The expansion of digital transformation across all industries has made the need for businesses to remain digitally competitive integral to scaling and growing. Utilising software that improves product uniformity and process control is one way business’ can maintain a competitive edge on their competitors.
Statistical Process Control (SPC) is an effective process improvement tool and has been long adopted by the manufacturing industry, and more recently within the healthcare sector. However, the reach for SPC implementation is not limited to any one industry.
SPC software helps professionals identify inefficiencies in processes that would benefit from change, and give decision makers at all levels complete data sets, enabling informed decision making.
Find out how BCN Group can assist your business with Statistical Process Control.
What is Statistical Process Control?
Statistical Process Control is the use of analytical tools that plot data over time to help users visualise variations in their data. Understanding these variations helps guide decision makers to take the best course of action to standardise their data.
What makes SPC process improvement so effective is that it enables users to easily see whether or not an implemented change has resulted in improvements. By employing SPC software rules to data, users are able to tailor SPC charts to the specific process they are measuring.
Can your business use SPC tools?
Statistical process control has been implemented across numerous service-orientated industries, such as in healthcare, financial services, manufacturing and public services. However, any organisation or industry that uses repetitive processes would be appropriate for implementing SPC software. So long as your business have measurable products or processes, SPC can be applied.
SPC software enables users to understand the performance of processes over time and whether the process they are measuring is in statistical control, and therefore predictable, or unstable and therefore unpredictable. As well as enabling users to understand whether a process is capable of meeting a desired level of performance.
Increased competition and rising operational costs make SPC implementation a logical step for decision makers to have better control and visibility over business operations. From time and cost efficiencies to helping with quality control, there are numerous benefits that businesses can gain from SPC implementation.
Understanding Statistical Process Control charts
There are two main chart types in SPC software; Run and Control charts.
Run Charts
Simply put, Run charts are line graphs of data plotted over time. By continually collecting and charting data over time, the Run chart visualises trends or patterns in what your measuring.
The Y-axis shows a measurement I.e. count, plotted over time on the X-axis. Additionally, a centre line (CL) is generally drawn at the median of measurements.
A ‘run’ is when one or more consecutive data points fall on the same side of the median.
Run charts visualise the performance of processes, enabling users to see patterns in the variation of their data, as well as show whether an implemented change has resulted in an improvement, and whether that improvement has been sustained.
Control Charts
The control chart is the more advanced version of the run chart, yet just as simple to understand.
Like the Run chart, the Control chart depicts a single line of data, but includes an ‘Upper Control Limit’ (UCL) and ‘Lower Control Limit’ (LCL) line.
The addition of the UCL and LCL allow professionals to decipher between common (normal) and special cause variation in data.
The central line is generally drawn at the mean of measurements.
Control charts have their own set of rules for identifying special causes which are commonly different from the rules applied to Run charts.
How bread baking can help us understand variation in Statistical Process Control
Common Cause Variation
Common cause variation are causes that are inherent in a system over time. Common cause variation fall within the control limit (within the UCL and LCL) of a control chart, and show that a process is stable over time.
An example of common cause variation can be seen through the process of baking a loaf of bread. A common cause of variation would be the oven’s thermostat slightly altering the temperature of the oven during the baking process, something we would expect to occur.
Special Cause Variation
Special cause variation are causes that are not part of the process or production methods, but arise due to specific circumstances. Special cause variation are the assignable causes of variation in a process and the focus on process improvement.
An example of special cause variation would be the changing of an ovens temperature as a result of opening the oven door during the baking process, causing needless temperature fluctuation.
Benefits of SPC
Eliminates non-conforming products
Improves process reliability and quality
Improves operational efficiency
Identifies and reduces process errors
Streamlines processes
Time efficiencies
Cost efficiencies
Improved customer satisfaction
Prevents rubbish in, rubbish out
Business-wide efficiency improvements
How BCN and Cloud2 saved ELFT 19 staff days every day
Why choose BCN Group?
BCN Group are in the unique position of being one of only a handful of SPC software providers in the UK. With our experience in Statistical Process Control, Industry leading expertise, and our own, in-house built SPC Charts, we can provide your business with the skills, knowledge, and services you need.