Module 19 · Capstone

Capstone: a DMAIC project end to end

One process, one problem, every tool. A brazed aluminium heat-exchanger line rejects about four cores in a hundred at the leak test. You are the Green Belt. The datasets below are everything the project collected, in the order it collected them; work each phase yourself before you open its solution. Nothing here is a real company's data: every number was generated by a seeded script so that the story holds together, and every number on this page is traceable to that script.

Learning objectives

How to use this module

Each phase gives you the situation, the data, and a set of tasks. Do the tasks with the calculators (linked in each phase and collected on the Calculators page) or your own software; the tables can be copied straight into a spreadsheet. Then open the solution. Where the solution reports a judgement rather than a number ("this is a lead, not a cause"), argue with it; that is the point. The whole project is about 5,000 words of reading and perhaps a day of work.

Why this matters

Published DMAIC cases with real data are rare, because the data are proprietary; the ones that exist show what a completed project looks like. Sharma and Rao's 2014 open-access case in the Journal of Industrial Engineering International took an engine crankshaft grinding process through DMAIC with an Ishikawa diagram and a process FMEA in Analyze, and reported the standard deviation of the critical dimension falling from 0.003 to 0.002 mm, Cp rising from 1.29 to 2.02 and Cpk from 0.32 to 1.45, figures cited here exactly as the authors published them.[1] That shape, a capability index that was unacceptable, a cause found with the analysis tools, a designed change, and a capability index that is acceptable with a chart to keep it there, is the shape of the project below, with one difference: here you can check every number.

Define

The situation

The line brazes aluminium heat-exchanger cores: tubes are expanded into header plates, fitted with fins and baffles, clamped in a fixture, fluxed and passed through a controlled-atmosphere furnace where a clad filler melts and fills the joints. Every finished core is helium leak-tested. Over the last quarter the leak test rejected 0.042 of the cores, 4.2 %, which the charter (Module 3) recorded as 42 per 1,000 with a goal of no more than 10 per 1,000, 1.0 %.[2] A rejected core is either reworked by hand (a second braze at a repair station) or scrapped; both are expensive, and the customer has asked what the plan is.

Tasks. (a) Write the problem statement and the goal statement in the Module 3 form: what, where, how much, since when, and the measurable target. (b) Draw the SIPOC. (c) Name the primary CTQ and its metric, and the secondary metric that must not get worse. (d) List the stakeholders and what each needs from the project.

Show the solution

(a) Problem: "Over the last quarter, 4.2 % of brazed cores (42 per 1,000) failed the final helium leak test, against a historical level the plant regards as normal of about 1 %, causing rework and scrap and a customer escalation." Goal: "Reduce the leak-test reject rate to at most 1.0 % (10 per 1,000) within four months, confirmed by a p chart over 30 production shifts, without increasing cycle time or rework."

(b) SIPOC. Suppliers: tube and header supplier, filler-clad sheet supplier, flux supplier. Inputs: tubes, headers, fins, baffles, flux, furnace atmosphere. Process: expand tubes into headers → assemble fins and baffles → clamp in fixture → flux → braze in furnace → cool → leak test. Outputs: leak-tight cores; leak-test records. Customers: the assembly plant; the end customer; the repair station (as an internal, unwanted customer).

(c) Primary CTQ: leak-tight joints; metric: leak-test reject rate per lot, with the leak location recorded. Secondary metric: braze-joint gap at the tube-to-header joint (the physical variable behind the CTQ, once Measure confirms it), and cycle time, which must not grow.

(d) The plant manager (cost, customer), the customer's quality engineer (evidence, timing), the furnace and fixture owners (their processes will be examined), the leak-test operators (they record the data and locate the leaks), the repair station (their workload should fall), and finance (the benefit calculation, which is theirs to make, not the Green Belt's).

Measure

Step 1: can we measure the gap?

The braze-joint gap at the tube-to-header joint is the variable the team suspects. Before any study of it, the gauge: a calibrated pin-gauge set reading to 0.001 mm, used by three operators. Ten cores spanning the range were measured twice by each operator in random order.

