On surveillance methods for drifted processes

In this current era, manufacturing processes are highly capable of producing conforming products. However, due to wear and tear of the machining parts, the manufacturing processes do not remain stable and hence cause non-conforming products over time. Fore example, the machine's needle plays a significant role in adequately sewing garment products in manufacturing. When the needle tip is damaged, the flaws in sewing increase with time. In literature, such gradual changes over time are known as drift, while a sudden temporary change is known as shift. Generally, location control charts are used to monitor the processes' shifted mean. However, these charts are not widely discussed under the drifted setup; therefore, this study is intended to show the performance of location charts under linear and quadratic shifts. A simulation setup is designed to assess charts' zero-state and steady-state run length performance under normal and non-normal setups. Moreover, the proposed charts are implemented on a real-life dataset to highlight the stated proposal's importance.