Quarter 3, 2002:  Volume 3, Issue 2

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Objective(s)
The primary objective of this FRED report is to identify an opportunity to improve and raise the baseline of acceptable reliability levels of the production equipment. This reliability growth can only be accomplished through root cause analysis and then by engineering a sound, verifiable fix.

Introduction
The following report represents an Availability study of the X202 Front Structure Station 003 in the Jaguar Castle Bromwich Plant. ReliaSoft’s Weibull++ MT and BlockSim MT (version 1) software applications were used to produce the FRED charts, as prescribed by Point 1 of the Ford Corporate R&M specification.

Methodology
The raw data set used was from the equipment fault detail report of POSMON (the facility’s event tracking system) beginning 07:30 on 28th May 2002 and ending 12:00 on 19th July 2002. The study included all components in Station 003, as shown in the BlockSim block diagram in Figure 2. During this period, 882 events were recorded in the specified shift pattern. Events were analyzed at three levels: Station, Component (e.g. Rivet Gun, Proximity) and Fault Code.

To make the POSMON downtime log readable by Weibull++ MT, some pre-processing was required. First, the data set was filtered to remove any events that fell outside the specified shift pattern and then events were removed that had a continuous duration over planned downtime. The data set was then entered into the Weibull++ data entry form. For the Weibull analysis, the Rank Regression estimation method was used because of the completeness of the data. Time-to-failure and time-to-repair (or failure duration) distributions with their parameters were then used to build a reliability block diagram in BlockSim. Within BlockSim, a simulation was run for 10,000 minutes (approximately 2 weeks of production) with results calculated for instantaneous availability 10 times. The simulation resolution was set to run 100 inner loops and 10 outer loops. This means that 100 simulation points were generated for each reliability entity and results were returned for each of the 100 runs; then the simulation returned results 10 times at system level, each time with a new stream of random numbers for the simulation points. This yielded 10 different system reliability values and 100 reliability entity values. The system reliability at the specified time returned by the simulation was the average of these 10 reliability values. The simulation results were used to estimate MTBF, MTTR and Availability at the System level.

Similar steps were taken to work down the availability hierarchy from Component level to Fault Code level, as shown on the FRED chart in Figure 1.

Results
Figures 1 through 4 demonstrate the results of the analysis.

Figure 1: Front Structure Station 003 FRED Tree

Figure 2: Front Structure Station 003 Block Diagram

Figure 3: Front Structure Station 003 Pareto

Figure 4: Front Structure Station 003 Rivet Gun FRED Tree

Conclusions
The immediate opportunity for reliability improvement follows a critical path of Component = Proximity (98.53% availability) to Fault Code = 102062 waiting part present (98.5% availability).

The study has highlighted the importance of having data in electronic format that can be operated on for pre-processing before entry into the analysis software. The study also demonstrates the value of the ReliaSoft software for performing the analysis and creating graphical representations of the output. Finally, the study illustrates the value of automated analysis to point out the dominant areas and sources of failure as an aid to prioritize reliability improvement efforts.

For Comau Estil UK’s throughput simulation model, the most easily understood input would be the MTBF from the FRED tree generated by BlockSim. It would be preferable to use MCBF, which represents the failure frequency based on station/component busy time.