maintenance cost as a percent o f total sales.
Maintenance cost per unit of output.
Total downtime (all causes) as a percentage
of total production time.
Unplanned maintenance downtime as a
percent o f total production time.
Ratio of planned maintenance hours to
unplanned maintenance hours.
C. Failure Analysis Module:
This module provides a systematic means of
maintenance task development and
documentation. For each subsystem identified by
the "System Decomposition Module," a
methodology is applied to determine the most
critical components, those which have hidden
functions, and those whose failures have the most
243
severe safety repercussions. Next, a range of
viable task options is generated against each
identified failure mode. This methodology has
extracted the fundamental task generation
rationale of the RCM II decision diagram, and
integrated it with the Failure Mode, Effects and
Criticality Analysis (FMECA) technique [ 10].
Apart from its strategic and traceable approach,
an added advantage is that it identifies cases
where no applicable effective task could be
found, and addresses failure avoidance by design
correction.
D. Logic Tree Analysis(LTA) Module:
The Failure Analysis module provides a "wellcharacterized" input of failure modes and a range
of possible maintenance tasks. This module
presents an attribute oriented refinement strategy
for promotion of the most appropriate task. The
approach enables justified decisions on
application of resources such as money, time, and
re-design effort. The four basic decision
facilitators of the LTA module are:
1. Maintainability evaluation,
2. Economic feasibility evaluation,
3. Hazard function matching, and
4. An expert system for selecting monitoring
devices for condition based tasks.
E. Maintenance Planning Module:
This module provides the necessary link
between the maintenance strategy and production
requirements. It performs the planning and audit
functions of the system. Task scheduling
functions of the strategy are applied here.
Its inputs are the production schedule and a
knowledge of component criticality and failure
severity from the failure analysis. The module
applies "Theory o f Constraints" to set the
framework for presenting a prioritized schedule
of maintenance tasks.
The maintenance task audit feature supports
task refinement upon execution as part of the
continuous improvement loop. Experience has
shown that at this stage, valuable task refinement
can be achieved by contributions of maintenance
personnel after task execution. The task audit
feature thus covers any issues overlooked during
execution of the task development modules.
Maintenance Information System (MIS)
The MIS :ommunicates with, and supports
the functions of the basic modules. It contains
separate databases which store failure history
•records between separate instances of system
evaluation. Its work order and inventory
management systems correspond with the
244
19th International Conference on Computers and Industrial Engineering
maintenance planning module in order to develop
a feasible maintenance schedule.
IV. APPLICATION EXAMPLE
A field survey is being performed to test the
practicality and effectiveness of the decision
support system. An electronic printed circuit
board (PCB) manufacturing facility was
evaluated by executing the first and second
modules. Initial results of the System Evaluation
module execution are illustrated in Table 1.
TABLE
INITIAL
SYSTEM
NO
1
1.1
1
RESULTS
EVALUATION
SUMMARY
PERFORMANCE MEASURE
• MAINTENANCE EFFECTIVENESS
EQUIPMENT ACHIEVED AVAILABILITY
VALUE
69.14%
85%
1 .I .1
MEAN TIME BETWEEN FAILURE
3 1 . 8 Hr$
1.1.2
MEAN TIME TO REPAIIq
1.02 H i s
1.2
PERFORMANCE RATE
1.3
QUALITY CONFORMANCE RATE
83%
98.40%
2
MAINTENANCE COST AS A % O f SALES
0.67%
3
MAINTENANCE COST PER UNIT OUTPUT
$0.0446
4
TOTAL DOWNTIME IALL CAUSESI AS A % OF TOTAL
PRODUCTION
10.63%
5
UNPLANNED MAINTENANCE DOWNTIME AS A % OF TOTAL
PRODUCTION
6
RATIO OF PERCENT PLANNED vs. UNPLANNED
MAINTENANCE HOURS
2.46%
77%122%
Most significantly, these results show that
although the rate of quality products is reasonably
close to the industry standard, the low values of
availability and performance rate, severely
impact maintenance effectiveness. A low value of
69.14% was seen compared to the industry's
standard of 85%.
A value of 2.46 % unplanned maintenance
downtime of total production time may easily go
unrecognized. This however reflects an actual
value of 51.2 b t.rs lost production per year.
These quantitative values present a datum
against which improvements resulting from the
application of the strategy could be measured. It
clearly shows that although the quality system is
performing satisfactorily, the effects of
unplanned downtime, and low performance
characteristics of equipment, significantly affect
profitability.
