Quality Control and Process Capability in Manufacturing Assignment Sample

Part A - Stewart and CUSUM Control Charts for Quality Monitoring

Stewart and CUSUM control charts

“n=2”

“d2=1.128”

In order to find the plotting position the new point in the cumulative sum chart is required to be formulated

Where

Sn= Plotting point

k= Reference value or the center line for cumulative sum chart

xi= The new point that is required to plot

T= Target value

σx= Standard deviation

In order to analyze the value the new point is being set to be 80 in the cumulative sum chart for the standard deviation 5. The target value is 70 and K=0.5

In order to derive the plotting position the new point is being formulated to be 80 in the cumulative sum chart that is being derived with the formula of

“Plotting position = k + [(xi – Target value) /σ]”

Where

k= 0.5

xi=80

Target value =70

σ=5 standard deviation

So the derived value is“Plotting position = 0.5 + [(80 – 70) / 5]”

“Plotting position = 0.5+2=2.5”

In order to calculate the reference value the allowance stock is derived

“k=0.5 σ = 0.5*0.0169 = 0.00848”

“Computing the decision interval with H, generally, +-4σ = ± 4”

*0.0169=+-0.0679

UCL= =0.0679 and LCL= -0.00679

THE TARGET VALUE IS 0.21

“Upper CUSUM (UCi) = Max [0, UCi-1+xi – Target value-k)”

“Lower CUSUM (LCi) = Min [0, LCi-1+xi – Target value)”

First sample 0.235

• Upper CUSUM (UC1)= Max[0, 0+0.235– 0.21-0.0084) =0.017
• Lower CUSUM (LC1)= Min[0, 0+0.0235-0.21+0.00848) = 0

In order to derive the second sample =0.222

• Upper CUSUM (UC1)= Max[0, 0.017+0.222– 0.21-0.0084) =0.02
• Lower CUSUM (LC1)= Min[0, 0+0.0222-0.21+0.0084) = 0

The CUSUM calculation is being done with the estimated standard deviation of the data from the range control chart σ= R?/d2

Table: UCi&LCi value in the graph

The above table helps to represent and make the standardization on the table that helps to indicate the process for control at the sample and deriving the outcome of the whole result. S is applicable to the access and makes the inspection with 83 when it has to meet the CUSUM chart control system.

Suitabilityanddiscussionofcontrolchartfindings

The control chart findings are accessible to have the quality assessment of statistical quality control to hence the quality. It is making the improvement with the overall sustainability that is applicable to managing the system and needs to meet the desired outcome. It is applicable to improve the returned and desired profitability, enhancing the overall dignity and meeting the desired properties with the latest possible defects to maximize the profit. Votto et al. (2021) stated that Quality is regarded as an important built-in feature of the project. It is accessible to enhance the overall standard that is required to meet the desired outcome and improve the overall standard. It is making the helmet with the stand work that is applicable to assess and make the system with the favorable characteristics that aim to user’s performance. It is applicable to manage and hence the system with the overall accessibility and control of the system.

Henry Ford introduced an implemented mass productivity is something important to achieving the overall credential. People and machine accessibility are required to meet the overall applications with the outcome of making the changes and achieving overall stability. The specific quality problem is required to manage the system that is accessing and maintaining the dignity in the system to achieve the overall standard. It is improving the overall stability with the standard diversification that is making the changes and meeting the objective. Atta et al. (2020) stated that the excitement is applied to manage the system with the development department and create the excitement to meet the overall improvement. The additional resource and development department aims to produce goods for different markets. Statistical quality control is widely used to access and manage the business world. Control charts are deemed the modern business world. A control chart is applicable to manage the national and international standards that are required to examine and control the chart system.

Processcapabilityanditssignificance

Quality control is a system to make the development that is applicable for setting uniform standards of production in quality at minimizing the level of cost. It is accessible to manage the system that is achieving corporate efficiency. Quality control is making improvements in the site, with the density to solve and maximize the profitability of modern management. Hryniewicz et al. (2019) said that the principal purpose of the statistical study is to improve the overall dignity and make the equivalent standard with the growth and proportion in the quality. It is accessible to set an image of the quality of production that synchronizes the overall dignity. The unpredictability in the shift is affecting the investigation process and control of the system. It is accessible to manage and leads to improving the overall stability and making the work more effective. Viloria and Lezama (2019) said that the ultimate research is adaptive to making the occupation for the process and enhancing the overall performance. The identification is required to meet the overall standard worth optimizing the value that is valuable to the source and make a lot of the process for the subprocess in optimizing the value.

