MEL420: Total Quality Management

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A grinding and deburring operation is monitored using a mean and a range ..... The postmaster of a small city receives a certain number of complaints each day ...
MEL420: Total Quality Management

Lab Book

This is a compiled list of exercises done in a typical course like TQM.

Part A: A. Construction of Control chart for defectives B. Construction of Control chart for defects C. Problems on Xbar and R chart D. Problems on P Chart E. Problems on C chart F. Problems in Acceptance sampling G. Problems on Quality Costing

Construction of Control Chart for Defectives OBJECTIVE : To demonstrate the ‘p’ control chart and the calculation of control limits. BASIS : Students select random samples generated through calculator and present data. EQUIPMENT: Scientific Calculator METHOD: A student generates a random number (between 0 and 1 from the calculator. If the random number is less than 0.100, the outcome is noted as ‘defective’. This process is repeated 15 times. This represents a sample. Repeat the process to represent 20 samples. Tabulate your readings in a systematic way. S No

RN1

RN2

RN3

RN4

RN5

RN6

RN7

RN8

RN9

RN10

RN11

RN12

RN13

RN14

1 2 .. 20 Compute the mean fraction defectives.

Here : pbar = mean fraction defectives, n= sample size=100. Examples on p-chart 1. The CB(Circuit Boards) s are supplied to Acme Ltd (AL), a leading manufacturer of power equipment and one of the prime customers of EL. The quality control department of AL selects a batch of 50 item everyday and measures the number of defectives. The following data shows the number of defective CBs seen in the month of Jun 2005 (data to be read row wise!). 4,

4, 2, 5, 0,

0, 3, 3, 1

1, 5 1, 0.

2,

1,

0,

0,

0,

1,

1,

0,

0,

0,

1,

0,

0,

0,

2,

0,

Comment on the process manufacturing this item. If three items are taken randomly, what is the probability that exactly two items are defectives? 2. Using sample of 200 observations each, a quality inspector found the following: Sample 1 2 3 4 Number of defectives 4 2 5 9 Is the process in control? 3. During long runs of canned vegetables through a labeling machine, a few labels invariably fail to adhere properly and eventually fall off. Using the following sample data, which are based on samples of 100 observations each. Determine if the process is in control. Sample Defectives 1 2 3 4 5 6 7 8

No. of Defectives 5 3 6 7 4 6 8 4

Fraction Defectiv es

Pbar

Establish the control limits and plot the control chart. UCL(LCL) = pbar + (-) 3 Sqrt (pbar(1-pbar)/n)

0,

RN15

Sample 9 10 11 12 13 14 15 16

No.

of 5 8 3 4 5 6 6 7

4. The Western Jeans Company produces denim jeans. The company wants to establish a control chat to monitor the production process and maintain high quality. The company has

taken 20 samples each containing 100 pairs of jeans, and inspected them the results of which are as follows. Comment on the process. Sample 1 2 3 4 5 6 7 8 9 10

Number of Defectives 6 2 4 10 6 4 12 10 8 10

Sample 11 12 13 14 15 16 17 18 19 20

Number of Defectives 12 10 14 8 6 16 12 14 18 16

Construction of Control Chart for Defects OBJECTIVE : To demonstrate the ‘c’ control chart and the calculation of control limits. BASIS : Students select random samples generated through calculator and present data. EQUIPMENT: Scientific Calculator METHOD : A student generates a random number (between 0 and 1) from the calculator. Map this number into defects as follows: If the random number is less than 0.67 , the outcome is noted as ‘ 0 defects’. If the random number is between 0.671 & 0.93, the outcome is noted as ‘ 1 defects’ If the random number is between 0.931 & 0.98, the outcome is noted as ‘ 2 defects’ If the random number is between 0.981 & 0.99, the outcome is noted as ‘ 3 defects’ If the random number is between 0.991 & 1, the outcome is noted as ‘ 4 defects’

This process is repeated 50 times to represent 50 samples. Tabulate your readings in a systematic way. S No

