Introduction to Statistical Control

Today, manufacturing companies face increasing competition due to raw material cost and other factors like employees and resources. Therefore companies must concentrate on strategies to improve their level to come best in the market. Companies must try for continuous improvement in quality, efficiency and cost reduction. Many companies still rely on inspection after production for quality analysis. In recent trends, many control methods has come into existence which would increase the product quality.

Control plays a major part in every industry for the betterment of the process and the quality. For this purpose, statistical approach is used in many organizations. In statistics, controlling a variable attempts to reduce the effect of other variables i.e., it is an observational study effect of one variable is measured while all other variables are kept constant.For statistical control in research, during experiments, researchers assign variables randomly to the treatment group such that the variables are not interchanged and hence their effects are observed independently, and the defects are found out easily if there occurs a malfunction in the process.

There are several mechanisms for the process control and quality control. Statistical quality control refers, to the usage of statistical method that helps in monitoring and maintaining the quality of products and services. Acceptance sampling method and rejection method is followed based on the quality test conducted during testing method.


Statistical Process Control (SPC)

On the other hand, Process control is a discipline that deals with architectures, mechanisms and algorithms in order to obtain an output for the desired range. It is extensively used in industry in various parts of departments such as power plants, manufacturing, production, Manufacturing and so on. It enables automation and thus reduces human errors and wastage of resources.  Statistical process control is a processcontrol method that uses statistical methods to monitor and control a process to ensure that the process operates at its full potential.

SPC is used to reduce the process waste and to eliminate the step-by-step manufacture inspection. The concept of SPC was brought out by Walter A. Shewhart in early 1920s along with control chart for understanding the process and specification limits, eliminating assignable sources of variation and monitoring the ongoing production products.

Statistical Process Control (SPC) is a branch of statistics that combines time series analysis methods with graphical representation of data and thus helps to take a deep insight on data more quickly and in fast decision-making. Although SPC was introduced in the early before the six sigma approach it is still one of the most advantageous methods used in most of the organizations. SPC data is collected in the form of measurements of a product dimension or future or readings. The data is then recorded and tracked on various types of control charts. The data can be in the form of continuous variable or average.

Statistical Control

Fig.1-SPC plan implementation

It helps in ensuring whether the process is stable or not. An example for the process where SPC is applied is in the manufacturing lines. In industries, those who manufacture on large-scale experience confusions and conflicts during the process and the quality measurement. And as the reputation mainly depends on the quality, these control method are quite useful and easy to be implemented by the organization. It is more common in the manufacturing industries and in organizations which operate in multiple streams like manufacturing, production, testing and delivery.

SPC seeks to measure the quality of work in process, and its implementation is typically the first step towards total quality systems management. It is useful process improvement technique in getting and keeping a process on target with minimal variation. SPC emphasizes early detection and prevention of problems, which can benefit to production of quality products and hence time plays a major constraint in implementing SPC. SPC is cost-effective as if the process changes, it leads to the wastage of the resources. Another major problem in implementing SPC is the misunderstanding of the real concept of SPC.

Control Charts

Statistical Control or Process Control can be obtained by various statistical control charts and the best suitable method is the usage of control charts. Control charts, also known as Process-Behavior Chart is a statistical process control tool that determines if a process is in stable state or overwhelmed. It is one of the most useful tool in the fields of management and can be applied in any modes of management like planning, organizing and in decision making. It is used to control the process when the control goes out of hand. It is a graph that depicts how the process changes over time.

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Fig.2-Example of SPC Chart


The control chart changes according to the process and the outputs obtained in each and every process. A control chart is used to keep the process and quality under control. A control chart has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data. The analysis of control chart indicates whether the process is under control or not. If not stable, the precautionary measures to make it stable can be taken. It is one of the seven basic tools of quality control.

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Fig.3-Normal Distribution

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Fig.4-terms used in Control Chart


The control chart uses various parameters such as normal distribution, mean, and standard deviation for the measurement of the variables by which the efficiency is determined. Normal distribution is defined as the heart of SPC as its typical Gaussian distribution curve les in the heart of the mathematical model that illustrates statistical process control. Normal distribution is based on principle of limitless totality. 

Control charts consists of control limits which are known as Tolerance limits of the sample series. Control limits are used for the mean and mean variation of a series. One of the most commonly used control chart for variable data is X bar and R chart. X bar represents the average and it displays the variation in the sample data collected. Once the chart is set up, the operator will measure multiple samples and calculate the average. This value is recorded and depicted in the chart.

Control chart reveals the factors like variations in material properties, seasonal changes in temperature or humidity, normal machine or tear, normal measurement variation. It also includes special cause variation such as process shift, machine malfunction, broken tool and inexperienced operator. These changes should be identified and corrective actions should be taken.

Contents of Control Chart

Basically, a control chart consists of points that resemble a statistic for measurement of quality characteristic in samples that are taken at different times, the mean of those statistic samples calculations, a central line at the value at the mean of the statistic, the standard deviation calculations for the statistic samples and the upper and lower limits that indicates the threshold between which the graph is drawn.

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Fig.5-Points on a SPC chart

The chart may also contain warning and control limits depending upon our needs. The purpose of control charts is to allow simple detection of events that indicate the actual process change. SPC is used as a real time method implementation in various organizations and baldor is one of the examples for it.

Application

Baldor is one of the organizations that implement SPC on the ongoing process in the management. It is one of the leading producers of industrial electric motors, power transmission products and generators. At baldor, the management believes in product quality as much as production quantity to ensure the level of quality baldor decided to institute a policy dedicated to consumer satisfaction and this policy was entirely based on statistical process control. The management reveals that this solution is user friendly for production and was quickly adopted by their employees. SPC was instituted into baldor, a corporate culture with quality personnel, engineers and managers all using data to improve processors.

After the implementation of SPC, baldor evaluated the successful SPC techniques and founded the user-friendly interface and better inspection tools and methods. The methods produced faster, more accurate inspections with reduced cost. These savings eliminated the handwritten charts and log books with control charts. As, a result of this implementation, baldor was able to measure improvement in quality throughout the manufacturing process.They reported 66% annual dollar savings while others reported only 63% annual dollar savings. Baldor’s customers are on the winning end of quality improvement and reported 48% reduction in warranty claims.

Conclusion 

Recently, an infinity QSProFicient software with SPC was developed that can detect production errors as it occurs and such that it alerts you before it is too late. It allows data to stream in real-time to a central quality control hub. With this real time data you will be able to alter specific aspects of your production.

This will increase efficiency and provide maximum control over process and quality. SPC Software is the tool that will allow this process to take place. It reduces the monthly reports and the software provides fast and accurate comfort so that take holders can confidently move forward with organizations plans without any confusions. Hence, SPC has been proven as a best solution for the upcoming challenges in the field of business.

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