Pareto Analysis’ Impact on Reliability Testing
One of the most common questions we ask at the outset of a project is whether the client has performed a Pareto analysis. The information from this type of analysis helps us determine the most efficient course to take when it comes to reliability testing and maintenance.
What is a Pareto Analysis?
The Pareto Principle, or the “80/20 rule,” has made its way into popular discourse in many areas. Thought leaders in industries ranging from economics to sports have realized that 80% of results are often driven by 20% of inputs. This principle has enormous implications for those charged with maintaining equipment. By ensuring that the top 20% of equipment experiences little to no downtime, reliability professionals can better protect the vast majority of a company’s output.
That’s where the “analysis” comes into play. Sources of failure and inefficiency need to be measured against their frequency and impact to then inform what maintenance should be prioritized.
Conducting Pareto Analysis
Pareto analysis can be seen as the next step after conducting case-by-case failure analysis. It can also be the impetus to conduct more thorough failure analysis. By tallying causes of failure in case-by-case analysis and pairing those causes with other sources of information like customer surveys and statistics from RMA, reliability engineers can have a full picture of any inefficiencies. They can then begin to relate those findings to their impact on overall effectiveness.
Once the data has been compiled, it can then be plotted on a graph to illustrate how often equipment requires maintenance. This can be collected via work orders or returns, for example. The individual data (work orders, returns, etc.) can then be measured against the proportion of total requests to the combined articles in questions (machines, components, etc). An example of this kind of graph can be found below.
Along the X-axis are the articles being compared. For a manufacturing plant, this could represent all of the machines that have required maintenance. More granularly, the components of the machines could be compared, such as the belts, valves, or actuators. Companies can also compare end products in this way to see what products are experiencing the highest rates of failure and returns.
The Y-axis on the left shows the amount of times each article has experienced failure. The value of the graph comes from superimposing the second dataset along the Y axis on the right side as a line graph. This line graph can show at a glance how many articles should be focused on to reach that desired 80% increase in impact.
Using the Results
The results of a Pareto Analysis can influence a wide range of decisions. It can inform what spare parts to keep on hand, which machines to prioritize fixing, and which brands of machines to invest in in the future. The results can also influence preventative maintenance schedules and allow companies to forecast their maintenance costs.
Armed with this information, ARL can help in a number of ways. Our accelerated life testing and environmental testing capabilities can further refine preventative maintenance schedules. Also, if more information is needed to determine the root cause of failure, our partner lab network can handle failure analysis.
If you’re ready to begin to make more informed and strategic reliability and maintenance decisions, contact us today.