Random Number

No of Defects

1 2 .. 50 Mean Cbar Compute the mean fraction defects(cbar). Also compute the standard deviation. Comment on this. Establish the control limits and plot the control chart. UCL(LCL) = cbar + (-) 3 Sqrt (cbar) Here : cbar = mean number of defects Examples on c-chart 1. A c-chart is used to monitor the number of surface of imperfections on sheet of photographic film .The chart is presently set up based on c = 2.6.Find 3-sigma control limits for this process. 2. A manufacturer produces metal panels that are painted with a liquid and then baked. The finish some times contains the defects, which can be caused by a number of conditions; including the surface of the metal panel, paint viscosity etc. The firm periodically inspects the panels. The defects themselves are independent of one another and are known to be Poisson distributed. For a particular kind of panel the numbers of defects contained in 25 sampled panels were found to be as follows. 7293247682754636172453192 Construct control limits and comment on the process. 3. The Mankato Transit System (MTS) uses the number of written passenger complaints per day as a measure of its service quality. For 20 days, the number of complaints received was as follows:

------------------------------------------------------------------------------------------------------------------------Day (sample) No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Total ------------------------------------------------------------------------------------------------------------------------No. of Complaints 6 5 6 5 4 5 3 4 3 0 2 1 2 2 1 1 0 1 0 0 51 ------------------------------------------------------------------------------------------------------------------------Is MTS providing a quality service for its customers? Explain.

4. The following tabulation gives defects c observed in an aircraft sub assembly operation observer in various shifts for a week. Comment on the process. Shift/Day

Mon

Tue

Wed

Thu

Fri

Sat

Shift 1

19

25

15

19

16

17

Shift 2

20

20

14

9

12

14

Shift 3

18

17

12

14

16

19

Procedure

Problems on xbar and R chart Data for Xbar and R control

n 3 4 5 6 7 8 9 10

A2 1.023 0.730 0.577 0.483 0.419 0.373 0.337 0.308

D3 0 0 0 0 0.076 0.136 0.184 0.223

D4 2,575 2.28 2.114 2.004 1.924 1.864 1.816 1.777

1. The results of an analysis yield x = 360,  = 40. Assume that generates a normal distribution specifications are 400  60. (a) What proportion of the meets specifications? (b) If the process is re-centered what proportion would meet the specifications? (c) To what extend should process dispersion be reduced if it is least 99% of products meet specifications?

chart the the and

following: process the product at 400,

required that at

2. A manufacturer of electrical products purchases many parts from outside vendors. A lot of 20000 of a certain small component are received from a new vendor. The receiving inspection department for the manufacturer has taken a random sample of 200 components from this lot and measured the resistance of each component. These resistances in ohms have been arranged into the following frequency distribution. Cell boundaries( ohms) Frequency 88.5-86.5 2 86.5-84.5 5 84.5-82.5 16 82.5-80.5 24 80.5-78.5 40 78.5-76.5 44 76.5-74.5 25 74.5-72.5 22 72.5-70.5 13 70.5-68.5 7 68.5-66.5 2 a) Compute the average and standard deviation of this frequency distribution. What percentage of a normal distribution having your computed average and standard deviation would fall outside the specification limits 75  10 ohms?

b) If you make an assumption that the resistances are distributed uniformly through out each sell, what percentage of actual distribution fell outside these limits? c) What would be the percentage reduction in defectives if the process is recentered at mid point of the specifications as given in a) ? 3

A continuous process cuts plastic tubing into nominal lengths of 80 centimeters. Samples of five observations each have been taken, and the results are as listed. Determine upper and lower control limits for mean and range charts, and decide if the process is in control.

