IE 301 Industrial Engineering laboratory LAB No.5: The seven QC tools and Acceptance sampling Instructor: Assisant.Prof. Parichat Chuenwatanakul Lab

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1 IE 301 Industrial Engineering laboratory LAB No.5: The seven QC tools and Acceptance sampling Instructor: Assisant.Prof. Parichat Chuenwatanakul Lab objectives: To practice using the seven QC tools to discover problems, organize information, analyze cause, improve and establish control. The seven QC tools are : 1) Check sheets A check sheet is a paper form on which items to be checked have been printed already so that data can be collected easily and concisely. 2) Graphs A graph is a picture that represents data in an organized manner 3) Pareto diagrams Pareto diagrams are a type of bar chart in which the horizontal axis represents categories of interest, rather than a continuous scale. 4) Cause and effect diagrams A cause-and-effect, or fishbone, diagram depicts potential causes of a problem. The problem (effect) displays on the right side and the list of causes on the left side in a treelike structure 5) Histograms Bars represent the number of observations falling within consecutive intervals or bins. Use a histogram to evaluate the shape and central tendency of your data, and to assess whether or not your data follow a specific distribution such as the normal distribution. 6) Scatter diagrams Scatter diagrams is graph. Use to illustrate the relationship between two variables by plotting one against the other. 7) Control charts Use control charts to track process statistics over time and to detect the presence of special causes. 1

2 Check sheets Product: Date : Manufacturing stage : final inspection Section : Type of defect : Missing Screws, Missing Clips, Defective Housing, Leaky Gasket, Scrap, Unconnected Wire, Inspector s name : Lot no. : Missing Studs, Incomplete Part Total no. inspected : Order no. : Type of defect Tally Total Missing Screws //// //// //// //// //// //// 274 Missing Clips //// //// //// //// //// 59 Defective Housing //// //// //// //// 19 Leaky Gasket //// //// //// //// /// 43 Scrap //// 4 Unconnected Wire //// /// 8 Missing Studs //// / 6 Incomplete Part //// //// 10 Pareto diagrams Suppose you work for a company that manufactures motorcycles. You hope to reduce quality costs arising from defective speedometers. During inspection, a certain number of speedometers are rejected, and the types of defects recorded. You enter the name of the defect into a worksheet column called Defects, and the corresponding counts into a column called Counts. You know that you can save the most money by focusing on the defects responsible for most of the rejections. A Pareto chart will help you identify which defects are causing most of your problems. 1 Open the worksheet EXH_QC.MTW. 2 Choose Stat > Quality Tools > Pareto Chart. 3 Choose Chart defects table. In Labels in, enter Defects. In Frequencies in, enter Counts. 4 Click OK. Interpreting the results Focus on improving the number of missing screws because over half of your speedometers are rejected due to this defect. 2

3 Control charts You work at an automobile engine assembly plant. One of the parts, a camshaft, must be 600 mm +2 mm long to meet engineering specifications. There has been a chronic problem with camshaft length being out of specification, which causes poor-fitting assemblies, resulting in high scrap and rework rates. Your supervisor wants to run X and R charts to monitor this characteristic, so for a month, you collect a total of 100 observations (20 samples of 5 camshafts each) from all the camshafts used at the plant, and 100 observations from each of your suppliers. First you will look at camshafts produced by Supplier 2. 1 Open the worksheet CAMSHAFT.MTW. 2 Choose Stat > Control Charts > Variables Charts for Subgroups > Xbar-R. 3 Choose All observations for a chart are in one column, then enter Supp2. 4 In Subgroup sizes, enter 5. Click OK. Session window output Test Results for Xbar Chart of Supp2 TEST 1. One point more than 3.00 standard deviations from center line. Test Failed at points: 2, 14 * WARNING * If graph is updated with new data, the results above may no * longer be correct. Graph window output Xbar-R Chart of Supp2 Sample Mean UC L= _ X= LC L= Sample UC L=8.225 Sample Range _ R= LC L= Sample Interpreting the results The center line on the X chart is at , implying that your process is falling within the specification limits, but two of the points fall outside the control limits, implying an unstable process. The center line on the R chart, 3.890, is also quite large considering the maximum allowable variation is +2 mm. There may be excess variability in your process. 3

4 Acceptance sampling A Step-by-step procedure for using MIL STD 105E is as follows: 1. Choose the AQL. 2. Choose the inspection level. 3. Determine the lot size. 4. Find the appropriate sample size code letter from Table Determine the appropriate type of sampling plan to use (single, double, multiple). 6. Enter the appropriate table to find the type of plan to be used 7. Determine the corresponding normal and reduced inspection plans to be used when required The OC curve The probability of acceptance is simply the probability that d is less than or equal to c, or c P a = P{d c} = n! d! (n d)! pd (1 p) n d d=0 For example, A supplier ships a component in lot of size N = 1,000. The AQL has been established for this product at 1.5%. Find the normal single-sampling plans for this situation from MIL STD 105E, assuming that general inspection level II is appropriate. 1. The sample size code letter is J (Table 14.4) 2. The single sampling plan (Table 14.5) n = 80, c = 2 If the lot fraction defective is p= 0.01, n = 80 and c = 2, then 2 P a = P{d 2} = 80! d! (80 d)! (.01)d (1.01) 80 d d=0 =

5 Table 1 Probability of acceptance for the single-sampling plans n = 80, c = 2 Fraction defective, p Probability of acceptance, Pa Figure 1 OC Curve of the single-sampling plans n = 80, c = 2 5

6 Lab Exercise no.1 Suppose you work for a company that manufactures Auto parts. You want to reduce quality costs arising from defective parts. 1) Divide into group of 6 students. 2) Design a check sheet for collecting and recording data. The company classify defect in to 6 type which are crack, scratch, strain, stain, gap, pinhole and other. 3) Classify defect type form 200 defective parts and record the data. 4) Construct Pareto diagram to help you to identify which defects are causing most of your problems. Check sheets 6

7 Pareto diagrams Interpreting the results 7

8 Lab Exercise no.2 1. Use the following data IE.301 lab 7 QC tool.mtw 2. Perform Xbar-R chart. Finding the control limits and interpret the results X chart UCL = UCL = CL = CL = LCL= LCL= R - chart 8

9 Lab Exercise no.3 A supplier ships a component in lot of size N = 3,000. The AQL has been established for this product at 1%. Find the normal, tightened and reduced single-sampling plans for this situation from MIL STD 105E, assuming that general inspection level II is appropriate. 1. The AQL = The inspection level is 3. The lot size is. 4. The sample size code letter is 5. The single sampling plan Sample size Acceptance no. Rejection no. Normal Tightened Reduced 6. Draw the type-b OC Curve for the normal single sampling plan above. Fraction defective, p Probability of acceptance, Pa 9

10 OC Curve of the single-sampling plans 10