Table 1. Gauge R&R on the joint-gap gauge, mm (constructed data): 10 cores × 3 operators × 2 trials.
PartA · trial 1A · trial 2B · trial 1B · trial 2C · trial 1C · trial 2
10.0740.0770.0750.0760.0680.078
20.0780.0860.0830.0820.0800.080
30.0980.0960.1020.0940.0960.093
40.1040.0970.1030.1040.0970.103
50.1040.1060.1070.1020.1000.102
60.1190.1190.1160.1170.1140.114
70.1230.1230.1300.1230.1210.123
80.1310.1330.1350.1370.1290.136
90.1360.1370.1400.1400.1380.136
100.1510.1520.1500.1550.1480.147

Tasks. (a) Run the crossed gauge R&R by the ANOVA method. (b) Report %R&R of study variation and of the 0.10 mm tolerance, repeatability against reproducibility, and ndc. (c) Is the gauge acceptable for the capability study that follows, by the AIAG MSA guidelines?

Show the solution

(a) The part × operator interaction is not significant (F = 0.34, p = 0.99), so it is pooled into repeatability. Operators differ (F = 9.07, p = 0.0005): a small but real reproducibility component.

(b) Standard deviations: repeatability 0.00254 mm, reproducibility 0.00161 mm, gauge R&R 0.00301 mm, part-to-part 0.02475 mm, total 0.02493 mm. %R&R of study variation = 12.1 %; of tolerance = 6 × 0.00301 / 0.10 = 18.1 %; ndc = 1.41 × 0.02475 / 0.00301 = 11.6, reported as 11. Repeatability (10.2 %) dominates reproducibility (6.5 %).

(c) Acceptable with a note: under 10 % would be unconditional; 10 to 30 % is the "may be acceptable depending on the application" band of the AIAG MSA guidelines (cited in Module 4 as guidelines, confirmed through secondary sources), and 18 % of a 0.10 mm tolerance means the gauge alone uses a fifth of it.[3] ndc of 11 is well above the guideline of 5. Proceed with the capability study, record the gauge's contribution, and note that the operator difference (about 0.0016 mm) is worth a look at how the pins are seated.

Table 1 in the gauge R&R calculator (inputs collapsed)

Step 2: the baseline, as an attribute

Thirty shifts of leak-test results, one lot per shift.

Table 2. Baseline leak-test results by lot (constructed data): cores tested, leakers, and the lot proportion.
LotnLeakersp
119780.0406
220150.0249
322690.0398
424580.0327
515350.0327
616490.0549
723380.0343
8245100.0408
9175130.0743
10181130.0718
11237120.0506
1219280.0417
1317760.0339
1423370.0300
15175130.0743
1619180.0419
1721560.0279
1820590.0439
1915880.0506
2015270.0461
21237140.0591
2222650.0221
23234100.0427
2420480.0392
2523250.0216
2618390.0492
27195110.0564
28229100.0437
2916250.0309
30180100.0556

Tasks. (a) Build the p chart. Is the reject rate stable? (b) State the baseline as a capability: p̂ with its 95 % interval, DPMO, and the long-term Z. (c) How many cores would a confirmation study need to know the rate to within ±0.5 percentage points? (d) Compare with the charter's 4.2 %.

Show the solution

(a) 259 leakers in 6,037 cores: p̄ = 0.0429. Limits for a lot of 150: 0.0429 ± 3 × 0.0165, upper 0.0925, lower below zero; for 250: upper 0.0813, lower 0.0045. No lot is beyond its limits and no Western Electric rule fires (Nelson's test 3, six rising, fires once at lot 14, a pattern this weak is a false alarm with all tests switched on). The reject rate is stable: the process reliably makes about four leakers in a hundred. That is a common-cause problem, which is what a DMAIC project is for; a special-cause problem would need the reaction plan, not a project.

