Statistical Process Control (SPC) is a technique for observing and managing a process to guarantee that it runs consistently and generates goods or services that meet quality standards.

What is Statistical Process Control (SPC)?

To monitor and manage a process, the statistical process control (SPC) technique leverages techniques from the statistical community. Recognising and minimizing process variation is the primary goal of SPC. The items or services that are created as a result benefit from quality improvements. SPC is widely used in the service, healthcare, and industrial sectors.

Types of Statistical Process Control (SPC)

Different types of control charts are commonly used in statistical process control (SPC)

1. X-bar and R charts

These graphs are used to track process variability and mean. The R chart tracks the range of the sample, whereas the X-bar chart tracks the average of a sample of data. They are used to detect changes in the mean or variability of a process.

2. Individuals and Moving Range (I/MR) charts

These graphs are used to track the means of subgroups or individual measures over time. The MR chart depicts the moving range between subsequent observations, whereas the I chart plots the individual measurements. They are helpful in processes where sampling is not possible or where individual measurements have more significance than subgroup averages.

3. p, np, c, and u charts

The p, np, c, and u charts are used to track the quality or frequency of mistakes or errors within the process. The np chart tracks their percentage, while the p chart tracks the number of defects per item, which is tracked by the u chart. They are used to discover mistakes or incidents.

4. Attribute control charts

A process’s percentage of non-conforming items is tracked using attribute control charts. They are frequently applied during quality control checks, where each item is categorized as either complying or non-conforming.

5 Time-weighted control charts

Time-weighted control charts for monitoring processes where measurements are taken at regular intervals but the intervals may change with time as described They help keep track of procedures that are influenced by cyclical or other periodic variables.

What is Process capability analysis?

A statistical technique called process capability analysis is used in quality control to evaluate a process’s capacity to reliably generate goods or services that satisfy customer requirements. Analyzing a process’ ability to match client needs while allowing for the necessary amount of variance is the aim of this approach.

The process capability index (Cpk), a statistical indicator, is typically used to calculate process capability. The width of the customer specification limits is compared to the spread of the process data to determine CPK. Cpk numbers greater than 1 imply a process that is more capable than necessary, whereas a Cpk value of 1 indicates a process that is only just able to meet the customer’s expectations.

Organizations can find areas where process enhancements are required by using process capability analysis. Process modifications can be made to restore control if the process is unable to satisfy client expectations. This could entail alterations to the process architecture, enhanced operator training, or increased raw material control.

Organizations that are dedicated to continuous improvement and want to make sure that their processes are running at maximum efficiency should consider using process capability analysis as a key tool. Businesses may boost customer satisfaction, cut waste and expenses, and become more cost- and waste-efficient by strengthening their process capabilities.

Benefits of SPC

Implementing SPC in your organization can provide several benefits, including:

  • Reduced defects
  • improved process efficiency
  • increased customer satisfaction
  • Lower costs
  • Increased profitability
  • Improved communication and teamwork

How to Implement the SPC Methodology

The SPC methodology consists of eight steps:

  1. Define the process.
  2. Collect data
  3. Plot the data.
  4. Calculate control limits.
  5. Monitor the process.
  6. Respond to out-of-control signals
  7. Analyze the process
  8. Improve the process.

What are SPC tools and techniques?

1. Control chart

One of the main SPC tools used to track and manage a process is the control chart. A control chart shows the evolution of process data graphically. The upper and lower control limits (UCL and LCL) define the boundaries of allowable fluctuation, and the center line represents the data mean. Control charts can be used to spot process irregularities and implement improvements by taking corrective action.

Types of Control Charts

1. Variable Control Charts
2. Attribute Control Charts

2. Pareto charts

Pareto charts are graphs that show how frequently flaws or mistakes occur in a process. They are used to prioritise activities to resolve the most frequent causes of flaws or errors

Advantages of Pareto Charts

  • Determine what causes a problem most significantly..
  • Prioritise problem-solving efforts.
  • Facilitate communication among team members.

3. Histogram

Histograms are graphs that show how data is distributed. They are applied to determine a process’s frequency and distribution of flaws or faults.

Advantages of Histograms

  • Identify the shape of the distribution.
  • Identify outliers
  • Identify clusters or gaps in the data

4. Fishbone diagrams

Diagrams that show the root causes of an issue are called fishbone diagrams. They help create corrective measures by figuring out the underlying reasons for flaws or faults in a process.

Advantages of Fishbone Diagrams

  • Identify the root causes of a problem.
  • Facilitate communication among team members.
  • Identify areas for further investigation.

5. Scatter Diagram

The relationship between two variables can be visualized with the help of scatter diagrams by plotting the values of the variables against one another. The values for both components for a single observation are shown at each point on the graph. The use of scatter diagrams in engineering, social sciences, and economics

Advantages of Scatter Diagrams

  • Identify the relationship between two variables.
  • The data ought to be reviewed for any trends or patterns.
  • Identify outliers

6. Process Mapping

A method for describing a process is process mapping. Making a flowchart of the process involving each step being represented by a symbol is called process mapping. Any inefficiencies or bottlenecks in the process can be found via process mapping.