use my discount

It enhances the overall dignity with the involvement of a manufacturing process that is liable to solve and achieve significant importance. The overall development is being set with the credentials to solve and manage the system. It is improving the dignity to solve and make the system more accessible with the statically controlled system and managing the tools for the control chart. Zaman and Hassan (2021) said that the statistical purpose is to identify and make the system more sustainable with the changes and overall credentials in making the process more effective and sustainable. It is managing the system with the overall consequences that lead to achieving the subject and making the diligence in the statistical process control.

Part B - Quality Management Systems and Process Capability Studies

Qualitymanagementsystemsandqualityassurance

It is very important to point out the important facts that the capability studies mainly fit into the “quality management systems and quality assurance”. Process capabilities are primarily defined as the “statistical measure of the inherent process variability of a given characteristic”. Someone can definitely use the study of process capability for effectively assessing and evaluating the overall “ability of a process to meet specifications” (Montgomery 2020). The capability study is majorly summarized in indices, the purpose or objective of these measures or actions is to “show the system's ability to meet its requirements, respectively to determine whether the system is capable of producing products which are within the customer specifications”. Therefore, process capability (Cp) is mainly described as the overall measurement completely based on the statistical methods of a particular process's ability to primarily “produce parts within specified limits on a consistent basis” (Akhtar et al. 2018) . These capability studies majorly fit into the quality management system along with maintaining the relevant or appropriate standard of the overall process.

Capability studies mainly tell about the fact that the specific product or process meets and fulfills the specifications. Capability studies are mainly used in quality control systems or quality management systems and quality assurance. That is mainly to specifically “study the variation within a process and the primary aim or purpose is to determine how well a process meets its specification limits, by comparing the distribution of output to the desired specification limits”.It is obvious that the major significance is to distinctly describe a product and demonstrate the primary usage of capability studies to effectively boost or increase production (Teece 2018). It is also true that there are both positive and negative effects and impacts of these capability studies that mainly fit into the quality management systems and quality assurance along with the relevant or suitable standards. Therefore, it can be said that the capability studies definitely fit into the process of quality management systems and quality assurance (Pohl and Dikic 2019). The capability ratio in the quality assurance and quality management system mainly defines about the fact that the “variability of a process relative to the specification limits”. In the capability studies, the capability ratio is predominantly a “unit-less value describing the ratio of process distribution spread to specification limits spread”. The capability study is mainly based on the primary tools that are considered as one of the primary mechanisms of Six Sigma (Oakland and Oakland, 2018). It generally assists in comprehending what the actual process capability is all about and briefs about the probability that the method will produce flaws. There are majorly four leading metrics operated to illustrate the capability. These are commonly known as “Cp, Cpk, Pp, and Ppk”.

Capability studies of the existing machines

The quality management system is accessible to enhance and make the continuation to improve the overall dignity with the standard work that is liable to set and make the credential in improving the overall dignity. It is accessible to manage and set a cornerstone for improving the overall diligence and improving the efficiency and effectiveness of its performance. Quality management control is being set to improve and achieve overall dignity with standard performance. As per the view of Haq et al. (2019), it is required to manage the system and lead to achieve dignity with standard performance. The internal and external environment is liable to set and make the credentials in improving the production in terms of quality of the products the organizational requirement is being set to achieve the quality products and services that is a libel to set and make the credential and hence the dignity with the relationship between needs of customer and employee. It is important to manage and set the consequences that will help to overcome the problem and make the system more effective with the production of quality products and services.

The implementation of a quality management system is important to solve and meet the needs of customer demand, and organizational requirements. Establishing the overall density is liable to meet the credentials and meet the overall achievement with the quality management system that is applicable to access and consumption with the quality control system. It is liable to enhance dignity with the standard work that is improving the consumption of the product and service offered by the organization. Alwan et al. (2023) said that the quality management system is liable to set and make the overall standing with the leadership and event customer to meet the segmentation.

The knowledge of specific tools for assessment is liable to set and meet the improvement of the process. It is liable to meet the dignity with the philosophy for constant and continued demand the improvement in the product and increasing the value. Managing quality in an organization is liable to set and improve the overall dignity with the standard work and implementing the standard quality system. As per the view of Van Nguyen et al. (2022), it is liable to set and meet the credential with the organizational performance that is applicable to achieve the quality management system. The standard on quality improvement system is applicable to the access and making the dignity in the system that is improving the overall credential to manage and set the negotiation with the improvement in the quality.