(b) p̂ = 4.29 %, Wilson 95 % interval 3.81 to 4.83 %; DPMO 42,902 (one opportunity per core, the honest count); Zlong-term = 1.72, "sigma level" 3.22 with the 1.5 shift, which nobody should put on the charter without the Module 6 caveats.

(c) N = 1.96² p̂(1 − p̂)/0.005² = 6,310 cores, about a month at the current volume. The interval on the baseline is already about ±0.5 points because the study has that many cores.

(d) The charter's 42 per 1,000 sits inside the interval; the baseline is confirmed at 43 per 1,000 over these 30 shifts.

Table 2 as a p chart (inputs collapsed)

The baseline as DPMO and sigma level (inputs collapsed)

Step 3: where the leaks are

The test operators recorded the leak location for every leaker of the baseline period.

Table 3. Leak location of the 259 baseline leakers (constructed data).
Leak locationLeakers
Tube-to-header joint168
Tube-to-tube joint41
Baffle joint22
Manifold weld17
Other / not located11

Tasks. (a) Build the Pareto. (b) What fraction of leaks is at the tube-to-header joint, and what do the first two categories cover? (c) What does the Pareto not tell you?

Show the solution

(a, b) Tube-to-header joints account for 168 of 259 leakers, 64.9 %; with tube-to-tube joints the first two categories cover 80.7 %. The project's scope narrows to the tube-to-header joint: fix that and the reject rate falls by roughly two thirds at most, to about 4.29 × (1 − 64.9/100) ≈ 1.5 % if every header leak were eliminated, which is still above the goal. The other categories will need attention later, and the charter's goal should be read with that arithmetic in mind.

(c) Why the header joints leak. A Pareto locates, it does not explain. It also depends on the operators' classification, which is an attribute measurement system in its own right: an attribute agreement analysis (Module 4) on a sample of leakers would confirm that "tube-to-header" means the same thing to all three operators before the project bets on it.

Step 4: the gap, with its chart first

Five consecutive cores every hour for 25 hours, the mean tube-to-header gap per core (six joints) measured with the pin gauge. Specification 0.10 ± 0.05 mm.

Table 4. Baseline joint gap, mm, 25 subgroups of 5 cores (constructed data), with subgroup means and ranges.
Subgroupx1x2x3x4x5Mean x̄Range R
10.1150.1040.1060.0770.1380.10800.061
20.1290.1070.1230.1160.1040.11580.025
30.1260.1070.1070.1010.1190.11200.025
40.1110.1200.1030.1140.0990.10940.021
50.1240.1150.1170.1180.0970.11420.027
60.1230.1420.0880.0870.0900.10600.055
70.1240.1140.1280.1220.1150.12060.014
80.1160.1100.1250.0960.1060.11060.029
90.1160.1380.1010.0960.1040.11100.042
100.1260.1090.1310.0850.1280.11580.046
110.1270.0910.1140.1300.1130.11500.039
120.1260.1460.1160.1080.1010.11940.045
130.1210.1090.1090.1100.1210.11400.012
140.0970.0900.0770.1290.1130.10120.052
150.1340.1120.1010.1190.1110.11540.033
160.0940.0990.1380.1170.1180.11320.044
170.1080.1020.1250.1100.1010.10920.024
180.1100.0990.1150.1280.1000.11040.029
190.1330.1020.1140.1000.1090.11160.033
200.1130.1060.1020.1020.1000.10460.013
210.0890.1080.1180.1250.1210.11220.036
220.1480.1170.1050.1390.0970.12120.051
230.1260.0980.1170.0830.1250.10980.043
240.1100.0980.1360.1230.1130.11600.038
250.1010.1110.1100.1230.1240.11380.023

Tasks. (a) X̄-R chart: is the gap process stable? (b) Normality. (c) Both sigma estimates and the indices under both naming conventions. (d) Predicted PPM out of specification and the observed count. (e) Reconcile the gap capability with a 4.3 % leak rate.

