Q&A for quality control in manufacturing 

  • How can I minimize downtime?

Manufacturing downtime is a nightmare for manufacturers. It may lead to significant delivery delays to your customers and damage the heart of your business.

In order to optimize your production, you need to be able to react fast in front of daily tasks. Running a digital root cause analysis gives you the opportunity to identify and fix problems that may occur in advance, resuming full manufacturing as soon as possible.

It is essential that the data collected from the testing stations are as updated as possible.  Ideally real-time or at least within seconds of events taking place. Our technology makes downtime no longer an issue when looking for ways to guarantee your quality control in manufacturing.

  • Why is it so important to run an efficient root cause analysis?

Many manufacturers base their quality criteria on one key indicator – “Pass” or “Fail”.  If the test result shows a “Pass”, then the unit is ready to move on to the next manufacturing stage. If the test result shows “Fail”, then the unit is sent to a technician for further analysis.

When evaluating unit quality, a simple “Pass” or “Fail” is far from sufficient. It gives you little or no information about edge cases, where one or more of the technical parameters of the unit under test are only just within its allowed tolerance. Edge cases may lead to unit failure during operation, for example in extreme environments (cold, heat, humidity, electrical overload, impact, etc.).

For accurate data analysis, you need to routinely review and analyze the entire test data for the unit and compare it in a meaningful way with other tested units, other testing stations, and with historic test data. 

Running an automated data analysis as a routine will ensure that you’re analyzing all the data for the unit and comparing it in a meaningful way with other tested units, other testing stations, and with historical data.

  • How is the manufacturing process in a digital factory?

The manufacturing process is a chain of separate but dependent assembly and testing processes, which together build our final product.

When running a manual root cause analysis a technical problem created in one stage of manufacturing may only be found in a later stage of testing. For example, a defective button assembled on a unit may only be found during functional testing several stages later. A digital factory integrates all that relevant information so you won’t miss any important information.

You should expect test results from any of your manufacturing stages to potentially influence other stages in the process. Reviewing and analyzing the data collected in one testing station in isolation is just not sufficient.

In order to see the entire picture, you need to collect and analyze the end to end results according to the severity and the frequency of each problem as a digital factory.

You might be producing the manufacturing of your products on another continent and it may be taking place in the next building.  Either way, you want to keep a close eye on every stage and be aware of major problems the instant they happen. With our solutions, an automated alert mechanism, that generates notifications about critical problems on the manufacturing line is sent to you when necessary. 

  • How can we predict errors when running root cause analysis?

“A clever person troubleshoots the problems that a wise person avoids in the first place”.  Let’s be wise and fix quality issues before they happen. A good way to achieve this is to set up a predictive mechanism as a digital root cause analysis that analyzes trends within the testing results and alerts us to potential quality issues.

Conclusions

  • Yes, you can definitely outsource the manufacturing of your products.
  • The monitoring system should collect the testing data from each testing station and present an integrated end to end view of the process.
  • The data collected by your quality in manufacturing monitoring systems should be up to date and presented in such a way that you can carry out quick root cause analysis of issues found during the manufacturing process.
  • The quality in manufacturing monitoring systems should alert you when the process is out of control and provide early warning of potential failures.

Quality control in manufacturing

Smart manufacturing technologies enhance the manufacturing process continuously collecting and analyzing your data in real-time to achieve and maintain quality performance. 

Our clients report a 30% increase in quality and yield in the first year of use. Companies can Reduce downtime incidents and have an average of 4 months ROI (return on investment). 

How does it work?

QualityLine automatically creates an analytics and interactive dashboarding system that automatically predicts and sends alerts for any anomaly detection to prevent degradation in the manufacturing process.

Our remote monitoring solutions let you gain full end-to-end transparency over the whole manufacturing cycle with accurate information about each unit tested. An automated root cause analysis will reduce manufacturing waste and minimize failure rate, improving your production efficiency and quality.

You’re invited to click here for a “free live demo”.