V. CONCLUSION
A specialized maintenance decision support
system has been presented as a strategic approach
to the maintenance task development process. A
modular approach was adopted, using the RCM
strategy which possesses ideal characteristics
[3,4and5]. Field testing is still in progress,
however the strategy shows a significant promise.
There are three distinct benefits of this
approach over traditional RCM. First, the system
decomposition enables failure analysis to begin at
the functional sub-system level rather than on the
multitude of individual elemental components.
This significantly reduces the burden of the
failure analysis exercise. Second, the combination
of FMECA with RCM in the failure analysis
module, enables a more detailed investigation of
each failure mode. Third, the incorporation of a
maintenance planning module supersedes the
great majority of current strategies which fail to
link the developed task list with the production
requirements of the facility. In this way, the
system benefits from tasks with higher likelihood
of execution than being put off and eventually
neglected due to production priorities.
There is however a price to pay for
implementation of this reliability improvement
strategy. An increased burden falls on the
professional team particularly during execution of
the system decomposition and failure analysis
modules. The applicability and effectiveness of
tasks rely heavily on team skills at these stages,
and so it is imperative that the best resources be
applied and sustained over this important phase.
Finally, the direction for future work lies in
development of intelligent LTA and maintenance
planning, modules. Coupled with a computerized
MIS the fully developed strategy is potentially
the complete solution to the DPMS maintenance
problem. Field testing is however the priority at
this stage of the research.
REFERENCES
[I] Moubray,John., 1991,Reliability-Centered
Maintenance, Butterworth-HeinmannLtd.
[2] Nolan, F. Stanley,and Heap, HowardF.,1978,
"ReliabilityCenteredMaintenance,"National Technical
Information Service Report, # A066-579, 1978.
[3] Mac Smith,A., 1992,"Preventive-MaintenanceImpact
on PlantAvailability,"1992 Proceedings Annual
Reliability and Maintainability Symposium, pp177-180.
[4] Shimizu,S., Sugawara,M., Sakurai,T., Mori,T. and
Saikawa,K., 1993,"DecisionMakingSupport Systems
for ReliabilityCenteredMaintenance,"Journal of
Nuclear Science and Technology. 30(6), pp.505-5i 5.
[5] Mac Smith,Anthony.,1987,"UsingReliability-Centered
Maintenanceto OptimizePM Programs,"Nuclear Plant
Journal, September-October 1987pp.19-22.
[6] Elfont,Mark and Procaccino,Vincent, 1992, "Measures
of Effectivenessas Appliedto MaintenancePractices,"
Naval Engineers Journal, 104(3), pp 135-140.
[7] Departmentof Defense.,M1L-STD-756,"Applicationof
ReliabilityCenteredMaintenanceto NavalAircraft,
WeaponSystems,and SupportEquipment."
[8] Ireson,W.Grant.,and Coombs,ClydeF., 1988,
Handbook of Reliability Engineering and Management,
Mc GrawHill, Inc.
[9] Nakajima,Seuchi., 1988, Total Productive Maintenance,
ProductivityPress.
[10] Departmentof Defense.,MIL-STD-1629ANOV. 1980,
"ProceduresFor Performinga FailureMode,Effectsand
CriticalityAnalysis."
CopyrightO 1996ElsevierScienceLtd
Printedin GreatBritaia.All fightsreserved
]Pergamon
S0360-8352(96) 00121-0
o36o-~52/~ $15.00+0.00
A RELIABILITY CENTERED MAINTENANCE STRATEGY
FOR A DISCRETE PART MANUFACTURING FACILITY
W. Pujadas and F. Frank Chen
Dept. of Industrial & Systems Engineering
Florida International University
University Park, ECS 442 Miami Florida 33199
Abstract- A specialized maintenance decision support system based on Reliability Centered Maintenance (RCM) and the US
dept. Of Defense's Failure Mode, Effect and Criticality Analysis (FMECA) has been developed. It was constructed using a
modular approach which uniquely integrates the virtues of RCM and FMECA to perform the failure analysis function. A
Logic Tree Analysis (LTA) module supports the decision process by performing Cost and Maintainability evaluation to
promote the most appropriate maintenance tasks. The Maintenance Planning Module applies "Theory of Constraints" to fit
tasks into the production schedule. Apart from a conventional focus on addressing operational failure modes, it takes
environmental impact and human safety concerns into perspective in developing tasks directed at achieving higher levels of
equipment availability and effectiveness. Ultimately, it contributes to higher quality product manufactured at a significantly
lower overall cost. Initial field test results for Miami, Florida based manufacturing system are reviewed.