Sample 1 79.2 78.8 80.0 78.4 81.0

2 80.5 78.7 81.0 80.4 80.1

3 79.8 79.4 80.4 80.3 80.8

4 78.9 79.4 79.7 79.4 80.6

5 80.5 79.6 80.4 80.8 78.8

6 79.7 80.6 80.5 80.0 81.1

4 . A control chart for x & R are maintained on a certain dimension of a manufactured part, measured in inches. The subgroup size is 4. The values of x & R are computed for each subgroup. After 20 subgroups, sum x = 41.340, and  R= .320. Compute the values of 3  limits for x & R charts, and estimate the value of process dispersion  ’on the assumption that process is in statistical control. The dimension is specified as 2.050  .020. If the dimension falls above UCL , rework is required; if bellow LCL, the part must be scraped. a) If the process is in statistical control and normally distributed, what can you conclude regarding its ability to meet the specifications? Can you make any suggestion for improvement? b) What should be the aimed at value of the process centering and control limits for future use if(cost of scrapping) Cs = 4.3*Cr(cost of rework) .Also find % reduction in the cost of defectives. 5.

A grinding and deburring operation is monitored using a mean and a range chart. Six samples of n = 20 observations have been obtained and the sample means and ranges computed. Sample Mean Range 1 3.06 0.42 2 3.15 0.50 3 3.11 0.41 4 3.13 0.46 5 6

3.06 3.09

0.46 0.45

Determine upper and lower control for the mean and range charts. Is the process in control?

6. A certain product has been statistically controlled at a process average of 36.0 and a standard deviation of 1.00. The product is presently being sold to two users who have different specification requirements. User A established specifications of 38.0  4.0 for the product, and user B has specifications of 36.0  4.0. (a) Based on the present process setup, what % of products produced will not meet the specifications set up by user A? (b) What % of the products will not meet the specifications of user B? (c) Assuming that the two users’ needs are equal, a suggestion is made to shift the process target to 37.0. At this suggested value, what percent of the product will not meet the specifications of the user A? (d) At the suggested value, what percent of the product will not meet the specifications of the user B? (e) Do you think that this shift to a process target of 37.0 would be desirable? Explain your answer. 7.

Electra Ltd (EL) has a manufacturing process that produces circuit breaker (CB), which is a prime product of the company. EL is beginning to experience huge increases in sales from housing and office building contractors both in the domestic as well as international markets. The parameter of interest is the width (2.0 in) of the circuit breakers. Too wide a circuit breaker will result in the breaker not fitting in the fuse box, similarly too narrow width will cause play once the breaker has been installed. It is imperative that the process producing CB is stable. The QC group of EL has collected the data about the width of CB as shown below for a 5-days week. Everyday the samples were collected twice (in day shift (AM), and in evening shift (PM)). Sample No

Monday

Tuesday

Wednesday

Thursday

AM PM AM PM AM PM AM PM 1 2.0 2.0 2.0 2.1 2.0 2.1 1.9 1.9 2 2.0 2.1 2.1 1.9 1.9 1.9 2.0 1.9 3 2.1 2.1 2.1 3.2 2.0 2.1 2.0 2.1 4 1.9 1.9 2.0 3.7 2.0 2.0 2.0 2.0 5 2.0 2.0 2.1 3.6 2.1 2.0 1.0 1.9 Analyze the above data in as much detail as possible and advise EL accordingly. 8.

Friday AM 2.0 2.0 2.1 2.0 1.9

Following are the readings of 10 (ten) samples (each of size 5) taken from a process regarding the dimension of a shaft, for which the specifications are 45 mm  1.5 mm. 48.3 47.2 49.2 48.5 46.3

45.8 47.9 46.5 43.4 45.5

46.3 50.1 48.1 51.2 50.2

47.3 44.5 45.2 46.2 47.6

48.3 47.4 45.2 46.2 45.4

41.2

47.6

42.2

45.2

44.3

PM 2.0 2.0 2.0 2.0 2.1

40.6 49.2 48.2 46.3 45.3 43.3 45.2 46.2 44.2 44.2 46.5 44.2 44.2 46.3 44.2 44.2 41.3 42.6 44.8 43.7 Is the process under control? Plot the Xbar and R chart. Comment on the plot. What is the process capability Index here? How will you improve the process capability? 9.

During the trial period for HiLife battery 25 samples were taken, each with a sample size of 4. For this, Σ Xbar = 130.25 volts, Σ R= 7.25 volts. Based on this data, the control limits were established. During the next week, the first three samples (each with sample size of 4) yielded sample means as 5.01, 5.51, and 5.35 volts. Is the process under control?

