Root Cause Analysis
is a data driven approach to problem solving.
There are two key issues with typical approaches to troubleshooting:
Root Cause Analysis overcomes these issues by utilizing a rigorous multi-step process that focusses the troubleshooters on the data related to a problem.
The data is used to guide the team to quickly identifying the root cause(s) of the problem
- Often only the symptom is cured - without addressing the real root cause. This results in the problem repeating - either on
other equipment in a facility or on the same equipment at a later date.
Secondly - often several false paths are investigated before the true cause of the problem is discovered.
This results in slower troubleshooting and more expense as various solutions are attempted in vain.
Examples of RCA usage include answering the following questions
- Why are our packages showing up at our customers damaged?(a rough floor in the warehouse and using the wrong containers)
- We are having sheet breaks on the suction pickup roll of a pulp machine. Knowing that the seals on the suction roll are leaking - do we need to take a $1 million outage to replace the roll? (no the real problem is an incorrectly ground wire return roll and a simple adjustment will fix the problem)
- Why is our pulp machine reliability dropping every year?(Need to improve PM's and operator training and implement the managed incident system)
- Can we meet future throughput requirements on our line kiln through operator training and other low cost improvements?(No - data shows a serious under capacity of key subsystems)
- Why have we experienced a sudden increase in ClO2 generator puffs?(Because the cooling system for the #2 turbo-generator in the powerhouse has sprung a leak)
Although typical uses of the
is in a team setting addressing large problems, the same principles are effective in small single troubleshooter scenarios.