Show the solution

(a) x̄̄ = 0.1124 mm, R̄ = 0.0344 mm; UCL = 0.1124 + 0.577 × 0.0344 = 0.1124 + 0.0198 = 0.1323, LCL = 0.0926; UCLR = 2.114 × 0.0344 = 0.0727. No point beyond a limit on either chart, no Western Electric rule: stable.

(b) Anderson-Darling on the 125 values: p = 0.91. No evidence against normality, and a gap of this kind (a difference of two machined dimensions) has no physical reason to be skewed.

(c) σ̂within = 0.0344 / 2.326 = 0.01479 mm; overall s = 0.01414 mm; ratio 0.96. Mean 0.1124 mm, 0.0124 mm above the 0.10 mm target: the upper side governs. Overall (2026 Cp/Cpk, since stable): Cp = 0.10 / 0.08485 = 1.18; Cpu = 0.0376 / 0.04242 = 0.89; Cpl = 1.47; Cpk = 0.89, 95 % interval 0.76 to 1.01. Within (Cwk, legacy Cpk): Cwu = 0.0376 / 0.04437 = 0.85, Cwk = 0.85. k = 0.25: a quarter of the half-tolerance is lost to centring.

(d) Predicted 3,938 PPM beyond the limits, almost all above 0.15 mm; observed 0 of 125, consistent with 0.4 %.

(e) A Cpk of 0.89 predicts 0.4 % of cores with a mean gap beyond 0.15 mm, not 4 %. The reconciliation is physical, not statistical: a joint leaks when its own gap exceeds what the filler can bridge, which the braze engineers put at about 0.14 mm, and the plotted value is the mean of six joints. The fraction of cores whose mean gap exceeds 0.14 mm under the fitted normal is 2.6 %, and individual joints scatter further than the core mean. So the gap distribution is entirely consistent with a few per cent of header leaks, and the specification limit of 0.15 mm is too generous for the process's purpose, a Module 15 conversation for later. The capability study says: stable, centred high, too wide for a joint that must not exceed 0.14 mm.

Table 4 in the capability calculator (inputs collapsed)

Step 5: the furnace, because everyone blames the furnace

The furnace's travelling thermocouple logs the peak core temperature; 40 consecutive cores.

Table 5. Furnace peak core temperature, °C, 40 consecutive cores (constructed data).
Parts12345678910
1–10599.0599.7602.5601.0597.5600.0599.1600.2597.6600.4
11–20600.4602.4600.5600.8597.8603.4597.1601.7599.5598.7
21–30599.0599.0600.6599.8602.2597.3600.0598.7601.2596.8
31–40599.5600.3597.8601.5600.3601.5601.4598.5598.8599.7

Tasks. (a) I-MR chart. (b) What does the chart say about the furnace as a cause of leaks?

Show the solution

(a) x̄ = 599.83 °C, MR̄ = 2.110 °C, σ̂ = 1.871 °C; limits 594.22 to 605.44 °C, MR limit 6.89 °C. Stable; no rule fires.

(b) The furnace peak temperature is stable to about ±5.6 °C around 600 °C. It cannot be the source of a reject rate that is itself stable at 4 % unless the whole band is wrong, which the braze engineers can answer from the filler's melting range, and the DOE below will test. It is not ruled out as a factor; it is ruled out as a special cause, which is a different thing. Everyone stops blaming the furnace, for now.

Analyze

Step 6: causes on paper

The team builds a cause-and-effect diagram for "tube-to-header joint leaks" and a process FMEA excerpt for the expansion, clamping and braze steps (Module 10).

Tasks. (a) List the candidate causes under the six branches. (b) For the three you rate highest, write the FMEA line: failure mode, effect, cause, current control, and the severity, occurrence and detection ratings that lead to an action priority. (c) Which causes can be tested with data you have, and which need new data?