Keywords: Reliability Centered Maintenance (RCM); Maintenance Planning; Performance Measures; Failure Analysis.
I INTRODUCTION
here has been a rekindling of interest in
maintenance practice over the last twenty
years [1]. The "F/x it when it breaks"
philosophy was common through the pre-World
War II era. It was in fact an adequate
maintenance strategy for the robust, overdesigned, and simply constructed equipment
which inherently possessed high reliability [2].
Following this era, the well-known Preventive
Maintenance (PM) practice proliferated. As the
name infers, PM aims at performing maintenance
before failure occurs.
There are at least six factors which identify
the unique requirements of today's Discrete Part
Manufacturing System (DPMS). These have been
translated into design objectives for the
development of a superior maintenance strategy.
A. Performance Measurement
This class of inter-dependent and
synchronized production systems require a range
of quantitative performance measures such as
Reliability Availability and Effectiveness to track
the impact of the new strategy. Flexible
Manufacturing Systems (FMS), and other
advanced or automated manufacturing systems
are characteristic of this class.
B. "Just In Time" Environments
Today's manufacturing sector is characterized
by separate groups of discrete part manufacturers
T
241
and downstream assembly plants. The majority of
the entire industry now employ the modern "Just
In Time" (JIT) inventory management systems.
Consequently, maintenance strategies must adjust
for this closer production control.
C. Focus on Functionality not Operability
A misdirected interest merely in keeping
equipment operational, has neglected functional
requirements [3]. The result has been
maintenance efforts which fail to maximize plant
effectiveness. A new maintenance design focus on
functionality, aims at producing high quality and
low scrap at a production rate which matches the
equipment design capability.
D. Environmental Impact & Human SafeO"
The US Department of Labor Occupational
Safety and Health Administration (OSHA) are
now more actively enforcing adherence of
industry to environmental and human safety
regulations. An increased awareness to this new
dimension must be reflected in task generation.
E. Systematic Documentation for Auditing
Most PM task lists are still being developed in
an ad hoc way using historical failures and
intuitive guidance [3]. The new strategy must
incorporate a lucid documentation system to
support an audit mechanism for review, query
and justification of tasks.
242
19th International Conference on Computers and Industrial Engineering
F. Cost Effectiveness
The advent of world-wide open market
policies has resulted in stronger economic
competition among modem DPMS.
Correspondingly, newly developed maintenance
strategies must be more cost effective than
before.
Research towards the solution of the
multifaceted maintenance problem has led to the
proposed model of the Decision Support System.
I!. RELIABILITY CENTERED MAINTENANCE
Reliability Centered Maintenance (RCM)
refers to a scheduled maintenance program
designed to realize the inherent reliability
capabilities of equipment [2]. It originated in the
Air Transport Industry in 1974. By its inherent
emphasis on reliability, interest in its application
soon spread to the other areas.
Four basic scheduled maintenance tasks are
defined by RCM to avert functional failures,
usually evident to operating crews, potential
failures, usually discovered by maintenance
crews, and hidden failures of redundant systems,
only evident under test conditions.
1. On-condition inspection of items to find and
correct any potential failures.
2. Rework at or before some specified age limit.
3. Discard at or before some specified life limit.
4. Failure finding inspections of a hidden function
items to correct functional failures.
The strategy is complemented by a yes/no
decision diagram termed The RCMII Decision
Diagram which guides the analyst through the
dominant failure modes towards one or more
appropriate scheduled maintenance tasks.
Two fundamental attributes qualify RCM as a
superior alternative for DPMS maintenance.
* It aims to address the maintainability of the
integrated system's function rather than
operation of individual equipment items [2_].
o A contradiction of the traditional theory
behind generation of P M tasks which were
premised on the false notion that scheduled
overhaul or replacement was sufficient to
prevent most of, if not all, failure modes.
The latter stems from the fundamental
conclusion of MIL-STD-756, [7] which revealed
that 89% of manufacturing equipment cannot
benefit from a limit on their operating age.
Therefore overhaul or replacement time control
could not form the basis of an effective
maintenance strategy.
