Why Traditional Statistical Process Control Monitoring does not work anymore – Part 1

Statistical Process Control had been deployed for almost 100 years in many established manufacturing organization such as Western Electric, General Electric etc. to monitor their process for any potential special cause.  However for the past 20 years, I found that many manufacturing organizations which produce computer/IT gadgets parts had been struggling to use Statistical Process Control as process monitoring tool mainly due to the chart exhibit too many false alarm out of control situation.

So what had changed over the past 20 years?  The boom of  computer industry had monopolize the manufacturing eco system globally with supply chains that are much more complex and longer compare to other types manufacturing industry such as automobile.  In order to stay competitive, IT gadget suppliers such as computer or hand phone companies had offer many options which include different shape and size of product to satisfy myriads consumer preference in the market.  Gone are the days where a factory shop floor can run products for a few weeks or even months without changing model.  There were some manufacturers continue to run a single product till end of life such as model T Ford automobile in the last century!

Today, daily or even hourly model conversion had become a norm in many manufacturing industry with high complexity and low volume to cater for different consumer needs.  Manufacturers are making smaller lot size where some could be less than 100 pcs batch and the batch run only last for an hour or less.  If the control chart sampling frequency to collect data is 5 pcs per hour,  then only one data point manage to be collected.  There is even not enough data point to calculate control limits. 

Most manufacturing line use 2 approach  in traditional SPC to manage frequent model change and both has its own problem:

Traditional SPC method
Type of run
Use  one chart for one model or same part number
Single production run. 
There is not enough point to read the potential out of control situation where some out of control situation need about 7 points. 
Increase sampling frequency is not an answer as it will increase the cost of production. 
Use one chart for one model or same part number.  Whenever there is a production run for a part number, the same chart will be used to plot the SPC point. 
Multiple production runs
There will be too many false alarms such as center line shifted due to different production lot throughout the supply chain. 

Below is an example of notebook cover length data collected on different production run.  It is really impossible to apply conventional SPC method to monitor the process as there are shift of trend with each new production run. 

This chart show that there are parts from different batches in different date with different process center and possibility  different data spread.

In traditional SPC method,  the manufacturing engineer could have use one chart for one single lot date code run. This is not a practical method as there would too many charts to monitor for a single product.  

We shall look at how we can simplify SPC chart in the part 2 of this article for  such scenario where parts with different process center and even data spread for different production lot.

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