Why Traditional Statistical Process control Monitoring does not work anymore – Part 2

International Quality Institute in US had innovated the SPC monitoring techniques known as short run SPC to address the needs of current production line with low volume high mix.   In this technique, one chart can be used across different models with different process center and control limits such as part A, B and C shown in chart below.

Short run SPC method transform data collected and can use predetermined the control limits to enable different process center and even standard deviation product can be plotted in one chart.  This is applicable for 

1. Same model product  with different lot to lot process center 
2. Different model product with different process center

There are 2 types of data transformation in short run SPC to get the plot points

1. Target method - Calculating actual measurement readings and calculate the deviation from target point (either using specification or process control) for average chart
2. Standardized method - Nominal transformation of actual measurement data to plot point for both average and range chart.

Unfortunately short run SPC is still not a widely used technique especially in the world of electronics part manufacturing which could due to lack of true quality engineering expert.  There is also limitation in software as currently there is only one commercial statistic software which is capable of plotting short run SPC, Stat soft Statistical.   

It is imperative to be able to monitor the critical quality parameter correctly to ensure that product  quality parameter is reflecting the actual product quality per customer requirement which is the method to consistently good quality product.  Short run SPC is one of the techniques that work in high complexity low volume environment.

Appreciation notes  :  I would like to thank my mentors in Dell who had introduced me to short run and enable me to go further in my journey of SPC discovery  and share with my audience.

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	Problem
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.

Monitoring Process Output using Statistical Process Control Method

One of the most effective ways to monitor a key process output performance is using statistical process control (SPC) chart.  This method was invented by Dr Shewart nearly a century ago and it is the most frequent used process control method with some enhancement over times.  Control chart is actually a run chart with a calculated upper, lower control limit and process average from the actual key process output. The control limit must be calculated under the influence of stable common cause variations.  The 3 lines,  upper and lower control limits and average will be used as a guide post to show the presence of  special cause variation in the process which required immediate attention.  The interpretation of  the control chart is available in my previous article (http://www.360qualitymanagement.com/2017/09/how-to-detect-common-cause-and-special.html).  In order to have an effective SPC to monitor the process,  manufacturers  must  create a proper procedure on how to manage SPC implementation.

After auditing more than 100 suppliers’ sites which produce electronics parts (first and subtier) across the globe, I had NOT seen a decent SPC procedure yet.  Some companies does not even had SPC procedure and some companies SPC procedure only contain  text book  information on the type of control chart and how to plot control chart with calculation of control limits.   SPC procedure is NOT about how to plot control chart, it is should be about how to plan, implement and manage SPC within the process.  Each site/company should establish its own SPC procedure and not make copycat procedure from SPC textbook.

The table below shows some of the recommended content for SPC procedure in detail :-

Areas	Details
Identify person in charge of SPC.	There must a dedicated department or at least dedicated team who is responsible for the implementation of SPC
SPC training for employees	Outline the SPC training curriculum for different level of employee in the company such as operator, technician, engineer and even management.
Select the parameter needs to be controlled	The most effective method to determine which process output parameter should be monitored and controlled would be through failure mode effect analysis (FMEA) technique.  FMEA is a systematic prediction use to identify potential failure which will impact customer and what are controls needs to minimize or eliminate those failure risk.  There also other method which include product mapping, brain storming etc.
Setting up of control chart, chart selection, calculation of control limit, rationale subgrouping.	Select the most suitable type of chart (attribute or variable chart), rationale subgrouping by category (either by machine or line or tooling) and subgroup size follow by control limit calculation.   There were a few good article rationale subgrouping by Dr DJ Wheeler in the internet The  SPC control point must updated into the process management plan
Manage control limit	The responsible SPC person must be able to determine when to fix a control limit according to the process nature.   Normally it is recommended to study the trend of 100 subgroup points under the influence of common cause variations before fixing the control limit. Once control limit is fixed, there should NOT be any revision on control limit done unless there is major improvement in either one or a few process input.
Define out of control (OOC) rules	Not one manufacturing process in the world are able to use all the 7 Western Electric rules as it would be too complicated to control the process and there will be too many false alarm.  Normally I would recommend companies to use only 2-3 rules to avoid complication
Reaction plan when there is OOC	If there out of control trend per the company define out of control rules, there should be an investigation conducted to check if there is presence of special cause.  Efforts should be taken to eliminate unwanted special cause and to bring the process under the influence of only common cause.  There must be clear ownership to drive the problem to closure preferably through the company correction action request system.  Refer to my previous article on corrective action (http://www.360qualitymanagement.com/2017/09/various-special-cause-problem-solving.html)
Review the effectiveness SPC chart	Check and balance to ensure SPC s implemented correctly and effective There should be review conducted monthly or quarterly to ensure the effectiveness of the SPC :- False alarm are  within preassigned goal for false alarm SPC chart is effective to catch special cause defect, through correlation of the any special cause which happen.

Ironically there are many companies create SPC chart just to full fill customer requirement of using SPC chart to monitor the process.  Upon a closer look at the chart, there are so many faults associated to the control chart such as:-

1. Control limit are actually spec limit, 
2. Out of control trends/points not investigated, 
3. Chart is show cyclic trend of up and down due to wrong subgroup category

You can gain more insights on how to use SPC as an effective process monitoring system by taking this course : - 

Click on this image for course URL @ USD12.99 👇

If a SPC chart does NOT serve its purpose to detect a special cause variation, then it would be better to just remove the chart totally rather than to waste resources to maintain and print the chart which does not bring any value!