7. Statistical Analysis

Data analysis and process stability are both determined using a set of methods known as statistical analysis. Techniques used in statistical analysis include the analysis of variance (ANOVA), regression analysis, and hypothesis testing. When attempting to identify patterns or trends in the data, statistical analysis is utilized to assess their statistical significance


Both statistical quality control (SQC) and statistical process control (SPC), which use statistical methods to monitor and control processes, are quality control methodologies. If there are some connections between the two approaches, their scope and application are unique.

SQC is a more general term that describes the use of statistical techniques to track and manage the quality of a good or service. SQC involves gathering data on output quality and applying statistical tools to analyze the data and identify any patterns or trends. Any stage of the production process, from the raw materials to the finished product, may be observed with SQC.

SPC, on the other hand, is a part of SQC that specialises in process monitoring and control. SPC involves collecting and analysing data in real-time in order to identify any differences from expected or desired results. The data gathered is utilised to modify the procedure, reducing errors and improving quality.

The degree of granularity between SQC and SPC is another significant difference. SPC is used at the process level; SQC can be used at the product level. This means that SPC is used to monitor and control the quality of a process that creates a product, but SQC can be used to monitor and control the quality of a single product.

In conclusion, SPC is a part of SQC that focuses only on the monitoring and control of a process, whereas SQC is a larger term that incorporates the use of statistical methods to monitor and manage the quality of a product or service. Both methods are crucial resources for ensuring quality and enhancing operational effectiveness in businesses.


SPC is a set of statistical methods that are used to monitor and control a process to make sure it stays in a state of statistical control and makes goods or services that meet customer needs.

SPC may help processes become more efficient, remove waste and rework, and save time and money.

A process’s common cause variation is a natural aspect of its variability and is part of the process itself. On the other hand, special cause variation is brought on by elements that are not a part of the regular process and can be located and removed

SPC distinguishes between common cause and special cause variation using control charts. On the chart, points outside of the control limits show special causes, while points inside the control limits show typical causes

A control chart is a visual tool for tracking a process over time and locating any variations with a specific root cause

The X-bar chart, R chart, and p-chart are the three control charts that are most frequently used.

An X-bar chart is used to track a process’s average over time.

An R chart is used to monitor the range of a process over time.

The percentage of nonconforming items in a sample is tracked over time using a p-chart.

A capacity index measures how well a process meets customer needs. It is calculated as the process variance divided by the permitted tolerance

Cp is a measure of the process’s ability if the process is centred at the goal value. Cpk is a measurement of process capability that takes process centering into consideration

Process capability analysis is a method used to determine if a process is capable of meeting customer requirements.

Process capacity analysis involves defining the process, gathering data, calculating process capability indices, analysing the data, and, if necessary, taking action.

A process improvement project is a planned strategy of enhancing a process through the use of data and statistical techniques.

Identifying the issue, measuring the process, analysing the data, improving the process, and controlling the process are the stages in a process improvement project.

A control plan is an outline of what is needed to keep process control. Each stage in a process are shown visually in a process flowchart.

Information with discrete categories or qualities, such as pass/fail or good/bad, can be categorised as attribute data. Data that can be measured on a continuous scale is referred to as variable data.

A histogram shows the frequency distribution of a set of data visually. SPC frequently uses it for analysing variable data

A visual tool for tracking a process over time is a run chart. Although it lacks control limitations, it is similar to a control chart.

A stratification analysis is a strategy for identifying patterns or trends in data by categorising it based on a specific trait or attribute.

An Ishikawa diagram, commonly referred to as a fishbone diagram, is a graphic tool for pinpointing potential sources of a problem. Its name refers to how much it resembles a fish skeleton

A Pareto chart is a graphical aid used to prioritise and concentrate on a problem’s most important factors or causes. It is founded on the Pareto principle, which claims that just 20% of causes account for 80% of consequences.

A process map shows a process’s inputs, outputs, and flow of operations.

Utilising SPC can help ensure that products or services are delivered on time and within budget constraints. Additionally, it can enhance overall process effectiveness and assist in locating and removing sources of consumer unhappiness.

SPC is a method for monitoring and controlling a process in order to produce output that meets consumer requirements and specifications. Six Sigma is a broader methodology that incorporates SPC as one of its tools and focuses on enhancing process performance and reducing errors or defects.

Leadership supports SPC by providing resources, conveying its relevance to the organisation, and integrating it into the strategic plan. Additionally, leaders are essential in creating a culture of continuous improvement and promoting employee participation in the SPC process

Data analysis is a key part of SPC. It includes collecting and analysing data to find patterns and trends in process performance. Making knowledgeable decisions about process improvement and identifying and resolving possible issues can both be done with this information.

A type I error is when a hypothesis is rejected when it is actually true. A type II mistake is when a hypothesis is accepted when it is actually false. When conducting hypothesis testing, it’s crucial to account for both kinds of errors because they both have potentially harmful effects.