OM2. CHAPTER 16. QUALITY CONTROL AND SPC. DAVID A. COLLIER AND JAMES R. EVANS. Chapter 16 Learning Outcomes. l e a r n i n g o u t c o m e s. LO1 Describe quality control system and key issues in manufacturing and service. - PowerPoint PPT Presentation
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arriott has become infamous for its obsessively detailed standard operating procedures (SOPs), which result in hotels that travelers either love for their consistent good quality or hate for their bland uniformity. “This is a company that has more controls, more systems, and more procedural manuals than anyone—except the government,” says one industry veteran. “And they actually comply with them.” Housekeepers work with a 114-point checklist. One SOP: Server knocks three times. After knocking, the associate should immediately identify themselves in a clear voice, saying, “Room Service!” The guest’s name is never mentioned outside the door. Although people love to make fun of such procedures, they are a serious part of Marriott’s business, and SOPs are designed to protect the brand. Recently, Marriott has removed some of the rigid guidelines for owners of hotels it manages, empowering them to make some of their own decisions on details.
Chapter 16 Quality Control and SPC
What do you think? What opportunities for improved quality control or use of SOPs can you think of at your college or university (e.g., bookstore, cafeteria)?
The task of quality control is to ensure that a good or service conforms to specifications and meets customer requirements by monitoring and measuring processes and making any necessary adjustments to maintain a specified level of performance.
1:10:100 Rule: If a defect or service error is identified and corrected in the design stage, it might cost $1 to fix. If it is first detected during the production process, it might cost $10 to fix. However, if the defect is not discovered until it reaches the customer, it might cost $100 to correct.
Quality at the source means the people responsible for the work control the quality of their processes by identifying and correcting any defects or errors when they first are recognized or occur.
Quality Control for Medical Prescriptions Poor doctor handwriting is the number one root cause of
medication errors. Often the wrong drug is prescribed, or the wrong dosage is used, or drug interactions cause adverse reactions. Mr. J. Lyle Bootman, the dean of the College of Pharmacy at the University of Arizona noted that “The economic consequences of medication errors are as costly as the entire cost of diabetes, and close to cancer and heart disease. It is a silent disease in America.” The Institute of Medicine estimates that a U.S. hospital patient is subject to at least one medication error daily. They estimate that more than 7,000 people die from medication errors every year. The solution is to streamline related processes, build quality control checks into every stage of each process, and use electronic prescription systems to eliminate handwritten prescriptions.
Statistical process control (SPC) is a methodology for monitoring quality of manufacturing and service delivery processes to help identify and eliminate unwanted causes of variation.
Constructing Control ChartsSteps 1 through 4 focus on setting up an initial chart; in step 5, the charts are used for ongoing monitoring; and finally, in step 6, the data are used for process capability analysis.
1. Preparationa. Choose the metric to be monitored.b. Determine the basis, size, and
frequency of sampling.c. Set up the control chart.
• A continuous metric is one that is calculated from data that are measured as the degree of conformance to a specification on a continuous scale of measurement.
• A discrete metric is one that is calculated from data that are counted.
• SPC uses control charts, run charts to which two horizontal lines, called control limits, are added: the upper control limit (UCL) and lower control limit (LCL).
• Control limits are chosen statistically to provide a high probability (generally greater than 0.99) that points will fall between these limits if the process is in control.
• As a problem-solving tool, control charts allow employees to identify quality problems as they occur. Of course, control charts alone cannot determine the source of the problem.
Interpreting Patterns in Control ChartsA more in-depth understanding of SPC charts includes evaluating the patterns in the sample data using guidelines, such as:• 8 points in a row above or below the center line • 10 of 11 consecutive points above or below the
center line • 12 of 14 consecutive points above or below the
center line • 2 of 3 consecutive points in the outer one-third
region between the center line and one of the control limits
• 4 of 5 consecutive points in the outer two-thirds region between the center line and one of the control limits
• Sample size: small sample size keeps costs lower; however, large sample sizes provide greater degrees of statistical accuracy in estimating the true state of control.
• Sampling frequency: samples should be close enough to provide an opportunity to detect changes in process characteristics as soon as possible and reduce the chances of producing a large amount of nonconforming output.
IBMAt one IBM branch, pre-employment physical examinations took too long and taxed the medical staff assigned to conduct them. Such examinations are vital for assuring that employees can perform certain jobs without excess stress and that they pose no health threat to other employees. Therefore, the challenge IBM faced was to maintain the quality of the exam while reducing the time needed to perform it by identifying and eliminating waiting periods between the various parts of it. Preliminary control charts revealed that the average time required for the examination was 74 minutes, but the range varied greatly. New equipment and additional training of the medical staff were suggested as means of shortening the average time. Initial charts indicated that the process was out of control, but continued monitoring and process improvements lowered the average time to 40 minutes, and both the average and range were brought into statistical control with the help of x and R-charts.
• Cp > 1, indicates good capability as in Exhibit 16.8(c); in fact, many firms require Cp values of 1.66 or greater from their suppliers, which equates to a tolerance range of about 10 standard deviations.
• The value of Cp does not depend on the mean of the process; thus, a process may be off-center, such as in Exhibit 16.8(d), and still show an acceptable value of Cp.
One-sided capability indices that consider off- centered processes
Cpu = (UTL – µ)/3σ [16.10]
Cpl = (µ – LTL)/3σ [16.11]
Cpk = min (Cpl, Cpu) [16.12]
whereUTL = upper tolerance limitLTL = lower tolerance limit µ = the mean performance of the process σ = standard deviation of the process (or an estimate based on the sample standard deviation, s)
Solved ProblemA controlled process shows an overall mean of 2.50 and an average range of 0.42. Samples of size 4 were used to construct the control charts.
Part A: What is the process capability? From Appendix B, d2 = 2.059, σ = R/d2 = 0.42/2.059 = 0.20. Thus, the process capability is 2.50 3(.020), or 1.90 to 3.10.
Part B: If specifications are 2.60 ± 0.25, how well can this process meet them? Because the specification range is 2.35 to 2.85 with a target of 2.60, we may conclude that the observed natural variation exceeds the specifications by a large amount. In addition, the process is off-center (see Exhibit 16.9).