What is Statistical Process Control (SPC)?

SPC is a strategy for process improvement that uses statistics-based techniques to evaluate the process and identify opportunities for possible improvements. It majorly focuses on quantifying, classifying, and reducing variability in the process. It helps in enhancing process stability by making the use of SPC tools. The 7 basic SPC tools are:

1. Check Sheet
2. Stratification
3. Scatter Diagram
4. Histogram
5. Pareto Chart
6. Control Chart
7. Cause and Effect Diagram (Fishbone Diagram)

Variable and Attribute Data

Data is a factual information (as measurements or statistics) used as a basic for reasoning, discussion and calculation. Data is important because without data, we cannot understand the process and when we cannot understand the process, we simply cannot control the outcome. Data is needed for problem identification and further improvements. We are focusing on two types of data

1. Variable data [Continuous data] – Measurement on a continuous scale. Examples: weight, time, cutting speed, etc.
2. Attribute data [Discrete data] – Data by counting. Examples: Defective parts, surface defects etc.

Variation

As data are collected, it is possible that it may deviate from its specified value. It is termed as Variation. It is almost impossible to manufacture a product that does not have variations from its specified limits. Even though the variation might be negligible, but it is present and cannot be avoided. There are two types of variation.

1. Common cause variation- If this type of variation is present in the process, it is considered as stable and controlled and the outcome is predictable.
2. Special cause variation- Results from one or more points outside the specified limit [control limit] and if present in a process, results in instability and out of control conditions.

Variation in any process cannot be eliminated completely, but it can be controlled through various tools.

How SPC helps in improving product quality?

With the advancement in studies on Quality control, it is found out that it is possible to reduce variation to a larger extent by making use of enhanced methods, such as SPC. Whether you are producing a small lot of a product or a batch of thousands of products, you need your product to be as per the design criteria. Thus, in any company, it is important to control the product quality as this further helps in customer satisfaction.

 SPC tools like Control chart helps you specify a control limit. The larger value is the upper control limit and the smaller value is the lower control limit and the centerline is the ideal value. Any value that is lying in the given range is acceptable and will be considered as a good quality product. After the production of a amount of product, sampling process is carried out. Product characteristics are being measured by a skilled person and the values are then noted. The variation of the sampled products is used to predict the variation in the whole lot. Thus, these tools are very useful as they save time, money and give a big picture of the quality of the products being produced.

Other such tools include Pareto chart. It is important to identify defects and the type of defects in the produced units. For example, the surface finish of the product might be inappropriate due to casting defects such as blow holes, misrun, slag inclusion etc. Data is collected by sampling and the number of defective products and its types is then obtained. The defect which appears the greatest number of times is taken into further consideration and corrective action is taken accordingly. It also helps in predicting how many products will be defective in the whole batch of production. By making the use of smart technologies, providing SPC tools, one can save a lot and get an upper hand in product quality as compared to their peers. Using data as input, one can get many useful outputs such as Cp index, PP index, Standard deviation, etc. These all helps in streamlining the product according to the design specifications, improving product quality and hence customer satisfaction.

• By Sharad Mishra