When faced with a list of problems, it’s often hard to know which to tackle first. Pareto analysis is a tool for prioritizing efforts in terms of scale of impact or size of benefits. A Pareto analysis is often displayed as a bar chart and it’s widely used in quality, maintenance and lean manufacturing. You’ll often see a Pareto chart in the manufacturing industry being used to explain why problems are being prioritized and addressed in the order they are.
What is a Pareto chart?
A Pareto chart is the visual display of the results of a Pareto analysis, which in turn, is an application of the Pareto Principle. Often called the “80-20 rule,” this is the observation that the causes of problems don’t all occur with the same frequency. Rather, 80% of the problems are created by 20% of the causes.
The maintenance team in a plant is usually well aware of this. In almost every plant a few pieces of equipment are responsible for most of the unplanned downtime. The same applies to quality problems, and indeed, anything else that can impact operational efficiency. Actual percentages will vary, but the principle is almost always correct — most problems arise from just a few causes.
A Pareto chart, sometimes called a Pareto diagram, is a visual display of the frequency with which each problem arises. Causes or problems are sorted in order of occurrence, and a cumulative total line shows how each one contributes to the total. This makes it immediately obvious where to focus attention for maximum impact.
Key benefits of Pareto analysis in manufacturing
Pareto analysis can be applied to many of the problems encountered in manufacturing. Some common applications are:
- To understand the biggest causes of quality defects
- To identify machinery making the biggest contribution to unplanned downtime
- To determine which spare parts are used most often (so they can be grouped together in the most convenient location)
- To discover which product lines make the biggest contribution to revenue (and therefore where to focus maintenance effort)
The main benefit of a Pareto analysis is that it’s (usually) a quick way of finding where to focus attention for maximum benefit. Then, once a solution for the top problem has been implemented, the analysis can be repeated to identify the new “top problem.” In this way, the Pareto chart is one of the most used continuous improvement tools in manufacturing.
The value of Pareto analysis is that it’s data driven. If groups or teams are unhappy with the priorities set as a result of the analysis, they need to identify deficiencies in the data that have led to, arguably, incorrect decisions. Such data-driven manufacturing avoids determining focus based on instinct or other unquantifiable methods.
How to conduct a Pareto analysis: step-by-step
1. Start by selecting or defining a problem that needs addressing. It could be “aluminum scrap levels are too high” or “excessive bottle filling machine downtime.”
2. Gather data on the cause of each incident or occurrence of the problem. In the case of a scrap problem, identify all the reasons for scrap. If the problem is downtime, determine why downtime occurred.
3. Quantify the magnitude of each cause. This might be in terms of tons of scrap produced, or hours of downtime resulting. Determine the total, then calculate the percentage due to each cause. (For example, if 100 tons of aluminum was scrapped, and 50 tons of this was due to porosity, porosity accounts for 50%.)
4. Rank the causes by magnitude. This could be presented graphically as a bar chart. A vertical arrangement is most commonly used. For the sake of this example, let’s assume there are 10 causes.
5. Plot the cumulative magnitude by ranked order of cause. If 50% of aluminum scrap was due to porosity, and this was the largest single cause, this goes first. If the second-biggest cause was inclusions, and that accounted for 30% of scrap, the cumulative total is now 80% (50+30). Continue adding the percentages until very close to 100%. (It’s rare to get the total to 100% because there are often some unaccounted for losses.)
6. The graph of causes with bar height indicating total quantities should now be supplemented with a line showing cumulative percentage. With this complete, you are ready to start analyzing.
The chart will show that 2/10, or 20%, of the causes account for 80% of the scrap. This is the 80-20 rule at work. Armed with this information, you can start work on reducing the leading cause of scrap. Typically, once progress has been made, the Pareto analysis is repeated to determine the top causes now responsible for the problems or losses.
Applications and examples
The Pareto analysis example in manufacturing above was somewhat simplified but should illustrate the power of this tool for establishing priorities. Here are some other examples:
- Determining the 20% of machines responsible for 80% of plant downtime — so preventive maintenance can be targeted where it will have most impact
- Identifying the leading reasons for downtime on a specific piece of equipment — so improvements can be made to prevent future breakdowns
- Determining the most used items in the MRO stores — so they can be placed in a location that minimizes the time needed to assemble a kit for a maintenance job
Get help to improve maintenance operations
Pareto analysis is one of the easiest, yet almost most powerful, continuous improvement tools available. It’s used for tasks ranging from planning factory and storeroom layouts to maintenance planning and focusing on quality control in manufacturing.
As the leader in outsourced industrial maintenance, ATS helps manufacturers prioritize and improve asset life and care. Our services go from short term help with spikes in workload to advice and assistance on implementing predictive maintenance and more. Contact us to learn more.
