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Moving toward zero-defects manufacturing with gusto to make your factories smarter

This blog series discusses strategies, priorities, and challenges manufacturers face to automate factories of any size to move the needle towards zero defects manufacturing

What does zero defects strategy mean in smart manufacturing?

A zero-defects strategy is not a new concept; most companies have been working on developing one for many years. However, the approach to building such a strategy in smart manufacturing is an evolving concept. Technology has changed, expectations have changed, there are more extensive possibilities, and even what we’re expected to do from an automation and quality perspective has evolved. It’s important to look at some of the challenges we face in developing a zero-defects strategy, and how we may go about mitigating them.

What are some of the challenges we face?

We’ll use the automotive industry as an example many people are familiar with. Vehicles have considerably more sensors, automated driving systems, safety systems, and features on board. As a result, there has been increased pressure on the industry to build more chip driven subassemblies.
However, the industry is experiencing a problem from the latent failure perspective. This is when a factory manufactures a component that makes its way through the supply chain and fails in the field. Ultimately, it becomes a challenge to determine what caused the failure. This has become particularly difficult as 22% of warranty failures are electronic components related. Furthermore, they fail within the warranty period of an automobile. The industry faces a daunting task to track the geneology of parts manufactured in a factory. 85% of the automotive parts are made in 150mm and 200mm facilities that are not as well equipped to track the history of parts. This history needs to span several years.

This challenge is significant. Think about what’s involved in accurately collecting, reconciliating, and tracking mounds of data. This task is so big and important that IATF standards (IATF 16949 Standards) were developed to assess the ability to meet the manufacturing practices required to minimize the risk. The challenge comes from the reality that legacy facilities were not designed to track to this extent of granularity. The desire to resolve discrepancies in the data exists, but to figure out how and the time it requires to do this efficiently and meet quality standards consistently is daunting (figure 1).

Figure 1 shows the baker’s dilemma in how to streamline quality standards.
Figure 1: Shows the baker’s dilemma in how to streamline quality standards.
Figure 1: Highlights the importance of precision required to streamline quality standards.

Identifying the Cause

Beyond following the standards, it’s important to ask, “How are we doing this today?” The first step in answering these questions is to look at the anatomy of failures. This anatomy of failures is broken into three categories to be considered at the macro level:

  • Systemic: Where the factory had a parametric test for something and yet there was still the opportunity to send something out the door that would have been caught by that test. For some reason, they failed to identify the problem. This is the most common cause of latent failure.
  • Test coverage: This is the cause for one-third of the cases of latent failure. It occurs when a factory designs something new, or something with a new characteristic that warranted a new parametric test that is missing. This is because they didn’t know they needed it or didn’t have it.
  • Random: In this instance there is an inability to classify where the failure came from and therefore it is deemed a random failure. These are some of the more disturbing problems because they point to a much more systemic gap in the automation capabilities.

The anatomy of the latent failures lends insight into the type of automation deficiencies that a factory may have (Figure 2).

Figure 2: Anatomy of Latent Failures

In our next segment in this blog series, Moving toward zero-defects with gusto to make your factories smarter, we’ll discuss how to identify types of missing automation CIM components. Stay tuned.

About the Author

Picture of Selim Nahas
Selim Nahas
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