Show the solution

(a) Machine: tube expansion mandrel wear, fixture clamp force, furnace peak temperature and dwell. Material: tube outside diameter and header hole diameter (the gap is their difference), clad thickness, flux quantity. Method: expansion depth, fixture loading sequence, flux application. Measurement: pin-gauge use (now characterised), leak-location classification. Man: fixture loading by shift. Environment: furnace atmosphere dew point.

(b) Three lines, ratings on the 1 to 10 scales of the AIAG-VDA FMEA handbook and its action-priority logic, which replaces the older RPN product:[4] (1) Failure mode: joint gap above bridging limit; effect: leak at test, severity 8 (escape to the customer if the test misses); cause: insufficient tube expansion; current control: none on the gap, leak test at the end; occurrence 6, detection 4; action priority high. (2) Gap above limit; cause: fixture clamp force low or uneven; control: monthly fixture check; occurrence 4, detection 5; high. (3) Incomplete filler flow; cause: furnace peak temperature low; control: continuous thermocouple log with alarm; occurrence 2, detection 2; low. The ratings are judgements and are recorded as such; the value of the exercise is that it puts expansion and clamping ahead of the furnace, which is where the data from Step 5 already pointed.

(c) Expansion and clamping can be tested by comparing the gap on leaking and passing cores (data the repair station can collect from the cores it sections) and by a designed experiment. Furnace temperature is already charted. Material diameters need incoming-inspection data the project does not yet have.

Step 7: is the gap really the cause?

The repair station sectioned 20 leaking cores at the leaking header joint and 20 passing cores at the corresponding joint, and measured the actual gap.

Table 6. Header-joint gap, mm, on 20 leaking and 20 passing cores (constructed data).
Group1234567891011121314151617181920
Leak0.1390.1310.1320.1080.1590.1510.1330.1460.1400.1300.1490.1330.1330.1270.1420.1360.1440.1300.1390.126
Pass0.1220.1130.1150.1160.0960.1210.1390.0870.0860.0890.1220.1120.1250.1200.1130.1140.1080.1220.0940.104

Tasks. (a) Compare the two groups with the appropriate test. (b) Report the difference, its interval, the p-value in a correctly worded sentence, and an effect size. (c) Does this establish causation?

Show the solution

(a) Welch's two-sample t-test (Module 11). Means: leakers 0.1364 mm, passers 0.1109 mm; standard deviations 0.0109 and 0.0142; Levene p = 0.34.

(b) Difference 0.0255 mm (25.5 µm); standard error 0.00401; t = 6.37 on ν = 35.6; p < 0.0001; 95 % interval 0.0174 to 0.0336 mm; Cohen's d = 2.01. "Leaking joints had gaps 26 µm larger on average (95 % interval 17 to 34 µm); a difference this large would arise in far fewer than one study in ten thousand if leaking and passing joints had the same gap distribution."

(c) It establishes association in the direction the physics predicts, with an effect of two standard deviations, which is about as strong as observational evidence gets. It does not by itself show that reducing the gap will reduce leaks: a third factor (a tube batch with a smaller diameter, say) could produce both. The designed experiment is what turns "leaking joints have bigger gaps" into "making the gap smaller stops the leaks".

Table 6 in the tests calculator (inputs collapsed)

Improve

Step 8: the experiment

A 2³ factorial with two replicates, 16 cores in random order on the production line during a maintenance window. Factors: A fixture clamp force (2 kN low, 4 kN high; production runs at 4 kN), B tube expansion (standard, or increased with a mandrel 0.05 mm larger; production runs standard), C furnace peak temperature (595 or 605 °C; production runs at 600). Response: the mean tube-to-header gap per core, mm.

Table 7. The 2³ experiment on the braze process, response mean joint gap in mm (constructed data), standard order with cell means.
Std. orderABCy (rep 1)y (rep 2)Cell mean
1 (1)0.1320.1360.13400
2 a+0.1080.1180.11300
3 b+0.1040.0970.10050
4 ab++0.0970.0960.09650
5 c+0.1350.1340.13450
6 ac++0.1090.1230.11600
7 bc++0.1010.1110.10600
8 abc+++0.1000.0980.09900

Tasks. (a) Compute the seven effects. (b) The ANOVA: which effects are real? (c) Interpret the interaction with the two-way table of means. (d) Choose the settings and predict the gap; say what the prediction assumes. (e) What did the experiment say about the furnace?

