We chat to TLC’s IT Manager, Prineshan Amichand to find out why Statistical Process Control is his top tool:
What is Statistical Process Control?
Statistical Process Control (SPC) is an analytical decision-making tool which allows you to see when a process is working correctly and when it is not. Variation is present in any process, deciding when its variation is natural and when it needs correction is the key to quality control.
The foundation for Statistical Process Control was laid by Dr. Walter Shewhart working in the Bell Telephone Laboratories in the 1920s conducting research on methods to improve quality and lower costs. He developed the concept of control with regard to variation and came up with Statistical Process Control Charts which provide a simple way to determine if the process is in control or not. Dr. W. Edwards Deming built upon Shewart’s work and took the concepts to Japan following World War 2. There, Japanese industry adopted the concepts whole-heartedly. The resulting high quality of Japanese products is world-renowned. Dr. Deming is famous throughout Japan as a “God of quality”. Today, SPC is used in various industries around the world
When would you use this tool?
- Do you currently scrap, downgrade, and/or rework products?
- Do your customers demand consistently high-quality products?
- Are you interested in increasing productivity?
- Have customers requested quality-control documentation such as your “process capability index”
If you answered yes to any of these questions, SPC is for you!
- Statistical Process Control improves process performance by reducing product variability.
- Improves production efficiency by decreasing scrap and rework.
- Leads to higher quality products by reducing variability and defects.
- Improving overall business competitiveness
- Minimize reworks
- Minimize loss of sales
- Reduce returns from customers
Saved 20% of SPC specialist time
What are the general steps to take when applying it?
Proper Statistical Process Control starts with planning and data collection. Statistical analysis on the wrong or incorrect data is garbage, the analysis must be appropriate for the data collected. Be sure to PLAN, then constantly re-evaluate your situation to make sure the plan is correct.
Give examples where you used it and what the benefits were.
I helped a textile factory design and develop a Statistical Process Control System. Control charts were implemented to understand and improve the performance of the process. The company gained many benefits from the implementation of SPC, such as general quality awareness being created among the employees, and training on SPC are knowledge on quality concepts, a better understanding of processes, analysing processes using statistical methods and as a whole, made the employees a part of the quality control process.
Why do you like this particular tool?
Companies today are facing ever-increasing competition. At the same time, raw material cost continues to increase. There are factors that companies, for the most part, cannot control. Therefore, companies must concentrate on what they can control: Their Processes. Companies must strive for continuous improvement in quality, efficiency and cost reduction. Many companies still rely only on inspection after production to detect quality issues. The SPC process is implemented to move a company from Detection Based to Prevention Based quality controls. By monitoring the performance of a process in real time the operator can detect trends or changes in the process before they result in non-conforming products and scrap.
What advice would you give to others thinking about using it?
Before implementing SPC, the manufacturing process should be evaluated to determine the main areas of waste. Examples of manufacturing waste are process rework, scrap and excessive inspection time. It would be beneficial to apply SPC tools to these areas first. During SPC, not all dimensions are monitored due to the expense, time and production delays that would incur. Prior to SPC implementation, the key or critical characteristics of the process should be identified. Data would then be collected and monitored on these key or critical characteristics.
Prineshan Amichand is TLC’s IT Manager and course facilitator. He provides technical support to internal TLC team and external customers. Prineshan provides IT support for The Leadership Centre and is involved in designing and delivering technology solutions on projects as well as managing software licensing and provider SLAs. Prineshan facilitates TLC’s Lean FOCUS, Lean Leader Internship and Design for Six Sigma courses.