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Sourcing >> Basic statistics any Chinese
factory can understand

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Basic statistics any Chinese factory can understand

Posted: October 19, 2016

By Renaud Anjoran

Whenever
some product attributes can be measured, statistical tools can help understand
the situation, prioritize improvement efforts, and even help those improvement
efforts.

For
example, if you measure your product’s size, thickness, or chemical
concentration, statistics can help. You can set specification limits and measure
products regularly.

Chinese
manufacturers are not used to this. Truth be told, I have never seen a Chinese
manufacturer, outside of car makers and their tier 1 suppliers, use statistics
correctly on their own. However, if they are open to learn, we have found that
there are a few basics they can apply easily.

First,
you need to define the CTQ (Critical To Quality) product characteristics.

For
example, Lego bricks have to fit together nicely. But what does “fit together
nicely” mean? Some dimensions need to be consistently the same, with very little
variation. For the sake of this exercise, let’s take say there are 2 CTQ
characteristics:

• Diameter of
the male parts

• Distance
between female part and the wall

By
measuring those dimensions on the PRODUCT, you will know the PROCESS capability.

Let’s
say you measure these 2 values on 40 pieces.

The
diameter value is often out of specifications (LSL = lower specification
limit; USL = higher specification limit).

The
distance value is very often above the specification. This is more
serious and should be worked on in priority.

Let’s
say, after you make changes to the mold and you control the temperature during
the injection process, the measurements look like this:

It
is better, but still a lot of observations fall out of the specification limits.
You decide to control the pressure and the time during the injection process,
and then it looks much better:

All
the data are within specification. However, the capability index (Cp) is still
below 1.00, which is often considered the very minimum. You might need to make
further improvements to ensure the variation gets lower, for example by checking
the polymer batches the supplier sends to the factory.

A
simple way to keep an eye on the parameters (pressure, temperature…) that are
suspected to influence greatly the end result is to measure them too… and to
calculate their Cp too. Same idea as above. If the main parameters are tightly
controlled, the end result should also be tightly controlled.

—

If
you are not sure what parameters have a strong influence, you need to use a
slightly more advanced statistical tool (multiple analysis of
variance).

Similarly,
if you need to make experiments to find the best combination (for example, “200
degrees at 100 tons of pressure for 60 seconds”), you need to use another
advanced tool (design of experiments).

The
key is, start simple. You can go as deep as you want in statistics, but if your
processes are simple you can probably get good results by using simple tools,
doing a few experiments, and seeing that yields the best result.

—

In
summary, basic statistical tools are not very complicated. When made visual,
anybody can draw a conclusion from them.

What
some Chinese factories really have a hard time understanding is, checking
products can tell us a lot about the underlying production processes. And, by
improving processes, it is possible to make better products. That’s not the type
of thought process they are used to.

Want
to learn more sourcing best practices?

Join the Global
Sources Summit that combines conferences and networking, co-located with our
Hong Kong trade shows. The event will be held October 17-19, 2016, and is geared
toward online and Amazon sellers.

Renaud
Anjoran has been managing his quality assurance agency (Sofeast Ltd) since 2006.
In addition, a passion for improving the way people work has pushed him to
launch a consultancy to improve factories and a web application to manage the
purchasing process. He writes advice for importers on qualityinspection.org.

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