2017

BACK TO BASICS

Get to the Root of It

Use an is/is not comparative analysis tool to pinpoint the problem

by David M. Rucker

This article was featured in January 2016’s Best Of Back to Basics edition.

We’ve all been there before—an elusive field failure sparks customer complaints and warranty claims, threatening to curtail future orders. Ambiguous, conflicting field reports of failure modes and products affected pour in. Root cause theories sprout like wildfire, coupled with emphatic statements like, "We’ve never had this problem before!"

At times like these, quality professionals need to inject reason, logic and quick but disciplined approaches to clarify the situation, identify the root cause and resolve the issue.

An is/is not comparative analysis is a powerful tool for quickly honing in on the root cause. Use this deductive logic tool in the measure phase of the define, measure, analyze, improve and control process to determine what is in scope and what is not going to be considered at this stage (see Figure 1).

The process works best with a cross-functional group of four to eight people who represent all facets of the issue. Post the diagram in Figure 1 on a flipchart, whiteboard or projector screen to engage the whole team.

Figure 1

Ask questions

The method involves deliberating and answering a series of questions designed to pinpoint when, where and how often a problem occurs and—just as importantly—does not occur.

The process tends to work best with an active facilitator who challenges statements made, such as "Do we have data to back that up?" and "Do we really know that to be true?"

The facilitator should constantly remind the team of the difference between facts and opinions. Team member knowledge and experience is useful; it’s important, however, to clarify the difference.

When data are not available to back up a position, ask yourself whether it could be quickly collected. To separate theories from opinions, could you conduct an immediate experiment as proof? Add the results of ensuing fieldwork to the diagram.

The matrix helps organize all relevant knowledge and information about the problem in one handy reference.

Classifying the problem in the categories of time-to-time, part-to-part or within-part defect assists the team in understanding how to structure the data-gathering process. Common sense and a simple deductive reasoning process leads the team to a conclusion and problem resolution.

Once the root cause is found, confirm the hypothesis and turn the defect off and on in the capping run of the simplified design of experiments.

Case study

During a recent workshop with shop floor supervision and quality personnel, a team attacked a major field failure of a critical cast component. In two days, the team identified the failure mode, structured the data collection and used comparative analysis to find the root cause.

The supplier of one casting had repaired bad castings by drilling out slag—the bottoming of the drill removed wall thickness that led to the failure. The defective parts were quickly quarantined, avoiding a potential $600,000 recall.

This process takes the emotion out of analysis at a stressful time. It also allows the group to slow down and move deliberately at a time when many want to jump to conclusions.

For many low hanging fruit-type quality issues, this tool leads directly to the root cause. For more complex problems, it helps identify the key performance variables requiring further study.


David M. Rucker is president of Rucker & Associates, a consulting firm in Raleigh, NC. He holds a master’s degree in mechanical engineering from Southern Methodist University in Dallas. Rucker is a senior member of ASQ and a frequent contributor to ASQ’s Lean Division newsletter.



good article about is / is not
in a logical manner
(if not computerized control)
a clear, unambiguous and unique definition of the item or data item description, which is or is not (in written form in any media) and clarifing any possibly failure modes of those and if possible "restrict" the possible failure modes might also help to decrease variation of the item / data item / process
--Aylin Nafia Sener, 11-16-2015

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