Show the solution

(a) A = −0.0126, B = −0.0239, C = 0.0029, AB = 0.0071, AC = −0.0001, BC = 0.0011, ABC = −0.0014 mm. Check B by hand: mean of the eight runs at increased expansion minus the eight at standard = −0.0239.

(b) Residual MS = 0.0000292 on 8 degrees of freedom (residual sd 0.0054 mm), standard error of an effect 0.0027 mm. F against a 5 % critical value of 5.32: B 78.1 (p = 0.00002), A 21.8 (p = 0.0016), AB 6.96 (p = 0.030); C 1.13 (p = 0.32) and the remaining interactions are noise. R² = 0.931. Expansion is the dominant factor, clamp force matters, the two interact, and the furnace does nothing over ±5 °C.

(c) Averaged over C: standard expansion gives 0.1343 mm at low clamp and 0.1145 mm at high clamp (the production condition); increased expansion gives 0.1033 mm at low clamp and 0.0978 mm at high. The effect of clamp force is −0.0198 mm with standard expansion and only −0.0055 mm with increased expansion: once the tube fills the hole, the clamp has little left to do. Note the production cell: 0.1145 mm, which is the baseline mean of Step 4 within noise, a consistency check that the experiment reproduced the process it was meant to study.

(d) Increased expansion with the clamp kept at 4 kN (changing one thing on the line is cheaper than two, and the interaction says the clamp can stay). Prediction from the fitted model: ŷ = 0.1124 + −0.00631 + (−0.01194) + 0.00356 = 0.0978 mm, on target, with the same spread as the experiment's replicates (about 0.0054 mm per core, which includes the gauge). It assumes the effect holds over a production run of hundreds of cores rather than eight, and that the new mandrel does not change something the experiment did not measure (tube wall thinning, fin contact). The pilot tests both.

(e) Nothing, over the range tested: C's effect (0.0029 mm) is within noise, and the furnace stays at 600 °C. The maintenance department is pleased.

Table 7 in the factorial calculator (inputs collapsed)

Step 9: pilot and confirmation

The mandrel change is piloted on one fixture for a week (no leakers in 140 cores, and no new failure mode at the fin contact), then released to the line. The capability study is repeated: five cores an hour for 25 hours. The leak test continues for 30 shifts.

Table 8. Joint gap after the change, mm, 25 subgroups of 5 cores (constructed data).
Subgroupx1x2x3x4x5Mean x̄Range R
10.1020.0950.0960.0770.1170.09740.040
20.1110.0970.1070.1030.0950.10260.016
30.1090.0970.0970.0920.1040.09980.017
40.0990.1050.0940.1010.0920.09820.013
50.1080.1020.1030.1040.0900.10140.018
60.1070.1200.0840.0840.0860.09620.036
70.1080.1010.1100.1070.1020.10560.009
80.1030.0980.1080.0890.0960.09880.019
90.1020.1170.0930.0900.0950.09940.027
100.1090.0980.1130.0820.1110.10260.031
110.1100.0870.1010.1120.1010.10220.025
120.1090.1230.1030.0970.0930.10500.030
130.1060.0980.0980.0990.1060.10140.008
140.0900.0850.0770.1110.1010.09280.034
150.1140.1000.0930.1050.0990.10220.021
160.0880.0920.1170.1030.1040.10080.029
170.0970.0930.1080.0990.0930.09800.015
180.0990.0910.1020.1110.0920.09900.020
190.1140.0940.1010.0920.0980.09980.022
200.1000.0960.0930.0940.0920.09500.008
210.0850.0980.1040.1090.1060.10040.024
220.1230.1030.0960.1180.0900.10600.033
230.1090.0910.1030.0810.1090.09860.028
240.0980.0910.1160.1070.1000.10240.025
250.0930.1000.0980.1070.1080.10120.015
Table 9. Leak-test results by lot after the change (constructed data).
LotnLeakersp
119710.0051
220100.0000
322610.0044
424510.0041
515300.0000
616420.0122
723310.0043
824520.0082
917540.0229
1018140.0221
1123730.0127
1219210.0052
1317710.0056
1423310.0043
1517540.0229
1619110.0052
1721500.0000
1820520.0098
1915820.0127
2015210.0066
2123740.0169
2222600.0000
2323420.0085
2420410.0049
2523200.0000
2618320.0109
2719530.0154
2822920.0087
2916200.0000
3018030.0167

