Closing the Loop on Quality

Recently, Jim Brown of TechClarity posted a blog on Siemens PLM Software’s new Dimensional Planning & Validation (DPV), solution for quality. Jim wrote, “One of the main things that manufacturers can do to improve quality is to “close the loop” on quality by feeding actual results back into the manufacturing and design processes to improve quality.” He goes on to say, “One of the key elements that make this beneficial is the analytical engine behind it, similar to other trends to use business intelligence (BI) in PLM.”

This is exactly why Siemens has developed DPV. Capturing as-built quality data from the shop floor, e.g. from coordinate measurement machines or visual measurement systems, and integrating it directly to the PLM platform Teamcenter. This enables for continuous product and process improvement through product design, manufacturing planning and production. More importantly with DPV, the design and manufacturing engineers do not need to switch between different IT systems. The quality data is available in a single source, fully associated to product, process, resources and plant information.

 

What does this do?

First, it significantly lowers the cost of quality of the next product versions. The product’s quality is defined during the design process: dimensions, orientation or location tolerances, surface-finish quality and more. Bringing actual quality data back to design now allows you to identify issues and correct them where they were initiated. By not closing this loop, ,manufacturers have to deal with with quality issues in later stages of the production process where the cost of change is much higher.

 

As an example, a high performance turbo charger assembly is monitored. It is found that an end-cap has too much gap at the mating surface causing a drop in pressure output which increases rework on the assembly. To solve this issue it is determined that the torque on the five bolts in the assembly must be increased. The bolt torque design spec is modified and new inspection points identified to more accurately monitor this issue.

Second, by associating actual measurement results to 3D product data and process information, you now have the ability to find the root cause of product quality issues. How important is this? It allows you to reduce rework, repair, scrap and non-conformance processes which ultimately impact profitability.

One example is a milling cutter which can be used only for a certain amount of parts or hours. Eventually the edges become too dull to cut material within a specified tolerance or for a particular surface finish. At some point, the surface starts to deviate from the design spec. Of course experienced shop floor workers know that they should exchange the milling cutter after a specific amount of parts or cutting hours. But with DPV, they will know when tolerances or surfaces are reaching limits and can plan accordingly. But what if the cutter was recently changed and you still identify quality issues? It might be that the fixture holds the part much too strong on one side and forces the part to bend, which finally leads to the quality issues. Now with DPV’s integration to the PLM platform Teamcenter, all of the other potential contributors, e.g. tooling, fixture, machine set-up, etc. are available and can be used to identify the root cause of the issue.

Here’s a picture about different surface qualities.

 

The Siemens PLM Software solution gives you full flexibility to capture, store, manage and analyze critical quality data. Imagine multiple global plants running daily, capturing hundreds of thousands of data points. DPV is a unique solution to efficiently visualize this data, identify the critical areas and take appropriate actions.

For more information just visit the Dimensional Planning & Validation product page. And take a look at my previous post from the PLM Connection Europe including a video interview about DPV.