The gage R&R study is a commonly used tool in various industrial environments, and the automotive industry is arguably one of its biggest users. That should come as no surprise to anyone familiar with both that part of the industry as well as the study methodology, as there are some close connections between the two that make this type of study one of the best tools for gauging the performance of an auto plant.

Repeatability and reproducibility are, after all, critical parts of the work of an auto factory, and determining the variance in measurements with a great deal of precision can often go a long way in improving the overall output of the factory.

Not only that, but you’ll be able to get a better sense of how well your different instruments are aligned to your current workflow, something which many auto plants tend to lack to a severe extent. This is a common problem when a plant has to go through multiple different iterations of the same vehicle model, in which case a good overview of the current measurement instrumentation is absolutely critical.

Understanding the Relevance of Gage R&R in the Auto Industry

Understanding why this type of study is so important in the auto industry mostly boils down to understanding the meaning behind repeatability and reproducibility in the first place. These factors can play a critical role in the operations of many types of factories, but when it comes to an auto plant, they have to be controlled with a great deal of precision.

Repeatability is variation caused by the measurement device itself, and it’s related to the operator taking the measure. This makes it important to control who’s involved in different stages of your studies, as changing between different operators on the same workstation can have dramatic consequences on the validity of your results in the end.

On the other hand, reproducibility is variation caused by the system in which you’re working, and it can be replicated when working with different operators. When studying the reproducibility of your systems, you can safely exchange operators as necessary for the current test, as this will not have any impact on the final quality of your measurements.

The Evolving Nature of Measurement Instruments

A factor that’s going to play a central role in conducting a gage R&R study is the way your instruments themselves evolve over time. This can matter quite a lot when trying to align the results of multiple different studies, so make sure that you account for it in conducting each stage of the gage R&R study.

In some cases it can actually be a better idea to work with older instruments if they are better aligned to your testing practices, instead of trying to realign the tests to a new instrumentation set. This may seem counterproductive, but it’s one of the most commonly used approaches in many automotive factories, and a common technique across the industry as a whole. That is, at least for factories that rely on the gage R&R study in the first place.

Conclusion

There is a very tight link between the gage R&R study and the automotive industry, and understanding this connection can be very beneficial for anyone in a leadership position in an auto plant. There is often a lot to gain from studying the variation involved in your measurement practices, and the sooner you put some systems in place to track it and record how it changes over time, the better results you’re going to get in the long run when running your plant. This is especially true for plants that tend to work on multiple different models over time.

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Many of the techniques and methodologies in the Lean/Six Sigma area have their roots in the automotive industry. While failure mode and effects analysis (FMEA) does not originate directly from there, it still sees a lot of active use by companies in this field, and it can bring many benefits to a modern manufacturing plant, as long as its leaders know how to apply it correctly and how to make use of the information it produces for them. FMEA can be a highly effective tool for minimizing the error rate in a system over a longer term and for identifying the underlying problems in any situation of failure, and it’s not hard to find examples of that.

Optimizing Manual Processes Step by Step

A commonly seen example of FMEA in the automotive industry is in manual processes which are carried out in discrete steps. It’s often important to assess the risk level of each of those steps separately, allowing the operator to know when they should be paying more attention. On the other hand, in cases of failure, this can very effectively help guide the investigating team to the root cause of the problem. They can simply target the high-risk steps first and sort the list by that criteria, moving down as they check each one.

The true power of FMEA shines when it comes to breaking down each of those steps into its potential causes and recommended courses of action for example, when it comes to something like applying wax to a car door, you can prepare a list of specific potential failures for each step of the procedure, and the operator can study that list and know where to start looking in case something goes wrong. What’s more, they will also know what details could potentially go wrong, and will be able to direct their attention to those areas when performing the task, minimizing the risk that they will mess up the job.

Optimizing the Construction of Safety Critical Parts

When it comes to cars, safety is a critical feature that has to be observed under a microscope at every step of the production process. FMEA can be used to assign risk levels to each separate part of the process when a worker is constructing a feature that can affect the safety of the car, giving the worker an opportunity to pay more attention to that feature and to potentially double-check it after completing the job.

This also carries over to post-production verification procedures, which can be made significantly simpler and more streamlined with the help of FMEA. The whole plant can work according to a standardized model that allows them to guarantee the safety of the parts they produce, and discard the ones that don’t fit the criteria early on. A proper implementation of FMEA can significantly improve the overall safety of a plant, and it can reduce the expenses of the company in this area.

Conclusion

Failure mode and effects analysis is a technique that should be studied in a lot of detail by people operating in the automotive industry, and there are plenty of examples of its successful use in this area. It doesn’t take long to find ways to apply it in a typical production plant, and as long as you’re motivated to ensure that the work done by your operators is safe and at a high level of quality, this is one of the first steps you should take. There is a lot of information about it out there too, so you shouldn’t have too much trouble getting up to speed with current trends.

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