Tasks. (a) Repeat the capability study: chart, normality, indices, PPM. (b) The leak rate after: p chart, p̂ and interval. (c) Compare before and after with a proper test. (d) Is the goal met, and with what confidence? (e) What has not been proved?

Show the solution

(a) X̄-R: x̄̄ = 0.1003 mm, R̄ = 0.0225 mm, limits 0.0873 to 0.1133, UCLR = 0.0476; stable, no rule fires. Normality p = 0.87. σ̂within = 0.00968, s = 0.00928 mm (ratio 0.96), the spread reduced by a factor of 1.52 as well as the mean moved. Cp = 0.10 / 0.05569 = 1.80; Cpu = 0.0497 / 0.02784 = 1.79; Cpl = 1.81; Cpk = 1.79, 95 % interval 1.56 to 2.02; Cwk = 1.71; k = 0.005, centred. Predicted PPM beyond the specification 0.07; more usefully, the fraction of core means above the 0.14 mm bridging limit is now negligible. Observed 0 of 125 out.

(b) 49 leakers in 6,037 cores: p̂ = 0.81 %, Wilson interval 0.61 to 1.07 %; DPMO 8,117; Z 2.40. The p chart is stable by rule 1; rule 2 fires once at lot 10 (two of three beyond 2σ), which was investigated without finding a cause and stays in the data.

(c) The 2 × 2 table (before: 259 leak, 5,778 pass; after: 49 leak, 5,988 pass) gives χ² = 146.9 on 1 degree of freedom, p far below 0.001 (the equivalent two-proportion z is √χ² = 12.1). The reduction is 3.48 percentage points, 95 % interval 2.92 to 4.04 points, a factor of 5.3 or 81 %: about 35 fewer leakers per 1,000 cores.

(d) The goal was at most 1.0 %. The point estimate (0.81 %) meets it; the upper end of the interval (1.07 %) does not quite. Honest wording: "the reject rate after the change is 0.81 % (95 % interval 0.61 to 1.07 %); the goal of 1.0 % is met at the point estimate and the data are compatible with a true rate between about 0.6 and 1.1 %." Another 1,933 cores (10 lots) would pin the rate to ±0.4 points. The control phase's ongoing p chart will supply them.

(e) That the remaining leakers are not header leaks: the Pareto must be repeated on the after data. That the improvement survives a mandrel change, a tube supplier change and six months of production, which is what the control plan is for. And the financial figure: the Green Belt reports leakers per 1,000 and the repair station's hours; finance turns that into money.

Table 8 in the capability calculator (inputs collapsed)

Table 9 as a p chart (inputs collapsed)

Control

Step 10: keeping it

Tasks. (a) Write the control plan lines for the changed process. (b) Write the reaction plan for the gap chart. (c) Specify the ongoing monitoring and when the limits may be recomputed. (d) Close the project.

