فهرس المصطلحات
Statistical Process Control (SPC)
Tags: فهرس المصطلحات
A method for achieving quality control in processes, the technique hinges on the observation that any process is subject to seemingly random variations, which are said to have common causes, and non-random variations, which are said to have special causes. SPC relies on measuring variation in output and setting control limits based on observations of variations arising solely from common causes. A process that is 'in control' is expected to generate output that is within the control limits.
What is Statistical Process Control (SPC)?
Statistical Process Control (SPC) is a powerful tool used in logistics to achieve quality control in various processes. It is based on the understanding that any process is subject to two types of variations: common causes and special causes.
Common causes refer to the seemingly random variations that naturally occur in any process. These variations are inherent to the process itself and are expected to happen. On the other hand, special causes are non-random variations that arise due to specific factors or events that are not part of the normal process.
The goal of SPC is to identify and differentiate between these two types of variations. By doing so, it becomes possible to determine whether a process is "in control" or "out of control." A process that is in control is one where the output consistently falls within acceptable limits, while an out-of-control process exhibits variations beyond the expected range.
To implement SPC, measurements of the process output are taken at regular intervals. These measurements are then analyzed to determine the amount of variation present. Control limits are established based on observations of variations arising solely from common causes. These limits define the acceptable range within which the process output should fall.
When a process is in control, the output is expected to remain within the control limits. However, if the output consistently exceeds these limits or exhibits patterns that deviate from the norm, it indicates the presence of special causes. In such cases, further investigation is required to identify and address the underlying issues causing the out-of-control variations.
SPC provides several benefits in logistics. It helps in detecting and preventing defects, reducing waste, and improving overall process efficiency. By continuously monitoring and analyzing process variations, organizations can make data-driven decisions to optimize their operations and ensure consistent quality.
In conclusion, Statistical Process Control is a valuable technique used in logistics to achieve quality control. By distinguishing between common and special causes of process variations, SPC enables organizations to identify and address issues, leading to improved efficiency and consistent output within acceptable limits.