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Why Statistical process control (SPC) is crucial?
Introduction to SPC
Statistical Process Control (SPC) is an approach to process control that has been widely used in any industrial or non-industrial fields.
Statistical Process Control (SPC) is based on so called Shewhart ́s conception of the process variability. This conception distinguishes variability caused by obviously effected common causes (process is considered to be statistically stable) from variability caused by abnormal assignable causes (process is considered not to be statistically stable).
The main goals of Statistical Process Control (SPC) is an identification of abnormal variability caused by assignable causes with the aim to
- make the process stable,
- minimize the process variability,
- improve the process performance
Benefits of Implementing Statistical Process Control (SPC)
Every year, customers save millions of dollars by cutting down on scrap and rework while optimising process performance. With numbers like these, An effective Statistical Process Control (SPC) program provides a strong ROI in both large and small-scale implementations. In today’s challenging economic environment, with its shrinking corporate budgets, companies like yours need investments that rapidly yield quantifiable returns. SPC is one of the tool to help you do just that.
We recently conducted a survey of our clients to quantify the results of implementing Statistical Process Control (SPC). Clients responded with savings in several key metrics. The average results are as follows:
- 12.7% Weekly Scrap Reduction
- 14.3% Man-hour Rework Reduction
- 12.9% Defect Cost Reduction
- 14.1% Warranty Claim Reduction
Recalls cost manufacturers billions of dollars each year in production losses and damage to their brands’ reputation. An effective Statistical Process Control (SPC) implementation provides complete visibility into both your internal and supplier quality data, minimising the possibility of costly recalls.