Operations Management Standards And Statistical Process Cont

Operations Management Standards and Statistical Process Control

Operations Management-Quiz 4 Question 1 (1 point): ISO 9001:2008 standards provide strict guidelines for how products are to be produced.

Question 1 options: True / False

Question 2 (1 point): The central line on a p-chart is 0.50 with a UCL of 0.65 and an LCL of 0.35. The results of the next six samples are 0.60, 0.37, 0.45, 0.48, 0.45, and 0.42. What should you do?

Question 2 options: Nothing; the process is behaving as expected. Explore the assignable causes because three observations are above the central line. Explore assignable causes because there is a run. Increase the sample size to get a better measure.

Question 3 (1 point): The Baldrige Performance Excellence Program considers a company's business results but ISO 9001:2008 registration does not.

Question 3 options: True / False

Question 4 (1 point): The underlying statistical distribution for the p-chart is:

Question 4 options: Poisson / binomial percentage / normal

Question 5 (1 point): The ISO 9001:2008 standard:

Question 5 options: emphasizes corporate leadership as a means of determining who receives the award. has the greatest number of points awarded for business results. is awarded by the U.S. government each year. addresses quality system documentation.

Question 6 (2 points): Use the information from Table 5.3. What is the upper control limit (UCL) if the bank were to use z = 2 and a sample size of 100?

Question 6 options: less than or equal to 0.02 / greater than 0.02 but less than or equal to 0.04 / greater than 0.04 but less than or equal to 0.06 / greater than 0.06

Question 7 (2 points): A metal-cutting operation has a target value of 20 and consistently averages 19.8 with a standard deviation of 0.5. The design engineers have established an upper specification limit of 22 and a lower specification limit of 18. What is the process capability ratio?

Question 7 options: 1.66

Question 8 (2 points): Historically, the average proportion of defective bars has been 0.015. Samples will be of 100 bars each. Construct a p-chart using z = 3. Suppose a sample had 0.07 defectives. What would you do?

Question 8 options: Nothing; it is just random variation. Look for assignable causes. Change z to 2 and take another sample. Change z to 4 and continue sampling.

Question 9 (2 points): Samples of 100 checks each were taken at a bank from an encoding machine over five days. Based on the provided data, if the bank uses the average proportion defective as the central line for a control chart, what is this central line?

Question 9 options: less than or equal to 0.01 / greater than 0.01 but less than or equal to 0.02 / greater than 0.02 but less than or equal to 0.03 / greater than 0.03

Question 10 (2 points): A metal-cutting operation has a target value of 20 and averages 19.8 with a standard deviation of 0.5. The engineering team established an upper specification limit of 22 and a lower limit of 18. What is the process capability index?

Question 10 options: 1.66

Paper For Above instruction

Operations management plays a pivotal role in ensuring organizations produce quality products efficiently and effectively. Standards such as ISO 9001:2008 have been instrumental in guiding organizations towards establishing robust quality management systems. This paper discusses fundamental concepts related to ISO standards, statistical process control tools like p-charts, and process capability indices, illustrating their application in quality assurance scenarios.

Understanding ISO 9001:2008 Standards

ISO 9001:2008 is an international standard that sets out the criteria for a quality management system (QMS). Its primary focus is on meeting customer requirements, enhancing customer satisfaction, and continually improving organizational processes. Unlike strict prescriptive guidelines for product production, ISO 9001:2008 emphasizes process approach, leadership, engagement of people, and evidence-based decision-making (ISO, 2008). The standard encourages organizations to develop, implement, and constantly improve their quality management systems to achieve consistent product quality and service excellence.

While ISO 9001:2008 does not prescribe specific product manufacturing procedures, it mandates organizations to maintain documented information that evidences conformity to the standard and ensures effective operation of their QMS. This focus on documentation and continual improvement distinguishes ISO 9001 from other standards that might emphasize specific technical specifications (Dale et al., 2015).

Statistical Process Control: p-Charts

Statistical process control (SPC) tools are vital for monitoring and controlling processes to maintain quality. The p-chart is a control chart used for tracking the proportion of defective items in a process over time. Its underlying distribution is binomial, which models the presence or absence of defects in a finite number of units (Montgomery, 2012). The central line of a p-chart represents the expected proportion of defects, with upper and lower control limits (UCL and LCL) indicating the bounds of process variation attributable to common causes.

In practice, observed data points that fall beyond these limits or exhibit patterns such as runs or trends signal the presence of special causes of variation, requiring investigation. For example, a sample proportion of 0.07 defectives in a process with historical average of 0.015 indicates a shift likely caused by an assignable cause, prompting corrective actions (Wheeler et al., 2010).

Process Capability and Indexes

Process capability indices, such as Cp and Cpk, are quantitative measures of how well a process meets specified limits. The capability ratio (Cp) compares the process spread to the specification width, indicating potential capability if centered properly. The formula for Cp is:

Cp = (USL - LSL) / (6σ)

where USL and LSL are the upper and lower specification limits, and σ is the process standard deviation (Juran & Godfrey, 1999). A Cp greater than 1 signifies that the process variation is within specifications. Similarly, the process capability index (Cpk) considers the process mean's proximity to the target, providing a real-world measure of process performance (Padek et al., 2014).

Application in Manufacturing and Service Sectors

The discussed tools and standards are widely applied across manufacturing and service industries. In manufacturing, they help detect deviations such as increased defect rates or process drifts, enabling managers to undertake timely corrective and preventive actions. In service sectors, like banking and healthcare, similar concepts ensure service quality and compliance with regulatory standards, ultimately improving customer satisfaction and operational efficiency.

Conclusion

ISO 9001:2008, coupled with statistical process control tools like p-charts and process capability ratios, provides a comprehensive framework for quality assurance. These standards and methods facilitate continuous improvement, reduce variability, and ensure products meet specifications consistently. Organizations leveraging these tools can achieve operational excellence and maintain competitive advantage in their respective markets.

References

• Dale, B. G., van der Wiele, T., & van Iwaarden, J. (2015). Managing quality in services. John Wiley & Sons.
• International Organization for Standardization (ISO). (2008). ISO 9001:2008 Quality management systems — Requirements.
• Juran, J. M., & Godfrey, A. B. (1999). Juran's Quality Handbook. McGraw-Hill.
• Montgomery, D. C. (2012). Introduction to Statistical Quality Control. John Wiley & Sons.
• Padek, B., Steckel, R., & Williams, S. (2014). Process capability indices: Understanding and application. Quality Management Journal, 21(2), 17-28.
• Wheeler, D. J., & Chambers, D. S. (2010). Statistical Process Control. Wiley.
• ISO. (2008). ISO 9001:2008 Quality management systems — Requirements. International Organization for Standardization.
• Schroeder, D. V. (2000). An Introduction to Statistical Process Control. American Society for Quality.
• Evans, J. R., & Lindsay, W. M. (2014). Managing for Quality and Performance Excellence. Cengage Learning.
• Chary, S. N. (2011). Production and Operations Management. McGraw-Hill Education.