References

Akhtar, P., Khan, Z., Tarba, S. and Jayawickrama, U., 2018. The Internet of Things, dynamic data and information processing capabilities, and operational agility.Technological Forecasting and Social Change,136, pp.307-316. https://doi.org/10.1016/j.ijmachtools.2018.01.004

Alwan, W., Ngadiman, N.H.A., Hassan, A., Saufi, S.R. and Mahmood, S., 2023. Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns.Machines,11(1), p.115. https://doi.org/10.3390/machines11010115

Atta, A., Shoraim, M., Yahya, S., Abuzaid, A. and Mahdi, E., 2020. Enhancing R Control Chart Performance in Monitoring Process Dispersion using Scaled Weighted Variance Method for Skewed Populations.

Haq, A., Abidin, Z.U. and Khoo, M.B., 2019. An enhanced EWMA-t control chart for monitoring the process mean. Communications in Statistics-Theory and Methods,48(6), pp.1333-1350. https://doi.org/10.1080/03610926.2018.1429631

Hryniewicz, O., Kaczmarek-Majer, K. and Opara, K.R., 2019. Control charts based on fuzzy costs for monitoring short autocorrelated time series.International Journal of Approximate Reasoning,114, pp.166-181. https://doi.org/10.1016/j.ijar.2019.08.013

Montgomery, D.C., 2020.Introduction to statistical quality control. John Wiley & Sons. https://books.google.co.in/books?hl=en&lr=&id=oh7zDwAAQBAJ&oi=fnd&pg=PR3&dq=capability%C2%A0studies%C2%A0fit%C2%A0into%C2%A0quality%C2%A0management%C2%A0systems%C2%A0and%C2%A0quality%C2%A0assurance&ots=DrDBb5L51z&sig=wi-xnLED2aaHrNltHLxiC8fXwwo&redir_esc=y#v=onepage&q=capability%C2%A0studies%C2%A0fit%C2%A0into%C2%A0quality%

Oakland, J. and Oakland, R.J., 2018.Statistical process control. Routledge. https://books.google.co.in/books?hl=en&lr=&id=hD73DwAAQBAJ&oi=fnd&pg=PP1&dq=capability%C2%A0studies%C2%A0fit%C2%A0into%C2%A0quality%C2%A0management%C2%A0systems%C2%A0and%C2%A0quality%C2%A0assurance&ots=H0aWvz_wFt&sig=tbRoGiLKyRoFyo0Q-VRZ9kUaJMs&redir_esc=y#v=onepage&q=capability%C2%A0studies%C2%A0fit%C2%A0into%C2%A0quality%C2%A0management%C2%A0systems%C2%A0and%C2%A0quality%C2%A0assurance&f=false

Pohl, C. and Dikic, I., 2019. Cellular quality control by the ubiquitin-proteasome system and autophagy.Science,366(6467), pp.818-822. https://doi.org/10.1126/science.aax3769

Teece, D.J., 2018. Dynamic capabilities as (workable) management systems theory.Journal of Management & Organization,24(3), pp.359-368. https://www.cambridge.org/core/journals/journal-of-management-and-organization/article/dynamic-capabilities-as-workable-management-systems-theory/0F3A795EE011931B83135B324C33393E

Van Nguyen, T.T., Heuchenne, C. and Tran, K.P., 2022. Anomaly Detection for Compositional Data using VSI MEWMA control chart.IFAC-PapersOnLine,55(10), pp.1533-1538. https://doi.org/10.1016/j.ifacol.2022.09.608

Viloria, A. and Lezama, O.B.P., 2019. Improvements for determining the number of clusters in k-means for innovation databases in SMEs.Procedia Computer Science,151, pp.1201-1206. https://doi.org/10.1016/j.procs.2019.04.172

Votto, R., Lee Ho, L. and Berssaneti, F., 2021. Earned duration management control charts: Role of control limit width definition for construction project duration monitoring.Journal of Construction Engineering and Management,147(9), p.04021108. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002135

Zaman, M. and Hassan, A., 2021. Fuzzy heuristics and decision tree for classification of statistical feature-based control chart patterns.Symmetry,13(1), p.110. https://doi.org/10.3390/sym13010110