Applying SPC

Statistical Process Control (SPC) is like many tools used in Continuous Improvement (CI) and Quality Control methodologies in that it is not something that you would use for every process. It is also true to say that we don't just apply it to processes that have variable data, as there are other forms of SPC charts available for use (which we will discuss later in this article).

Dependant upon which industry you are applying SPC in, there may well be industry standards to be considered, for example supply chain control systems. Therefore, in this article, we will make general recommendations on how you might approach the application of SPC.

Selecting Processes For SPC

SPC should not be applied as a scattergun approach but reserved for processes that are:

• Critical (as defined by the FMEA process)
• Producing critical outcomes (as defined by the FMEA process)
• Known to have reliability issues (out of control conditions)
• Critical to customer satisfaction (internal or external)

In all cases, it is better to control process parameters rather than the process outcomes. In other words, if the process parameters that make the outcome reliable are known then why risk making reject parts?

For example to produce a 'good' spot weld, the process parameters that can be controlled are:

• Tip condition
• Power (Amps)
• Dwell time
• Tip to anvil pressure
• Substrate condition

Get all of these right and the spot weld is guaranteed!

Planning to implement SPC requires the involvement of the team and ensuring that everyone understands their role and are trained in the requirements for this. The plan also needs to reflect why SPC is to be applied to the process in question.

The plan should include:

• Understanding the process paramters and common cause variation
• Sample size
• Sampling frequency
• Measurement system analysis
• Data collection and analysis responsibilities
• Training requirements (where necessary)
• Timing

When planning to set up SPC on a process, there are a few rules that need to be observed including data source - the data to be collected should be from one source only. In other words avoid collecting data from:

• More than one process
• More than one tool
• More than one mould or cavity
• More than one measuring station

Calculating Control Limits

Control Limits should not be calcuated, in the first instance, until such time as all of the common causes of variation have been experienced, such as:

• Changes of shift
• Normal changes in the environment (internal and external)
• Change of supply of materials (under normal circumstances)
• Cutting tool sharpening (after tool wear)
• Autonomous maintenance
• Change of operator
• Change of person taking the measurement

In any event a minimum of twenty sub-sets of data will need to be collected

Once the control limits have been calculated, thay should not be re-calculated until something has changed, that is to say a special cause has taken place, process re-set, tooling changes or other significant event.

We have have experienced, in some organisations, the recalculation of the control limits after every SPC sheet has been completed, this should not be done unless the completion coincides with a significant event, as above.

Other Control Charts

There are two types of data that can come from a process.

1. Variable Data: something that can be measured (length, volume, mass for example), which has been the focus of this series of articles.

2. Attribute Data: something that can be observed, for example presence of components, marks, blemishes, go / no go conditions.

For variable data there are two charts in common use:

X-bar and R Charts (see here for downloadable version of blank and completed)

X and R Charts (individuals and moving range). These are used where small amounts of data are available or sampling frequency is required to be relatively high.

With attribute data the following charts are available for use:

P-Chart - for inconsistent sample sizes and non-conforming uits

N-Chart - for inconsistent sample sizes and non-conformities (faults)

C-Chart - for constant sample sizes and non-confirmities (faults)

Np-Chart - for constant sample sizes and non-confirming units

For more information about how these charts are appplied, or for assistance in your SPC efforts please contact either myself, Graham Cripps on graham.cripps@resultsresults.co.uk or Julie Camp on julie.camp@resultsresults.co.uk

Answers to Capability Exercise are here!