The Consequences of Dealing with Paper and Digital Documents
An energy company performed a study to determine how the availability of correct and intelligent technical information would contribute to the increased availability of their energy facilities. They found that facility availability was impacted by the following:
- Mean Time Between Failure (MTBF): This is also known as “Reliability.”
- Mean Time To Repair (MTTR): This is also known as “Maintainability.”
- Mean Waiting Time (MWT): This is also known as “Supportability.”
The primary factor that impacts MTBF or Reliability is maintenance. The maintenance consequences of not having correct and intelligent technical documentation are:
- Extended lead time to find information
- High risk of using information that is not up to date
- Maintenance tasks take longer to accomplish
The major factor influencing MTTR or Maintainability is the ability to repair or maintain equipment quickly and easily. And the consequences of the maintainability of having incorrect or non-intelligent content are:
- Extended lead time to find information
- Maintenance tasks take longer to accomplish
Several significant factors influence MWT or Supportability, including:
- Extended lead time to locate and purchase the correct spare parts
- Long lead time to find information
- High risk of using information that is not up to date
- High management cost
All of these elements impact the availability of a mission-critical system regardless of industry. All of these elements can be reduced or eliminated by ensuring that users always have access to correct and intelligent content.
Availability Calculation
Availability, then, is calculated as a function of MTBF, MWT, and MTTR. MTBF can be improved by reducing the number of failures (shown in brown in the illustration below). MWT can be improved by quicker reaction times and better preparation before a task (shown in gray in the illustration below). And MTTR can be improved by faster repair times (shown in blue in the illustration below).
In the first row (“Before”) of the table above, we see an example of the number of hours spent on different tasks in each category before implementing the new process using S1000D. This example shows 90% availability. The bottom row (“After”) shows the impact that was having correct, current, and intelligent technical information has on the same processes:
- Finding data/documentation decreased from 8 to 4 hours
- Finding spare parts decreased from 4 to 2 hours
- Rework because of wrong instructions was reduced from 2 to 1 hour
- Rework because of misunderstood instructions dropped from 2 to 1 hour
- Control and test were reduced from 4 to 2 hours
By applying these new values in the formula for availability, the availability would increase from 90% to 94%.
Now consider these two examples of the value of 1% availability as determined by this energy company:
- 1% availability of a windmill is worth 15,000 EUR per windmill per year
- 1% availability of a nuclear reactor is worth 5 million EUR per year