10.

Following table gives voltage data for a battery (Customer specification for which is 9 + 0.5 Volts) based on 15 samples each of size three. Analyze in as much detail as possible and give your specific comments.

1 2 3

1

2

3

4

5

6

Sample Number 7 8 9

10

11

12

13

14

15

8.75 8.95 8.93

8.79 9.03 9.00

9.30 8.91 9.01

8.84 9.02 8.94

8.91 8.98 9.05

8.76 9.00 8.89

8.99 8.85 8.97

8.93 8.88 9.01

9.03 8.86 9.10

8.95 9.00 8.92

8.83 9.07 9.02

9.00 8.78 9.11

9.06 8.94 8.88

9.01 9.22 8.95

8.96 8.84 8.93

Problems on p and np charts 1. An electronics company manufactures several types of cathode ray tubes on a mass production basis. During the past month tube type A has caused considerable difficulty. The following table contains data from 21 days of this troublesome period. Compute the central line and 3 sigma control limits for a p chart for this tube process. 100 units are inspected each day. 1 0.22 2 0.33 3 0.24 4 0.20 5 0.18 6 0.24 7 0.24 8 0.29 9 0.18 10 0.27 11 0.31 12 0.46 13 0.31 14 0.24 15 0.22 16 0.22 17 0.29 18 0.31 19 0.21 20 0.26

21

0.24 The CBs are supplied to Acme Ltd (AL), a leading manufacturer of power

2

equipment and one of the prime customers of EL.

The quality control

department of AL selects a batch of 50 item everyday and measures the number of defectives. The following data shows the number of defective CBs seen in the month of Jun 2002 (data to be read row wise!). 0,

4,

0,

1,

2,

1,

0,

0,

0,

1,

1,

0,

2,

3,

5,

4,

5,

3,

1,

0,

0,

1,

0,

0,

0,

2,

0,

0,

1

0.

Comment on the process manufacturing this item. If three items are taken randomly, what is the probability that exactly two items are defectives?

3.

Using sample of 200 observations each, a quality inspector found the following: Sample 1 2 3 4 Number of defectives 4 2 5 9 a. Determine the fraction defective in each sample. b. If the true fraction defective for this process is unknown, what is your estimate of it? c. What is your estimate of the mean and standard deviation of the sampling distribution of fraction defective for samples of this size? d. Using control limits of 0.047 and 0.003, is the process in control? e. Suppose that the long-term fraction defective of the process is known to be 2 percent. What are the values of the mean and standard deviation of the sampling distribution? f. Construct a control chart for the process, assuming a fraction defective of 2 percent, using two-sigma control limits. Is the process in control?

4.

During long runs of canned vegetables through a labeling machine, a few labels invariably fail to adhere properly and eventually fall off. Using the following sample data, which are based on samples of 100 observations each, construct a control chart for the fraction defective using 95 percent control limits, and determine if the process is in control. Sample 1 2 3 4 5 6 7 8

5.

No. of Defectives 5 3 6 7 4 6 8 4

Sample 9 10 11 12 13 14 15 16

No. of Defectives 5 8 3 4 5 6 6 7

The Western Jeans Company produces denim jeans. The company wants to establish a control chat to monitor the production process and maintain high

quality. The company has taken 20 samples (one per day for 20 days), each containing 100 pairs of jeans, and inspected them for defects, the results of which are as follows. Sample 1 2 3 4 5 6 7 8 9 10

Number of Defectives 6 2 4 10 6 4 12 10 8 10

Sample 11 12 13 14 15 16 17 18 19 20

Number of Defectives 12 10 14 8 6 16 12 14 18 16

Which control chart is most appropriate for this problem? Why? Is the production process in control? Explain by showing all your work including a control chart with 95% control limit.

6.

