Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.
Introduction
When processing or manufacturing a new product, the manufacturer needs to ensure the quality of the products meets the customers expectations. Quality control (QC) is a process through which the quality of a product is assessed, maintained, or improved (Eissa, 2018). Quality control is essential to create an enabling environment where employees and management strive for perfection. QC is done by creating quality product benchmarks and testing tools that check for statistically significant variations (Eissa, 2018). Consequently, these controls help the manufacturers to establish well-defined controls by limiting any room for errors.
Discussion
Control charts are examples of QC used in operations and manufacturing departments. Othman et al. (2019) defined control charts as graphs used to monitor the quality of a product being manufactured or processed. For instance, during the production of electric black box items for vehicles, a company may need to monitor the quality of the boxes to ensure that they meet the requirements of automatic driving (Eissa, 2018). A printed circuit board with a solder paste is placed on top of the electric component in preparing electric boxes. To ensure the success of this process, the application of control charts is encouraged.
A control chart has three lines. The central line (CL), the UPL (upper control limit), and the lower control limit (LCL). During the production of the electric boxes, the producer must ensure that the process is in control. This happens when the graph is always between UPL and LCL. On the contrary, when the graph moves out of UPL or LCL, the production is said to be out of control. Further, if the production generally lies within the CL, then the production is within the recommended average.
Thus, the control chart helps monitor the oven temperatures needed for pasting the solder paste on the black boxes. Once the results are populated on the control chart from the computer, it becomes easy to monitor the temperatures and ascertain whether they lie within the specified temperatures. In this experiment, the control readings were within the specified temperatures from zero minute to the 11th minute (Eissa, 2018). However, on the 12th minute, the temperatures were out of the UPL range. Consequently, the production was out of control, so the a need to contact the supervisor to bring the production within the recommended temperatures.
Systems that are out of control can be brought back to control levels with the application of the Western Electric Company (WECO) rules. Velinovska et al. (2019) defined WECO rules as decision rules that help manufacturers detect out-of-control systems in statistical processes (Eissa, 2018). However, for the WECO rules to be applied, the system must fall within ±3 of the standard deviations. In this system, the recommended temperatures and the out-of-range temperatures in the oven are not given, which makes it difficult to calculate the mean temperature of the oven and the standard deviation of the out-of-control temperature (Othman et al., 2019). Consequently, it is impossible to tell the extent of the standard deviation in the control chart, making it challenging to apply the WECO rules. In this case, WECO rules could be applied or not.
Conclusion
In general, control charts play an essential role in monitoring the quality of the products in the final project. For instance, in this project, control charts play a significant role in controlling the quality of electric boxes by monitoring the temperatures in the oven. Furthermore, control charts are easy to use compared to other QC tools.
References
Eissa, M. E. (2018). Adulterated pharmaceutical product detection using statistical process control. Bangladesh Pharmaceutical Journal, 21(1), 7-15. Web.
Othman, L. M., Ponchet-Durupt, A., Boudaoud, N., Bosch-Mauchand, M., & Cherfi-Boulanger, Z. (2019). Integrated decision rules for adaptive condition-based maintenance and multivariate control charts. Proceedings of the 29th European Safety and Reliability Conference (ESREL). Web.
Velinovska C., M., Popstefanova, N., Ilievska, M., Karadzinska, E., Davceva Jovanoska, M., & Glavas Dodov, M. (2019). Trending and out-of-Trend results in the pharmaceutical industry. Macedonian Pharmaceutical Bulletin, 65(01), 39-60. Web.
Do you need this or any other assignment done for you from scratch?
We have qualified writers to help you.
We assure you a quality paper that is 100% free from plagiarism and AI.
You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)
NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.
NB: All your data is kept safe from the public.