It has been seen that manufacturing companies are facing the toughest competition nowadays. Also, the cost of raw material is increasing side by side. And this is what the company can not deny. Here, the company has the option to use a statistical control process.
In addition to this, the company needs to improve efficiency, quality, and cost reduction continuously. It is also seen that several companies rely on the inspection process once the production process gets completed.
With the help of performance monitoring, the operator easily detects the changes or the trends of the process. These changes are necessary to know before resulting in non-conforming products.
Below we have detailed all the useful and key points about the statistical control process. Scroll down to get familiar with the topic, so let’s move to the details.
Background of Statistical Process Control (SPC)
In 1920, Dr. Walter Shewhart of Bell Laboratories developed the concept of Statistical Process Control, and then it was expanded by Dr. W. Edwards Deming.
After that, this methodology was used by Japanese firms after the Second World War. Nowadays, it is used by all organizations around the world. It helps to keep a check on the organization’s process and product to earn profits.
A Short Definition of Statistical Process Control
Statistical Process Control can be defined as the scientific methodology to monitor and control the product and process method.
What is the meaning of Statistical Process Control?
Statistical Process Control is a statistical method to measure, control, and monitor the process to ensure the efficiency and effectiveness of the product and process. Since variation is an inherent part of a process (whether manufacturing or service, etc.), the organizations use different methods and tools to control such variation to get desired results.
SPC is the primary tool to detect even the small variation in a process so that corrective and preventive steps can be taken to control the process.
List of some important examples of SPC results!!
Over the years, we have measured and verified the result with the SPC implementations. Some important examples are:
A solar organization’s income has increased by 700K with the increasing yield/solar cell.A semiconductor organization eliminates the line inspection process.A pharmaceutical organization profited more than 850K/year accurate dosing and scrap reduction.The food company is able to reduce the overweight by 1%.The medical instrument company integrated SPC with Big data and OEE and saw an increase of 25% productivity within the 3 months.
Not each company sees high results, but we can see more efficient data entries, reporting, better communication, and improved quality.
Statistical Process Control Chart
The Statistical Process Control Chart is also called a Shewhart chart. It is the primary tool of SPS. It is in the form of a graph in which data and control limits are plotted. And this plotted data used to analyze the variation in the process.
Besides, it manifests three lines to show the variation level; these are the central line for the average control limit, the lower line for the lower control limit, and the upper line for the upper control limit.
These limits are evaluated as per the historical data. After that, the present data are compared with these lines to conclude the efficiency of the process.
Key Point
There are two different types of control charts, that is variable and attribute control charts.
Variable control chart: With the help of this, you can measure the product’s quality characteristics. Its examples are the R-Bar chart, X-Bar chart, and SIGMA chart.
Attribute control chart: With this, it is not possible to measure the product’s quality characteristics. Moreover, it needs observations’ count on the characteristics. Its examples are np-chart, p-charts, u-chart, and c-charts.
List of the steps involved in SPC Chart
Firstly, the organization establishes a process to evaluate the key areas of waste like rework, scrap waste, etc.
Secondly, the period during which such a process is to be evaluated must be determined concerning variation in Man, Material, Method, Movement, Machine, and Environment.
At last, data will be collected on the predetermined key areas of the process.
After that, the data collected and the predetermined control limits are plotted on a graph (i.e., Statistical Control Chart) for analysis.
If the data confines under the control limits, then it implies that the process is operating as expected. Even if there is any variation, then that is due to a common or natural cause. But suppose the data is outside the control limits. In that case, it implies that the process is not operating as expected due to unforeseeable factors and needs to be fixed before the actual defect occurs.
Why is Statistical Control Process important?
SPC is useful to enhance the processes by reducing the variations continuously. With the help of SPC, it is quite easy to meet other objectives, such as:
eliminate or reduce the requirement in the supply chain ,decrease scarp, inspection cost, and rework, more efficient analysis, data entry, and reporting, improve productivity, fewer customer complaints and improve customer satisfaction, establish the consistent and predictable level of quality, enhance the operators’ motivation, make better communication among the organization levels, lower investments due to improvement in the process, and more.
That is why it is always useful to understand the concepts of the statistical control process.
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Other Statistical Process Control Tools
1) Check Sheet
It is a simple structured document to collect the data in real-time. At the place where the data is generated and analyze the defects. That arises so that these defects can be timely cured.
2) Stratification
It is a type of flow chart which shows the whole process in steps through boxes. This tool divides the data, people, and objects into distinct groups. It thus gives the visual representation of the process, which helps analyze the whole process quickly and find out the defects therein.
3) Scatter Diagram
This tool is used to study the possible relationship between two variables through a graph. It helps to understand the relation between the two variables and the strength of the same. Under this method, if data is scattered close to a trend, it depicts a strong relationship or vice-versa. And if the data are randomly scattered. Then there is no correlation between such variables.
