Integrated Quality Session 4 Professor Janaina Gasparelo Henry Ford College January , 2015

1. Integrated Quality Session 4Professor Janaina Gasparelo Henry Ford College January, 2015 US Department of LaborMulti-State Advanced Manufacturing Consortium

2. AGENDA • Current Events • Quick review on 7 Basic Quality Control Tools • Basic Statistics & Normal Theory • Overview (APQP, PPAP, FMEA, SPC, Gage R&R, MSA) • 8D Problem Solving • Define Corrective Action, Preventive Action, Containment Action and Layered Process Audits • Discuss Continuous Process Improvements

3. BASIC QUALITY CONTROL TOOLS • Cause-and-effect diagram (also called Ishikawa or fishbone chart): Identifies many possible causes for an effect or problem and sorts ideas into useful categories. • Check sheet: A structured, prepared form for collecting and analyzing data; a generic tool that can be adapted for a wide variety of purposes. • Control charts: Graphs used to study how a process changes over time. • Histogram: The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs.

4. BASIC QUALITY CONTROL TOOLS • Pareto chart: Shows on a bar graph which factors are more significant. • Scatter diagram: Graphs pairs of numerical data, one variable on each axis, to look for a relationship. • Stratification: A technique that separates data gathered from a variety of sources so that patterns can be seen (some lists replace “stratification” with “flowchart” or “run chart”). Excerpted from Nancy R. Tague’s The Quality Toolbox, Second Edition, ASQ Quality Press, 2005, page 15.

5. BASIC STATISTICS • Ways of Describing Data

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11. BASIC STATISTICS • Give me some real world examples of using mean and median • Are there times when this information could be misleading? • How do you solve that?

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16. BASIC STATISTICS The Normal Distribution • The Normal Distribution is a distribution of data which has certain reliable properties • To understand the characteristics of the underlying process from which the data were obtained it is important to use the properties • It is possible to represent many natural phenomena and man-made processes and normally distributed. Some are naturally distributed. • Don’t be worried if your data is not normal.

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26. NORMAL THEORY • Is Something Fishy? • You manage the shipping department for a manufacturer of medical devices. You get a charge for $642 for expedited parts that you think usually comes in closer to $500. You obtain 250 recent charges for that same item to make comparisons. You want to know if there is something fishy about this charge or if it is within the usual range for that item. • How can you use the data to answer the question?

27. NORMAL THEORY • Is Something Fishy? • Option 1: Create a control chart of the data • Use a control chart of charges to see if the fishy charge is outside the limits • Option 2: Apply Normal theory • Use Normal theory, a body of statistics built around the properties of the Normal distribution • See where the fishy value falls in the distribution of this data

28. NORMAL THEORY • Definition • A probability distribution where the most frequently occurring value is in the middle and other probabilities tail off symmetrically in both directions. This shape is sometimes called a bell-shaped curve.

29. NORMAL THEORY • 1. Make a histogram to see if (continuous) data are Normal. • 2. Get the mean and standard deviation of data. 50 Looks roughly Normal 40 30 Frequency 20 10 0 350 450 550 650 Express Delivery Charges ($) A standard deviation is the typical amount an observation varies fromthe mean

30. 600 400 500 Express Delivery Charges ($) NORMAL THEORY • 3. Draw Normal curve for data. • 4. Compare the value-of-interest ($642) to the Normal curve. 450 550 350 650 $642

31. The “standard” Normal or Z-value NORMAL THEORY • 5. How many standard deviations away from the mean is the value-of-interest?

32. Area = probability NORMAL THEORY • 6. Look up the probability of a charge being that value or higher in the Normal table of Z-values. • 7. If probability is low . . . then something’s probably fishy. “Low” usually means < .05

33. X + X S - X S - X 2S + X 2S - Normal + X 3S X 3S data; -3 -2 -1 0 1 2 3 “any” scale Fill in the blanks for data with -3 -2 -1 0 1 2 3 = 500 X s = 50 NORMAL THEORY

34. X = value-of-interest Standard Normal (or Z-values) x=0 s=1 2 0 1 3 -2 -3 -1 NORMAL THEORY

35. mean = 0 st. dev. = 1 -3 -2 -1 0 1 2 3 Z-value anywhere on this scale NORMAL THEORY A “Standard” Normal Distribution • Z-value • How many standard deviations the value-of-interest is away from the mean

36. Area = .5 Probability = .5 or 50% -3 -2 -1 0 1 2 3 Area = ? -3 -2 -1 0 1 2 3 Value-of-interest NORMAL THEORY • Area under the standard Normal curve = probability • What is the probability a Z-value will be  zero? • What is the probabilitya Z-value will be 2.84? • Probabilities of Z-values Area = 1 -3 -2 -1 0 1 2 3

37. 8D PROBLEM SOLVING • Eight Disciplines (8Ds) Problem Solving is a method developed at Ford Motor Company used to approach and to resolve problems, typically employed by engineers or other professionals. Its purpose is to identify, correct, and eliminate recurring problems, and it is focused on product and process improvement. It establishes a permanent corrective action based on statistical analysis of the problem and on the origin of the problem by determining the root causes.

38. 8D PROBLEM SOLVING • Although it originally comprised eight stages, or 'disciplines', it was later augmented by an initial planning stage. 8D follows the logic of the PDCA cycle. • PDCA (plan–do–check–act or plan–do–check–adjust) is an iterative four-step management method used in business for the control and continuous improvement of processes and products. It is also known as the Deming circle/cycle/wheel, Shewhart cycle, control circle/cycle, or plan–do–study–act (PDSA).

39. 8D PROBLEM SOLVING The disciplines are: • D0: Plan: Plan for solving the problem and determine the prerequisites.D1: Use a Team: Establish a team of people with product/process knowledge. • D2: Describe the Problem: Specify the problem by identifying in quantifiable terms the who, what, where, when, why, how, and how many (5W2H) for the problem.

40. 8D PROBLEM SOLVING • D3: Develop Interim Containment Plan: Define and implement containment actions to isolate the problem from any customer.

41. 8D PROBLEM SOLVING • D4: Determine, and Verify Root Causes and Escape Points: Identify all applicable causes that could explain why the problem has occurred. Also identify why the problem was not noticed at the time it occurred. All causes shall be verified or proved. One can use five whys or Ishikawa diagrams to map causes against the effect or problem identified.

42. 8D PROBLEM SOLVING • D5: Verify Permanent Corrections (PCs) for Problem will resolve problem for the customer: Using pre-production programs, quantitatively confirm that the selected correction will resolve the problem. (Verify that the correction will actually solve the problem.)

43. 8D PROBLEM SOLVING • D6: Define and Implement and Corrective Actions: Define and Implement the best corrective actions. • D7: Prevent Recurrence: Modify the management systems, operation systems, practices, and procedures to prevent recurrence of this and all similar problems. • D8: Congratulate Your Team: Recognize the collective efforts of the team. The team needs to be formally thanked by the organization.