Operator SPC automatically gathers data from various production resources. However, it is not just a simple machine monitoring tool. With Statistical Process Control (SPC), you have a single point of access to all information relevant to the production process.
The Operator SPC module is embedded within one standard manufacturing monitoring client application. It offers users access to real-time data, which can be displayed directly within a user’s workstation consoles or on a Operator Mobile APP. Operator SPC can be applied to any process in which the product output (specifications) can be measured. The SPC adds value by allowing for the examination of the parts of processes that may conceal sources of variation in product quality.
By monitoring and controlling the process values, the SPC module ensures that your production continuously operates at its full potential. The Operator SPC enables optimization of production with the minimum of waste, rework or scrap.
Operator SPC allows you to make decisions based on facts and real-time statistical data.
Today’s customers are placing ever higher demands on service providers. In order to meet them, entrepreneurs must take care of the quality of production of their products or services. Statistical Process Control is a method which in a systematic way helps to establish and maintain the quality of processes (with simultaneous reduction of production costs).
What is SPC?
Statistical Process Control (SPC) is a method of quality management using appropriate statistical tools. Thanks to SPC, it is possible to examine, check and measure the process of product manufacture which gives the possibility to react quickly enough in case of deviations from the standard. The main tool used in SPC are Shewhart control cards, which are used to monitor the process as it is happening. Thanks to control cards using objective criteria, it is possible to distinguish natural variability of process parameters from non-random events using statistics. By using control cards, quality can be significantly improved and process efficiency can be increased.
What benefits can be achieved with SPC?
The key benefits of using statistical process control are:
Walter Shewhart and William Deming are considered the fathers of SPC. The former applied the method to the automotive industry as early as the 1930s. Shewhart noted that natural processes behave differently than industrial processes and cannot be uniquely characterized by Gaussian distribution (one of the most important probability distributions). So he developed innovative tools and methods to control industrial processes.
In the 50’s and 60’s of the twentieth century, the SPC method was successfully propagated by William Deming. He transferred his knowledge in post-war Japan, on the basis of which the Japanese built a powerful economy. Western industries became interested in Deming’s methodology only in the 80s of the twentieth century.
Statistical process control is a method used to this day throughout the world, most often in manufacturing industries.
Statistical process control (SPC) is a set of tools that help you identify the sources of variation in your process and take corrective action to reduce or eliminate these variations.
Some industries use SPC for quality control, while others use it for identifying the root-cause of problems.
It can be used to check if there are any changes in the production process, which might affect delivery dates or product quality.
Statistical process control (SPC) is a statistical method of analyzing and controlling processes to make them more predictable.
SPC will help improve the organizational performance by ensuring that the production process is managed in such a way that it meets customer requirements and expectations at all times.
Uneven distribution of products for sale for example, on a shelf, on a production line or in the warehouse can be identified and corrected with SPC.
Statistical process control / SPC is a technique that can be implemented to ensure that a process is stable, predictable and efficient.
One of the most common techniques to implement statistical process control is the use of control charts. Control charts are used to monitor quality or performance of a given process. They also provide information on how the data relates to an average or central tendency. Other techniques include:
– Cause and effect diagrams
– Prediction tables
– Time series plots