An item is made in lots of 200 each. The lots are given 100% inspection. The record sheet for the first 25 lots inspected showed that a total of 75 items did not conform to specifications. (a) Determine the trial control limits for the np chart. (b) Assume that all points fall within the control limits. What is your estimate process average fraction nonconforming p. (c) If this p remains unchanged, what is the probability that the 26th lot will contain exactly 7 nonconforming units

7. Receiving inspection is performed on a certain high volume part using a p chart based on a standard value (p0) of 0.02, 3 sigma limits and a standard sample size of 80. (a) Compute control limits for the chart. (b) A group of lots is received from a process that was generating 4% nonconforming products. What is the probability that this higher value of p will not be detected within the first five lots inspected? 8.. A large number of samples of 300 items each are taken from a process that has a percentage nonconforming of 10% (a) What is the expected average number of nonconforming units per sample? (b) Find the 3 sigma control limits for an np chart to control this process. (c) What is the upper limit of the number of nonconformities items in a sample that in the long run, you would expect to find exceeded only 5% of the time? Use a Poisson approximation. 9

In the manufacture of certain special duty transformers units are required to meet a number of specifications related to temperature rise, output voltages, and current ripple etc. Approximately 200 units are produced and subjected to a final inspection daily. At the end of 20 working days, 190 units have been rejected out of 4150 units produced and inspected. (a) Determine 3 sigma trial control limits for a p chart based on the estimated average daily production of 200 units. (b) Only one point on the control chart falls outside the limits. On that day, 30 non-conforming units were found in 200 units inspected. Investigations uncovered the fact that a voltage pot setting was being incorrectly adjusted. What aimed-at values of fraction defective and control limits would you

recommend for the following period based on an average daily production of 200 units? 10. The new item startup procedure of a certain electronics plant calls for 100% inspection for at least the 1st 4 months or until process control is established at an economically acceptable level of nonconforming products. A total of 960 units were found to not meet specification during the 1st 20 days. The number of units produced during this time period was 31985. Determine the central line and trial control limits for p chart based on the average no. of units produced per day. 11. A manufacturer purchases small bolts in cartons that usually contain several thousand bolts. Each shipment consists of a number of cartons. As part of the acceptance procedure for these bolts, 400 bolts are selected at random from each carton and are subjected to visual inspection for certain defects. In a shipment of 10 cartons, the respective percentages of defectives in the samples from each carton are 0, 0, 0.5, 0.75, 0, 2, 0.25, 0, 0.25 and 1.25. Does this shipment of bolts appear to exhibit statistical control with respect to the quality characteristic explained in this inspection?

Problems on c-Chart 1. A c-chart is used to monitor the number of surface of imperfections on sheet of photographic film .The chart is presently set up based on c = 2.6 (a) Find 3-sigma control limits for this process. (b) Determine the probability that a point will fall outside these control limits while the process is actually operating at µc of 2.6 2. c-chart is used to monitor surface imperfections on porcelain enameled water heater cabinets. Each cabinet is checked for non-conformities of a certain classification and the count entered on the c-chart. The two limits are used on the chart; a control limit at +3  and warnings limit at +2  . If a point falls above the control limit or 2 points in a row fall between the warning and the control limit the process is stopped until the problem is identified and corrected. The centre line is set at an aimed at value co of 1.5. Find the values of the warning and the control limit. 3. A c-chart is used to control imperfections in the glass face of the television picture tube .A target value of co of 1 is used with 5 identical size tubes forming a subgroup. A c-chart may be used in this case since the subgroup size is constant. Find the 3 sigma control limits for this process 4. A c-chart is to be used to control soldering imperfections on a certain mass produced circuit board. After 30 circuit board have been inspected a total of 42 bad solder joints were found. (a) Calculate 3 sigma control limits and the central limit for c-chart. (b) Find the probability of a point out of control on this chart. if the process should suddenly shift to a  c of 4. 5. A c chart for non conformities is to be used to control an automobile wind shield forming operation. It is to have 98% probability control limits and 90% probability warning limits. The  c of the process has been holding steady at 1.6. Calculate the control limits and warning limits for this process.