HI. OVERVIEW OF THE DECISION
SUPPORT SYSTEM
Five basic modules shown in Figure 1 contribute
to the maintenance decision support system.
A. System Decomposition Module.
B. System Evaluation Module.
C. Failure Analysis Module.
D. Logic Tree Analysis Module.
E. Maintenance Planning Module.
LEGEND
[
~
BLOCK
/ ( ~ DECISION.LOCK
FIGURE 1
PROPOSED MAINTENANCE DECISION
SUPPORT SYSTEM MODEL
The output of the system is a prioritized
maintenance task list and schedule of activities.
A Maintenance Information System (MIS)
supports the basic function of the modules.
A. System Decomposition Module:
The system decomposition module executes
the first stage of the analysis. Figure 2 illustrates
the hierarchical structure resulting from the
decomposition. The functionally independent
subsystems of each unit are identified, and this
sets the framework for system evaluation.
svsvwa~wt
1
r/j
¢ ~ A L EXECUTIONSTEPS:
2
i n d e n t subsystemsof eachitemof equipment
UsemaJntemmcepiddims andfiJure himo~to decompose
3.
funcdonM subsystem imo iu key opersdnll dements
Begine~cutionof die SystemEv~umionmodule.
FIGURE 2
AN EXAMPLE SYSTEM DECOMPOSITION MODULE
=!
19th International Conference on Computers and Industrial Engineering
B.
System Evaluation Module:
This module generates a series of meaningful
operational and maintenance system performance
measures. The procedure is repeated at regular
intervals to focus the improvement process, and
trend improvements derived from the application
of the strategy. This module serves a major role
in the continuous improvement feedback loop.
A combination of quantifiable business and
functional performance measures are applied:
•
EFFECTIVENESS= (Availability) x
(Performance rate) x (Quality rate).
where:
Performance rate = (Theoretical cycle time x
processed amount/~__.,~_~iproduction time) x 1 0 0 ~
Quality rate = Actual prime production/total
productto& x 100%
According to Nakajima [9], effectiveness is an
operating performance measure which combines
availability, productivity, and quality rate, into a
single quantitative measure in order to evaluate a
system's performance.
Availability (system/equipment) is the
probability that the system or individual item of
equipment is operational so that it will achieve
the objectives for which it was developed.
There are several commonly used measures of
availability. "Achieved Availability [8]" most
realistically matches this production
environment where support conditions exist, and
the logistic and administrative downtimes are
minimal.
Aa=
MTBM
MTBM + M
where MTBM = Mean Time Before Maintenance, and
M = Mean downtime considotng both Mean Time To
Repair (MTTR) and Preventive Maintenance Time.
•
•
•
•
•
Maintenance cost as a percent o f total sales.
Maintenance cost per unit of output.
Total downtime (all causes) as a percentage
of total production time.
Unplanned maintenance downtime as a
percent o f total production time.
Ratio of planned maintenance hours to
unplanned maintenance hours.
C. Failure Analysis Module:
This module provides a systematic means of
maintenance task development and
documentation. For each subsystem identified by
the "System Decomposition Module," a
methodology is applied to determine the most
critical components, those which have hidden
functions, and those whose failures have the most
243
severe safety repercussions. Next, a range of
viable task options is generated against each
identified failure mode. This methodology has
extracted the fundamental task generation
rationale of the RCM II decision diagram, and
integrated it with the Failure Mode, Effects and
Criticality Analysis (FMECA) technique [ 10].
Apart from its strategic and traceable approach,
an added advantage is that it identifies cases
where no applicable effective task could be
found, and addresses failure avoidance by design
correction.
D. Logic Tree Analysis(LTA) Module:
The Failure Analysis module provides a "wellcharacterized" input of failure modes and a range
of possible maintenance tasks. This module
presents an attribute oriented refinement strategy
for promotion of the most appropriate task. The
approach enables justified decisions on
application of resources such as money, time, and
re-design effort. The four basic decision
facilitators of the LTA module are:
1. Maintainability evaluation,
2. Economic feasibility evaluation,
3. Hazard function matching, and
4. An expert system for selecting monitoring
devices for condition based tasks.
E. Maintenance Planning Module:
This module provides the necessary link
between the maintenance strategy and production
requirements. It performs the planning and audit
functions of the system. Task scheduling
functions of the strategy are applied here.
