Stable Domains

The Model

The model represents a chemical plant that has a replacement value of $444 millions. The plant employs 91 mechanics who complete approximately 500 work orders per week. The plant operates at an average of 83.5% of full capacity but could sell more product if the plant ran better.

The model was built during a one year process and contains dynamic relationships that characterize the maintenance operation. The data for the model was drawn from internal DuPont reports, benchmarking studies, maintenance literature, interviews, and managerial judgment. The model is organized around the flow of equipment. The equipment can flow from a state of full functionality into either the Breakdown or Planned maintenance process. Equipment enters the Breakdown maintenance process when it breaks down and remains there until it is repaired. Breakdowns are caused by equipment defects that are introduced by the operation of the equipment, poor materials, poor design, or poor workmanship. The time to repair the broken equipment depends on the number of mechanics allocated to Breakdown maintenance and the productivity of the mechanics in executing repairs. Equipment moves into the Planned maintenance process when an inspection identifies a defect in the equipment. Some of the equipment inspections are required by law and are mandatory. Other inspections, typically those involved in a predictive maintenance program, are discretionary in the sense that maintenance managers determine their frequency. The inspections are valuable because they identify problems before the equipment suffers a costly breakdown. Scheduling involves setting a time when the equipment can be disconnected from the manufacturing process flow so that it can be worked on. A poor Scheduling process can cause a disconnect between inspections and repairs. Once it is taken off-line, the defective equipment can be repaired. The time to complete Planned maintenance depends on the number of mechanics allocated to Planned maintenance and the productivity of the mechanics in completing the repair. Planning is one of the factors that effects the efficiency of the mechanics in completing Planned or Breakdown maintenance. Planning refers to the process of creating an explicit plan for doing a specific task, planning increases mechanic productivity by standardizing work practices and by making sure that the materials and necessary skills are available to finish the job.

In the base case simulation, the plant does mostly Breakdown maintenance. There is almost no manpower allocated to doing discretionary inspections or to creating job plans, the maintenance strategy can be described as reactive in the sense that the maintenance organization reacts to breakdowns instead of preventing them.

Results of the Modeling

In this section, three of the maintenance programs are implemented in the simulation model. The results of the simulations are compared to the reactive maintenance strategy that is used in the base case simulation. Although the model generates a variety of performance measures, for simplicity, the simulations will be compared on the basis of plant uptime. Using other measures, such as net present value or cost, to compare the simulations does not change the basic results.

1. Planning

The first simulation implements more extensive job planning. This policy is implemented by increasing the number of job planners by reallocating seven mechanics to planning and by adding a library of plans. The library increases the productivity of the job planners by making it unnecessary to create a new plan for every job.

The rationale for increased planning is straight forward. More planning increases mechanic productivity. Higher productivity reduces the time to repair equipment and increases equipment uptime.

Just as it was in maintenance at the plant sites, the result of adding planning in the model is disappointing. Uptime increases by only 0.5%, which would not be measurable in the plants.

There are two reasons why the planning program is unsuccessful. First, in the reactive case, most of the work is breakdown work. By definition, breakdown work is difficult to plan and adding planning has a small impact on the efficiency of doing Breakdown work. Turning mechanics into planners is wasteful if the plans don't add much to productivity. Second, with a reactive strategy, the plants are typically overstaffed and there is not enough work to do on a day-to-day basis. Improving efficiency in their work causes mechanics to complete work faster when work is available but also lengthens the gaps when there is no work available. The net effect is a very small increase in mechanic productivity and uptime.

2. Scheduling

The second simulation implements a more efficient scheduling system. The first element of the scheduling program is to shorten the delay between the time a defective equipment piece is identified and the time it can be worked on. The second element of the program is to improve the scheduling system's memory. When a piece of defective equipment is identified often no action will be taken on it immediately because operations needs the equipment on-line. In this situation, the scheduling system may not remember that the equipment was defective unless there is an explicit record keeping system. The second element of the policy implements an efficient record keeping system.

The rationale for the scheduling policy is straight-forward. Better scheduling should increase the efficiency of Planned maintenance and lead to fewer breakdowns. Fewer breakdowns increases uptime. However, the results of the scheduling policy are disappointing. Up time increases by only 0.8%, which would be imperceptible at the plant.

The scheduling program fails because, in the base case, the plant is doing very little Planned maintenance. Breakdown maintenance, which is most of the work in the base case, is by definition unpredictable and almost impossible to schedule. The scheduling policy does very little to improve the efficiency of Breakdown work.

3. Predictive & Preventive Maintenance

In this policy, the frequency of equipment inspections is increased, in the base case, the frequency of inspections was one every twenty weeks on average. In the predictive and preventive program, the frequency is increased to one every two weeks. More inspections should identify equipment defects before they cause failures, fewer failures should directly increase uptime.

The predictive and preventive program is counterproductive as uptime falls by 2.4%. This surprising result is caused by the interaction of several factors. First, increased inspections draw manpower away from repair work. This would be fine if the inspections resulted in repairs that prevented breakdowns. Unfortunately, many of the inspections find defects but, without an efficient scheduling system, the inspections do not result in equipment repairs and the equipment fails while it is waiting to be scheduled. The man-hours spent on inspections are wasted for the lack of a good scheduling system. Second, some of the inspections do result in repairs but without a planning system, the repairs are done inefficiently. This increases the time to repair which decreases uptime.

4. Synergy between Policies

The analysis presented above suggests that there should be strong synergy between the maintenance policies. Model simulations reveal this to be the case. The combination of planning, scheduling, and predictive and preventive improves uptime by 4.1%, The combination of these three policies with an improved maintenance materials supply process increases uptime by 5.1%, Clearly, it is the combination of the four policies that generate the gains that were expected from a Planned maintenance process.

Overall, the analysis of the model can be distilled down to two basic conclusions. First, a structural analysis of the maintenance system demonstrates that it is unlikely that maintenance programs will be successful if they are implemented separately. Second, there is a great deal of synergy between the policies. The combination of planning, scheduling, predictive and preventive maintenance yield the expected benefits of the Planned Maintenance approach while the individual components, taken individually, produce small benefits in the long term.

Winston Ledet

Winston Ledet is a leading consultant and internationally known workshop instructor on proactive manufacturing and maintenance. He has 27 years of experience with E.I. du Pont de Nemours, serving in a variety of assignments. He is one of the creators of The Manufacturing Game® as part of his work at DuPont. Winston formed his own consulting firm, Ledet Enterprises, Inc., in 1993, using The Manufacturing Game® to help drive improvement efforts in process industries, as well as discrete part manufacturing sites around the world. 

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