6. A manufacturer produces metal panels that are painted with a liquid and then baked. The finish some times contains the defects, which can be caused by a number of conditions; including the surface of the metal panel, paint viscosity etc. The firm periodically inspects the panels. The defects themselves are independent of one another and are known to be Poisson distributed. For a particular kind of panel the numbers of defects contained in 25 sampled panels were found to be as follows. 7293247682754636172453192 Construct a c chart for the above the data. and interpret it.

7.

The postmaster of a small city receives a certain number of complaints each day about mail delivery. Assume that the distribution of daily complaints is Poisson. Construct a control chart with three sigma limits using the following data. Is the process in control? Day 1

2

3

4

5

6

7

8

9

4

10

14

8

9

6

5

12

13

10

11

12

13

7

6

4

2

14 Complaints 10

8.

The following data represents the number of defects found on each sewing machine cabinet inspected:

Sample Number 1 2 3 4 5 6 7 8 9 10

Number of Defects 8 10 7 7 8 6 9 10 7 8

Sample Number 11 12 13 14 15 16 17 18 19 20

Number of defects 9 11 10 7 5 10 7 9 8 8

Plot a c-chart for the above on a graph paper and comment. 9.

The Mankato Transit System (MTS) uses the number of written passenger complaints per day as a measure of its service quality. For 20 days, the number of complaints received was as follows:

------------------------------------------------------------------------------------------------------------------------Day (sample) No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Total ------------------------------------------------------------------------------------------------------------------------No. of Complaints 6 5 6 5 4 5 3 4 3 0 2 1 2 2 1 1 0 1 0 0 51

-------------------------------------------------------------------------------------------------------------------------

Construct a 99 % control chart. Plot the values on a control chart. Is MTS providing a quality service for its customers? Explain. 10.

The following table gives the results of the inspection of a 100-yd pieces of wooden goods.

Piece No.

No. Of Defects

Piece No.

No. Of Defects

Piece No.

No. Of Defects

1

3

10

8

19

5

2

3

11

4

20

1

3

6

12

10

21

1

4

3

13

5

22

0

5

0

14

5

23

1

6

1

15

5

24

1

7

3

16

4

25

4

8

5

17

3

9

7

18

4

Find c , compute trial control limits and plot a chart for c. 11.

The following tabulation gives defects c observed in an aircraft sub assembly operation observer in various shifts for a week. Prepare a control chart Shift/Day

Mon Tue

Wed Thu

Fri

Sat

Shift 1

19

25

15

19

16

17

Shift 2

20

20

14

9

12

14

Shift 3

18

17

12

14

16

19

Problems on Acceptance Sampling 1.

Calculate using the binomial formula the probabilities of getting 0, 1, 2, 3, or 4 defectives in a sample of 25, given a probability of 0.05 of being defective .Find the probability of getting more than five defectives in this sample of 25. 2.

Calculate the probability of getting 12 heads in 20 attempts from a fair coin

3

The variance of b(x; n, p) = n p (1-p). For given value of n, show that the maximum variance occurs when p = ½.

4.

On an average 5 % items supplied by M/s Acme Ltd. are defectives. If a batch of 10 items is inspected: what is the probability that 2 items are defective. What is the probability that 5 or more items are defective?.

5.

Consider a binomial distribution with n=30, p=0.01. Find the probabilities of x=5,x=10. Now use Poisson distribution to compute these probabilities.

6.

A supplier submits a lot that contains 2 % items as defectives. If a sample of 100 items is selected randomly, what is the probability that the sample will contain fewer than 3 defectives? State all your assumptions.

7.

A service station has received 100 items from a vendor, 20 of which are suspected to be defectives. If a random sample of 5 items is taken, what is the probability that exactly 1 defective item will be found in this sample?

8.

A vendor supplies a lot that contains 4 % defectives. A random sample of 50 is taken from this lot. If the number of defectives in this sample is less than or equal to 3, the entire lot is accepted, else, the lot is rejected. What is the probability of accepting the lot?

9.

10.

.

11.

12.