4) Histogram
It shows the variation in the process by showing the frequency of occurrence of given data. That is why it is also called Frequency Distribution. Thus, it helps conclude the distribution of the output of a process. Moreover, it concludes about the customer’s requirements or checks whether any variation has occurred in the process.
5) Pareto Chart
It is a kind of Bar Graph in which the longest bars are shown at the left. And the shortest bars on the right side. It represents the frequency of cost, time, or money. And it is evaluated through the size of the bar. Preto is used to analyze the frequency of any problem or defect in the process. And the critical areas to be focused on.
6) Cause and Effect Diagram
It is also known as Fishbone Diagram. This tool states all the causes of a particular effect or problem in a process. It prescribes the major heads of causes of any problem like Machine, Material or Manpower, etc. After that, subheads of all causes related to it are listed under each main head. So, whenever any variation is suspected in the process. The organization can detect the cause of such a problem or effect through this diagram.
A key point to remember
What are the key points to consider at the time of SPC implementation & automation?
There are some major points that you need to consider for automation and real-time SPC implementation. And these are:
Helps in integrating the organizations and companies (upto 3 levels),It supports integrating with other software such as MSA, CAPA, FMEA, OEE.The aspect of a particular company or industry requirements like IATF 16949, Legal requirement, centralization, FDA, AS13006, multiple languages, and reporting.Needed functionality.Integrate with IT architecture, like MES, Big data, ERP, and software.Integrated with measurement systems (like CMM and more) and gages.Local and training support.
What are the advantages of SPC?
- It is a statistical method to track the process to know whether the process is in control, which ultimately ensures the efficiency of the process.
- It helps to detect even the small changes in the process so that corrective and primarily preventive measures can be taken before the changes arise.
- SPC will lead to reduced scrap and rework and thus reduces the cost.
- It helps to make real-time decisions instantly.
- SPC helps to have the edge over the competitors in today’s competitive world.
- Importantly, it will improve the overall quality and productivity level of the products.
What are the disadvantages of SPC?
- Time requirement: SPC needs early detection and problem prevention. This can benefit quality product production. It also needs time to apply in the manufacturing settings.
- Cost consideration: The implementation of SPC is quite costly. In some cases, you are required to contract with professional consultants to get the personnel training. And these are not cheap.
- Lack of cooperation: SPC depends on the operators to give information regarding the process. It is done using the charts that use to monitor the production line. The implementation can be done with the other tasks using the production personnel. This leads to a lack of cooperation.
Statistical Process Control Software
SPC Software performs the complete procedure of SPC methodology. It collects the quality and performance-based data of the organization in real-time. SPC then statistically analyzes the same to detect the variation in the process to take preventive actions before such variation occurs. It will maximize operational performance.
What is the difference between SQC and SPC?
SQC is the short form of Statistical quality control. It is explained as the 14 statistical and analytic tools’ application. This is used for monitoring the process output (or we can say dependent variable).
At the same time, the SPC is the short form of Statistical process control. This is the same 14 tools application used for controlling the process input (that is, independent variable).
Although these terms might seem to be interchangeable, it is important to note that SQC involves acceptance sampling, but SCP doesn’t.
Below is the picture used to represent the relation between SQC (Statistical Quality Control) and SPC (Statistical Process Control).
A quick recap about Statistical Control Process or Statistical Process Control (SPC)
The main objective of SPC is to balance the controlled manufacturing process with the help of statistical techniques. It helps in reducing the process variation. The variation decrement results in:
lower costs (scarp, claims, waste, rework, etc.);better quality;provide useful insights into the process capabilities;
To come up with the controlled process:
The measurements need to register accurately;The decisions should be taken as per the proper procedure (OCAP) and analysis;The data need to be analyzed in a better and accurate way (SPC);The adjustment process needs to register to get the follow-ups and estimate the adjustments’ effect.
Conclusion
Statistical Process Control is a statistical method to control and monitor the process to evaluate the issues related to such a process beforehand by comparing through control limits so that corrective measures can be taken to avoid such special causes. It consists of various tools to make this method more efficient.
It will help the business improve its quality and productivity, save the cost and time of the business, and maximize the business profits. Therefore, we can say that it is one of the best strategies for a business to control and monitor its processes. If you want, then you can get CPM statistics homework help from us at affordable prices.
Frequently Asked Questions
Which is the main focus of statistical process control?
It is quite clear that the statistical process control has a significant influence over the quality methods. Therefore, its concepts can apply to detect the problems at the end of the service or product.
What are quality control examples?
Some of the major examples of quality control activity are deliverable peer reviews, inspection, and the software testing process. On the other hand, quality assurance examples include process standards, project audits, process checklists, and process documentation.
Which is one of the most widely used tools in statistical process control?
It has been seen that the Control chart considers as one of the most widely used tools in SPC.
