How to Perform Root Cause Analysis in Manufacturing Operations

When you have production problems in your manufacturing process, it’s essential to find and solve those concerns before they impact your company on a huge scale. When such issues arise, many companies turn to root cause analysis (RCA) to help implement a solution.

What is a Root Cause Analysis?

Root Cause Analysis is basically the process of tracking the causes of an observable issue and recognizing the basic underlying concern that was causing it.  

Once you have the concern under control, it is important to know how to keep away from it, so it doesn’t happen again. To do this, practicing and enhancing root cause analysis is your best solution.

In this article , we take an in-depth look at how to execute Root Cause Analysis in Manufacturing Operations.

Advantages of Root Cause Analysis

RCA can drive many tangible and intangible advantages to a business. Some of these advantages contain:

• Automation: An automated root cause analysis system can distribute data across factories within the same company, empowering managers to track notes concerning a common root cause and take the next steps to prevent it from happening at their own plant.
• Proactivity: Because automation via data analysis is generally adapt for the results of root cause analysis, safety, maintenance & quality concerns can be recognized more precisely and acted upon rapidly to minimize them.
  
• Realistic solutions: The solutions RCA generates can last for years. You can build clear, step-by-step processes that work every time and provide you remarkable ease of use.
• Cost savings: RCA can minimize cost by lowering downtime, minimizing defects and enhancing productivity. It also helps to maintain your revenue stream.

How to Conduct Root Cause Analysis

There are several ways to implement RCA within your manufacturing company but few basic steps still last in every methodology. The process you may take to get to the end will be different, but eventually, you’ll realize the final objective of transforming your operations and improving productivity.

Basically, there are six steps involved in root cause analysis:

1. Defining the Concern

Step 1 is the most essential step. It involves everything from making the team to making a plan for the project. All team members must understand the concern. Though the most crucial purpose of the step is to simplify what the concern is and define its scope.

2. Collecting the Information

Data collection is essential in root cause analysis. Today, it is simpler to locate and utilize data in root cause analysis due to many OEM equipment manufacturers insert data collection in their machines. It may also be the case that a factory has employed data collection devices for those machines that do not have inbuilt module.

3. Isolate Causes from Symptoms

If you require to do RCA for a malfunctioning machine or a step of the manufacturing system, separate all suspected parts of the machine or all equipment included in the specific process. Doing this will assist you to recognize the root cause more rapidly without the impact of other system components. Here, data collection can also be crucial as many data collection systems have analytic able to discover categories of problems.

4. Deciding Corrective Actions

Once the root cause is recognized, an effective solution can be formed. This may involve mechanical modification, floor layout, or more strong data collection and analytical abilities. Frequently, data can help in creating the corrective action. By having real-time insights in hand when the root cause is recognized, managers can generate an appropriate, real-world solution based on actual data.

5. Implementing the Solution

After finding the origin and the corrective action plan, the team must apply the solution. The deeper the data collection ability, the bigger the analysis’ influence on the selected solution. Once you verify that ideal solution, you can document it and make new workflows for others within your company to utilize it.

6. Verifying the Results

The process audit piece authenticates the effectiveness of the solution. This is made more available when data collection is strong and subjected to real-time analysis. By doing so, the effectiveness of the solution can be analyzed or adjusted to enhance effectiveness.

Root cause analysis can be tackled by a team manually. But when it is integrated with advanced data collection and analysis, it both improves the impact and improves production efficiency.

Pareto Charts

A Pareto chart is one of the most widely used and true visualization methods that assist teams to interpret the frequency of concerns in root cause analysis. As per the Pareto principle, removing 20% of the most common failure causes can result in minimizing the overall number of malfunctions by 80%.

Pareto charts will notify the top failure causes to be further examined and resolved, as per the criticality of the machine, the influence failure of a particular part, or an integration of the two.

RCA in Real-Time: The Current Shift Dashboard

The current shift dashboard is an excellent solution for analyzing production progress in real-time. It offers visibility of performance to goal so operators can easily distinguish predicted and actual performance. In this way, operators and managers can quickly rectify the problems.

This is a huge short-term and real-time strategy for resolving concerns in a day-to-day manner before a thorough analysis is capable to be completed.

There are several views that can be utilized for the current shift dashboard, containing parts goal, OEE, utilization and downtime.

Recognize the Top Causes of Downtime with Pareto Reports

The most useful report for interpreting downtime reasons is the Downtime Pareto, which will combine all the logged downtime reasons.

Using this report, you can recognize the most dangerous downtime reasons. Further, you can divide the data between different shifts, machines groups, or even individual machines for a more clear look at where the root cause may lie. Additionally, you can easily monitor where unplanned downtime is occurring versus planned downtime.

Frequent categories of downtime contain excessive tool changeover, excessive job changeover, operator deficiency and unplanned machine maintenance.

We not only offer an accurate view of downtime but the platform where you’ll be able to determine where the problem is. Check how IoT based machine monitoring system can help you to improve manufacturing strategies and eliminate the obstacles to success.