Excelsior receives a shipment of 3000 items. The sampling plan (n=60, c=3) is used. With respect to this plan, find a) The probability of rejecting a batch that has defective rate of p= 0.02 (in fraction), b) The probability of accepting a batch with defective rate of p=0.06 (in fraction) c) ATI and AOQL for this plan. Construct an OC curve for the following sampling plans a. n=100, c=2 b. n=200, c=4 c. n=50, c=1 Now compute the AOQLs for the above plans assuming lot sizes of 200 items. Draw an OC curve for the sampling plan : n=100, c=2. What is the ATI for this plan if incoming quality is 3 %.

Find the probability of acceptance for the following double sampling plans: a) n1= 80, n2=80, c1=1, r1=4, c2=6, r2=7, p=0.04 b) n1= 50, n2=50, c1=1, r1=4, c2=4, r2=5, p=0.04

Quality Costing 1. Following is the list of various items under quality cost for Excel Ltd., a medium engineering company located in Gurgaon. All figures are in Rs ‘000 for year 2004-2005. Item a) Complaint investigation and adjustment b) Maintenance of test equipment c) Rework d) Product design review e) Incoming material inspection f) Overtime used for rework g) Returns and replacements h) Training (quality related) i) Warranty expenses j) Yield losses Total annual sales

Cost (In Rs ‘000) 43 120 2150 90 60 340 610 75 24 65 20000

Categorize the above items under various heads related to quality costs (such as Prevention, Appraisal, Internal and External failure cost) and analyze the same in as much detail as possible.

Date SIDE A MEL420: TOTAL QUALITY MANAGEMENT: Exercise in Value audit Group Members Entry No/Group No Name Pick up any process you are familiar with. Sample process could be : Opening a bank account, Registering for ME425N course, Applying to a university abroad, getting some treatment in IIT Hospital etc. Write in detail the activities involved in this process. Template A: Existing Process Name of the Process: Sr No Description Time spent Remark: (approximate) Whether Value Adding 1 Yes/No 2 Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Total Yes/No Total number Valueof activities added

Non-Value added

Time spent in Minutes(days) In %

Value added activities

Non-value added activities

SIDE B Now based on the above, improve the process using some interventions such as combining some activities, eliminating some activities, using IT etc. Prepare a modified process Template B: Improved Process Name of the Process: Sr No Description Time spent Remark: (approximate) Whether Value Adding 1 Yes/No 2 Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Yes/No Total Yes/No Total number Valueof activities added

Non-Value added

Time spent in

Value added activities

Minutes(days) In % Comment on the improvements made possible and reasons for these.

Non-value added activities

MEL420 TOTAL QUALITY MANAGEMENT: Exercise in POKA YOKE Group Members Entry No/Group No Name Design a poka yoke for at least 2 applications. Draw a sketch of the existing mechanism and suggest improvements as a failsafe or poka yoke design. Write also the learning from this exercise.

MEL420: TOTAL QUALITY MANAGEMENT: Exercise in DOCUMENTATION Group Members Entry No Group No Name Map any process associated with “Rendezvous” OR “Tryst”.. Document the process in as much DETAIL as possible by clearly Identifying INPUTS, PROCSSING and OUTPUTS required for this. (You may use the revere side also). Kindly also write the insights you have gained through this exercise

Case A: Quality Conflict In your new role as quality manager of the high-tech unit of a large national company, you identify a problem which is typified by the two internal memos shown below. Discuss in detail the problems illustrated by this conflict, explaining how you would set agenda to improvements: Date: 4th Aug From: Marketing Director To: Managing Director cc. Production Director and Works Manager/ We have recently carried out a customer survey to examine how well we are doing in the market. With regard to our product range, the reactions were generally good, but the “Unique Thyristor56” is a problem. Without exception everyone we interviewed said that its quality is not good enough. Although it is not yet apparent, we will inevitably lose our market share. As a matter of urgency, therefore, will you please authorize a complete redesign of this product? -----------------------------------------------------------------------------------------------------------Date: 6th Aug From: Works Manager To: Production Director This really is ridiculous! I have all the QC records for the past ten years on this product. How can there be anything seriously wrong with the quality when we only get 0.1% rejects at final inspection and less that 0.01% returns from customers?