Its inputs are the production schedule and a
knowledge of component criticality and failure
severity from the failure analysis. The module
applies "Theory o f Constraints" to set the
framework for presenting a prioritized schedule
of maintenance tasks.
The maintenance task audit feature supports
task refinement upon execution as part of the
continuous improvement loop. Experience has
shown that at this stage, valuable task refinement
can be achieved by contributions of maintenance
personnel after task execution. The task audit
feature thus covers any issues overlooked during
execution of the task development modules.
Maintenance Information System (MIS)
The MIS :ommunicates with, and supports
the functions of the basic modules. It contains
separate databases which store failure history
•records between separate instances of system
evaluation. Its work order and inventory
management systems correspond with the
244
19th International Conference on Computers and Industrial Engineering
maintenance planning module in order to develop
a feasible maintenance schedule.
IV. APPLICATION EXAMPLE
A field survey is being performed to test the
practicality and effectiveness of the decision
support system. An electronic printed circuit
board (PCB) manufacturing facility was
evaluated by executing the first and second
modules. Initial results of the System Evaluation
module execution are illustrated in Table 1.
TABLE
INITIAL
SYSTEM
NO
1
1.1
1
RESULTS
EVALUATION
SUMMARY
PERFORMANCE MEASURE
• MAINTENANCE EFFECTIVENESS
EQUIPMENT ACHIEVED AVAILABILITY
VALUE
69.14%
85%
1 .I .1
MEAN TIME BETWEEN FAILURE
3 1 . 8 Hr$
1.1.2
MEAN TIME TO REPAIIq
1.02 H i s
1.2
PERFORMANCE RATE
1.3
QUALITY CONFORMANCE RATE
83%
98.40%
2
MAINTENANCE COST AS A % O f SALES
0.67%
3
MAINTENANCE COST PER UNIT OUTPUT
$0.0446
4
TOTAL DOWNTIME IALL CAUSESI AS A % OF TOTAL
PRODUCTION
10.63%
5
UNPLANNED MAINTENANCE DOWNTIME AS A % OF TOTAL
PRODUCTION
6
RATIO OF PERCENT PLANNED vs. UNPLANNED
MAINTENANCE HOURS
2.46%
77%122%
Most significantly, these results show that
although the rate of quality products is reasonably
close to the industry standard, the low values of
availability and performance rate, severely
impact maintenance effectiveness. A low value of
69.14% was seen compared to the industry's
standard of 85%.
A value of 2.46 % unplanned maintenance
downtime of total production time may easily go
unrecognized. This however reflects an actual
value of 51.2 b t.rs lost production per year.
These quantitative values present a datum
against which improvements resulting from the
application of the strategy could be measured. It
clearly shows that although the quality system is
performing satisfactorily, the effects of
unplanned downtime, and low performance
characteristics of equipment, significantly affect
profitability.
V. CONCLUSION
A specialized maintenance decision support
system has been presented as a strategic approach
to the maintenance task development process. A
modular approach was adopted, using the RCM
strategy which possesses ideal characteristics
[3,4and5]. Field testing is still in progress,
however the strategy shows a significant promise.
There are three distinct benefits of this
approach over traditional RCM. First, the system
decomposition enables failure analysis to begin at
the functional sub-system level rather than on the
multitude of individual elemental components.
This significantly reduces the burden of the
failure analysis exercise. Second, the combination
of FMECA with RCM in the failure analysis
module, enables a more detailed investigation of
each failure mode. Third, the incorporation of a
maintenance planning module supersedes the
great majority of current strategies which fail to
link the developed task list with the production
requirements of the facility. In this way, the
system benefits from tasks with higher likelihood
of execution than being put off and eventually
neglected due to production priorities.
There is however a price to pay for
implementation of this reliability improvement
strategy. An increased burden falls on the
professional team particularly during execution of
the system decomposition and failure analysis
modules. The applicability and effectiveness of
tasks rely heavily on team skills at these stages,
and so it is imperative that the best resources be
applied and sustained over this important phase.
Finally, the direction for future work lies in
development of intelligent LTA and maintenance
planning, modules. Coupled with a computerized
MIS the fully developed strategy is potentially
the complete solution to the DPMS maintenance
problem. Field testing is however the priority at
this stage of the research.
REFERENCES
[I] Moubray,John., 1991,Reliability-Centered
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[3] Mac Smith,A., 1992,"Preventive-MaintenanceImpact
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