Manufacturing businesses are today facing the fiercest competition. Also, raw material costs are rising. And the corporation can’t refute it. The corporation can employ statistical control here.

The organization must also consistently enhance efficiency, quality, and cost-cutting. Several companies also rely on inspection once the production process is finished.

With performance monitoring, the operator can easily spot process changes or trends. These changes must be known before non-conforming goods result.


We have summarized the statistical control approach below. So let’s get into the details.


Background of SPC (SPC)


Dr. W. Edwards Deming extended Dr. Walter Shewhart’s 1920 notion of Statistical Process Control.


After WWII, Japanese corporations used this practice. It is now used by all organizations worldwide. It keeps an eye on the company’s process and product to make money.


Statistical Process Control Definition


Statistical Process Control is a scientific method for monitoring and controlling products and processes.


What is Statistical Process Control (SPC)?


Statistical Process Control is a statistical method for measuring, controlling, and monitoring a process to assure product and process efficiency. Because variation is part of every process (whether manufacturing or service), organizations utilize various ways and instruments to control it.


SPC is the primary technique for detecting tiny variations in a process and controlling them.


List of important SPC findings!!


We have measured and confirmed the results with SPC throughout time. Some examples:


A solar company increased revenue by 700K by increasing yield/solar cell. A semiconductor company eliminated line inspection. A pharmaceutical company made over 850K/year by improving dosing accuracy and reducing scrap. A food company reduced obesity by 1% by integrating SPC with Big Data and OEE.




Not every organization benefits, but we may see better data entry, reporting, communication, and quality.


SPC Graph


The Shewhart chart is another name for the SPC chart. It is SPS’s main tool. It is a graph with data and control limitations shown. This plotted data was used to examine process variance.


It also has three lines to illustrate the variance level: the average control limit, the lower control limit, and the upper control limit.


The restrictions are based on historical data. Then the current data are compared to these lines to assess the process’s efficiency.




There are two sorts of control charts: variable and attribute.


Variable control chart: Used to assess product quality. The R-Bar, X-Bar, and SIGMA charts are examples.


Attribute control chart: This cannot measure product quality. It also requires a count of the traits. Examples are np, p, u, and c charts.




Steps involved in SPC Chart


First, the business sets a method to assess important waste areas such as rework and scrap.


Second, the time of evaluation must be determined for changes in Man, Material, Method, Movement, Machine, and Environment.


Finally, data will be collected on the process’s important areas.


The collected data and control limits are then placed on a graph (Statistical Control Chart) for analysis.


If the data stays inside the control boundaries, the procedure is working as planned. Any variance is attributable to a common or natural cause. But suppose the data is out of range. In that instance, the process is not working as planned due to unknown variables and must be corrected before the problem develops.




SPC helps improve processes by decreasing variability. Other goals can be easily achieved with SPC, such as:


fewer customer complaints and better customer satisfaction, establish a consistent and predictable level of quality, improve the operators’ motivation, better communication throughout the organization levels, lower investments due to process improvement, and more.


That’s why understanding statistical control principles is usually useful.


Also See




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Other SPC Tools


Check Sheet


Real-time data collection is a basic structured document. Analyze the faults where the data is generated. That arises to correct these faults in time.


2) Stratified


It is a flowchart that depicts the steps of the process in boxes. This tool categorizes data, people, and objects. It thus provides a visual picture of the process, allowing for rapid analysis and error detection.


3) Scattergraph


This tool is used to graph the possible association between two variables. It explains the relationship between the two variables and their strength. Using this strategy, data scattered near a trend indicates a significant link. And if the data are random. Then there is no association.


4) Hexagon


It depicts process variation by displaying data frequency. So it’s called Frequency Distribution. Thus, it aids in the distribution of a process’s output. It also finishes the customer’s requirements or checks for process variations.


5) Pareto


It’s a Bar Graph with the longest bars on the left. And the right side’s shortest bars. It represents expense, time, or money. The bar’s size is used to assess it. Preto is used to analyze problem or defect frequency. And the key areas to work on.


6) Cause-and-Effect


It’s also called a Fishbone Chart. This tool lists all the reasons of a process effect or problem. It specifies the key reasons of an issue such as machine, material, or manpower. Then, beneath each primary heading, are listed subheads of associated causes. So, anytime a process variation is suspected. This graphic can help an organization identify a problem’s root cause.


Remember this:


What are the essential elements to consider when automating SPC?


There are certain significant issues to consider while automating and implementing real-time SPC. So:


Integration of organizations and companies (up to 3 levels). Integration of other software such as MSA, CAPA, FMEA, OEE.Compliance with industry standards and regulations such as IATF 16949.Compliance with regulatory requirements such as FDA, AS13006, many languages, and reporting.


What are the SPC benefits?




It is a statistical method to track the process and assure its efficiency.




That way, corrective and primarily preventive steps can be performed before the alterations occur.




SPC lowers scrap and rework, lowering costs.




It helps make rapid decisions.




In today’s competitive world, SPC gives you an edge.




It will also boost product quality and productivity.


What are the SPC drawbacks?







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SPC Software


SPC Software completes the SPC approach. It collects real-time quality and performance data. SPC then statistically analyzes the data to find process variation and prevent it. It will improve operational efficiency.


How do SQC and SPC differ?


Statistical quality control (SQC) It is the use of 14 statistical and analytic tools. This monitors the process output (or we can say dependent variable).


Statistical process control (SPC) is an abbreviated form of SPC. An application for controlling the process input, 14 tools (that is, independent variable).


Although these words appear to be identical, SQC incorporates acceptance sampling whereas SCP does not.


The relationship between SQC (Statistical Quality Control) and SPC is illustrated here (Statistical Process Control).




A quick review of Statistical Process Control (SPC) (SPC)


SPC’s major goal is to balance the regulated manufacturing process using statistical approaches. It reduces process variation. The variation decreases to:


Better quality; fewer expenses (scarp, claims, waste, rework, etc.)


To create a controlled process:


The adjustments process needs to register to collect follow-ups and quantify the modifications’ effect.




Statistical Process Control (SPC) is a statistical method for controlling and monitoring a process so that unique causes can be avoided. It consists of numerous tools to improve this process.


It will help the company increase quality and production, save money and time, and maximize revenues. Thus, controlling and monitoring a company’s processes is one of the greatest tactics. If you like, we may do your CPM statistics homework for you at a low cost.


Questions & Answers


What is the major aim of SPC?


Statistical process control clearly influences quality methods. Thus, its concepts can be used to identify issues with a service or product.


What is quality control?


Peer reviews, inspections, and software testing are all examples of quality control activities. Process standards, project audits, process checklists, and process documentation are examples of quality assurance.