Case B: Case in TPM? The Factory The XYZ factory has a relatively flat organization structure with factory manager, Mr. Biswaranjan Sen on the top. Each manager has some 4-5 officers under him and the officers in turn have some apprentices, who the fresh graduates recruited from regional engineering colleges. Then, of course there are operators. The annual turnover of factory is 400 crores. The place where the factory is situated has a tax benefit and everybody is involved to produce as much as possible in the tax benefit period and so the factory works in 3 shifts. The factory is really quality conscious and everyday there is a meeting of all the managers and QC officer to discuss the quality of previous day. There is a QC Lab which continuously monitors the quality of various raw materials, packing materials as well as produced soaps by doing various chemical and physical tests. The Lab is also operational in 3 shifts. The lab is headed by Mr. Mazher. TPM:Total Productive Maintenance or Time Pass Management ? TPM started in Goa Factory in June 2002. Since then everybody in the factory has been learning TPM. Since then, Managers, Officers and even operators are sent for trainings in TPM. Various workshops are conducted in the factory by experts of TPM. There is TPM Secretariat in the factory, which is headed by Mr. Patil. In the TPM secretariat 5’S is most rigorously employed. It is always kept clean, and all the drawers and cabinets have labels on them telling what is inside. The factory is quite clean and there is strict cleaning schedule of the entire factory. All the operators are ITI technicians and they are taught courses on the machine on which they work. But not all of them are motivated to do autonomous maintenance of the machines. Many a times it was seen that a maintenance person does the routine

maintenance of the machine which according to TPM should be done by operators. Some of the operators do not even know anything about the machine on which they are working. The training started in May’04 and the TPM audit was due in August’04. In the first month of the training not much people were observed to be involved in TPM work. Not many operators were involved in doing any Jishu Hozen, or Kobetsu Kaizan. Planned Maintenance was also not done periodically. Then as came July, the managers started bombarding loads of TPM work on officers. The managers did not tell much to operators because they had a labour union. The officers in turn passed on the work to poor apprentices. There was an apprentice called Sumukh Kamat, who became my friend during the course of the training. He was under Pankaj Nagre, who was maintenance officer. As July came, he was transferred by Mr. Patil to the TPM department from the maintenance department. There is a norm that to obtain successful TPM status you have to have at least 150 kaizens. This job of doing kaizens, which should be done involving all the people, as we have been told many times in the TQM class, was done solely by Sumukh. And he was told to find out 150 kaizans in 1 week, a job which should be done over the entire last year. There were some more apprentices who were given the work to prepare various boards, graphs, one point lessons (OPTs), and God knows what, within that one month period. When asked what they were doing, they said it was ‘Time Pass Management’. So, is it really possible to successfully employ TPM in the factory? Because when the job is not carried out by the very person who is supposed to do it, then what is the use?. But one TPM pillar that was very successfully employed in Goa factory was safety, health and environment. The factory is a “zero effluent factory”. It has an effluent treatment plant and all the water is recycled. All the employees were asked to wear seat belts, where ever they are going. Work permits were required for any contractor work and they were given for a limited time, under the scrutiny of some officer. We think to successfully employ TPM, each and every employee of the factory should be motivated to do so, and managers should not force it on anyone. Unless and until it comes from the heart, the organization will not be able to get any benefit from it, and it will just remain Time Pass Management. Questions a) If you were manger at XYZ, what corrective actions would you take to rectify the situation? b) In a similar fashion, take a real life example you have encountered and articulate your experiences about maintenance scenario (your description should NOT exceed 700 words). c) According to you, what are the critical success factors for successful implementation for TPM? d) How will you go about implementing 5-S in your hostel? e) Take a machine/equipment you are familiar with (such as a TV, refrigerator, bicycle, car, motorbike etc.) - write a step-by-step procedure to maintain the same. The procedure should be self-explanatory and should be written in a user-friendly manner. Draw diagrams wherever necessary!