Electronics manufacturing is a complex process, and even some of the most experienced businesses sometimes have to deal with flaws in production. Whether it’s a failed capacitor or even just a build quality issue, what can you do to minimize the number of mistakes in the manufacturing process?
Flawed batches are a waste of time and resources. Improving the quality of your manufacturing has significant implications for the productivity and revenue you generate.
Read on to learn more about root cause analysis examples in manufacturing, and how you can use them to improve your quality control processes.
Quality control is not a simple process. Some of the challenges, especially in a complex field like electronics manufacturing, include the following.
A treatment merely addresses the symptoms but doesn’t look for the underlying issue. Businesses should not rely exclusively on treatments and should take time to look for the deeper cause. That is, it’s ideal to find a permanent solution over a band-aid fix.
The root cause analysis process aims to identify the origin of manufacturing issues and research relevant solutions. Because the problem is considered at the root cause, this protocol goes beyond just treating the symptoms and aims to find a cure.
Some issues are easy to fix. Changing a component to a less faulty one, for instance. However, some issues can be caused by a combination of factors, which can obscure what the root causes are.
Because of interrelationships between various factors in manufacturing, rarely is there a single cause that the business can pinpoint quickly. Also, the problem might actually be a symptom of a more fundamental issue somewhere else in the assembly line.
When we’re looking at examples of root cause analysis in manufacturing, we have to accommodate the vast number of factors involved. From component placement to even how each part is installed, there are too many potential mistakes that can occur for a manual analysis to be effective.
Most companies wisely do not rely too much on on-site experts to handle every aspect of the production line. Because human workers usually end up reporting issues, even advanced analytics is prone to error as inevitable blind spots and human biases obscure the results.
Manual analysis also does not scale well, and the information is rarely shared effectively. If one section of the company learns of an issue, there must be a way for the intel to reach the rest of the organization. Otherwise, the same mistakes may be repeated elsewhere and generate avoidable losses.
The electronics market is always changing, and a manual root cause analysis won’t evolve quickly to adapt to new additions to the manufacturing process.
Root cause analysis refers to a technique that searches for the exact origin of a problem. What happened, why did it happen, and what could be done to decrease the chance of it happening again? This “root cause” might be:
RCA assumes that all the systems and events in your production line are interlinked in some way. This way, the process backtracks each step until it reaches the main cause.
RCA is the answer to the woes of quality control in electronics manufacturing. The process may differ from company to company, but the following are the usual steps in a typical RCA protocol.
First define both the issue at hand and the symptoms involved as reported by staff on the factory floor. Collect this information to show that the problem exists and how it impacts your manufacturing.
Effective RCA relies on having everyone on board with the analysis. Frontline workers should understand the situation and be able to explain it.
Look at the events that led up to the problem and the factory conditions that allowed it to occur. Remember that there can be multiple reasons why a production failure transpired.
Dig deeper using stronger analysis and cause-and-effect flowcharts. Figure out why the causal factors exist, and finally narrow down to the root cause(s).
Create a prevention plan to address the faults in the assembly line. What are the risks of using the new protocol, and who should have the responsibility of implementing it?
So what happens now that RCA has identified a root cause and generated a solution, whether it’s a change in parts or a new company policy?
It’s worth planning ahead to predict the future impact of the new solution. A process known as Failure Mode and Effects Analysis (FMEA) analyzes the risk involved to determine potential points of failure in the solution.
FMEA can be thought of as a proactive approach to incident prevention. For each step in the manufacturing process, determine what could go wrong, why such a failure could happen, and what the consequences would be. Applying FMEA across your organization helps you explore the positive and negative impacts an RCA solution would bring to the company.
We’ve made it clear that manual analysis is not enough for most manufacturing firms thanks to the high complexity of electronics. That’s why automated root cause analysis has become more important than ever.
Models empowered by machine learning and AI pick up on historical data to make accurate predictions and informed business decisions through RCA. Unlike a human-driven approach, automation is entirely unbiased and uses as much historical data as is available. Not only that, but it opens up time for your staff to focus on actually solving the problems at hand.
Are you ready to see the difference an automated root cause analysis solution can make? Book a discovery call with Vanti-Analytics today to get started.