Show the solution
Table 10. Control plan excerpt for the tube-to-header joint (the AIAG control plan structure; entries are the project's decisions, not standard text).
Process stepCharacteristicSpecification / targetGaugeSample, frequencyControl methodReaction plan
Tube expansionMandrel diameter (new size)per drawing; wear limit set by toolingmicrometer, 0.001 mmat each tool change and weeklytool log; replace at wear limitreplace mandrel; check last hour's gap subgroup
Expansion / clampMean joint gap per core0.10 ± 0.05 mm; process target 0.100pin-gauge set (R&R 18 % of tolerance)5 cores every hourX̄-R chart, limits frozen from Table 8: X̄ 0.0873 to 0.1133, R ≤ 0.0476; rules 1 to 4see reaction plan
Braze furnacePeak core temperature600 °C; process band 595 to 605travelling thermocoupleevery core (logged)I-MR chart, limits from Table 5; controller alarmhold cores since last good reading; maintenance
Leak testLeak rate per lot, leak locationgoal ≤ 1.0 %helium leak tester (calibrated leak daily)100 %, one lot per shiftp chart, limits frozen from Table 9; monthly Pareto of locationsrule 1 or run: stop, review gap and furnace charts of the shift; escalate to engineering

(b) Reaction plan for the gap chart. Any point beyond a limit or a rule 2 to 4 signal on the X̄ chart: (1) re-measure the subgroup; (2) if confirmed, hold cores made since the previous subgroup and note tool, lot and operator on the chart; (3) check mandrel wear and clamp force setting; (4) if the cause is found and corrected, release the held cores after a leak test with location recording and a new subgroup inside the limits; (5) if not found within the shift, call engineering; (6) record every signal and its outcome. A point beyond the R limit: check the fixture loading and the gauge before anything else. Never offset the mandrel or the clamp toward a target on the strength of one subgroup.

(c) Ongoing monitoring. The gap and leak-rate charts run with the frozen limits above. Monthly, the quality engineer reports Cpk of the gap from the month's subgroups with its 95 % interval (from 125 values it is about ±0.46 wide at this level), and the leak rate with its interval; a change is real only when the intervals say so and the charts show it. Limits are recomputed only after a deliberate process change (a new mandrel size, a fixture rebuild) has been verified by a fresh study, never because "the process has drifted". This is what an IATF 16949 process-monitoring clause and a PPAP re-submission will ask to see: the studies, the charts, the reactions, and the record of significant events.[5][6]

(d) Closure. The report states the baseline (4.29 %, 3.81 to 4.83 %), the cause (tube-to-header gap running high, established by the sectioning comparison and the experiment), the change (mandrel 0.05 mm larger; clamp unchanged; furnace unchanged), the evidence (Cpk 0.89 to 1.79; leak rate to 0.81 %, interval 0.61 to 1.07 %; χ² = 147), what remains (the other 81 % of the Pareto's tail, the 0.15 mm specification limit that is looser than the joint needs, the operator effect in the gauge), the control plan, and the owner of each chart. Finance attaches the benefit. The Green Belt signs, the process owner signs, and the charts belong to production from that day.

Traps this project avoided, and where you will meet them

  1. Studying the gap before the gauge. An 18 % gauge would have been a 40 % gauge with a worn pin set, and the capability study meaningless. Measure first.
  2. Reporting Cpk = 0.89 as the problem. The specification was not the bridging limit; the physics was. The capability index framed the problem; the sectioning study and the DOE solved it.
  3. Blaming the furnace. A stable chart and an experiment with the furnace as a factor cost a day and settled an argument that had run for a year.
  4. Changing two things. The interaction said the clamp could stay. One change on the line is one thing to control.
  5. Proving with a bar chart. A χ² of 147 and a capability interval that clears 1.5 are proof; two bars are not. And the honest statement that the goal is met at the point estimate but not at the top of the interval is worth more to the customer than a green traffic light.
  6. Declaring victory at 4.3 → 0.8 %. The Pareto said header joints were two thirds of the leaks; the other third is the next project.
  7. Leaving the charts to look after themselves. The control plan names the sample, the frequency, the frozen limits, the reaction and the owner. Without those, the improvement lasts until the next mandrel change.

Quiz

Ten questions on the project. Score 70 % or more to mark the module complete on this device.

1. The baseline p chart showed no point beyond its limits and no Western Electric rule. That means
2. A gauge R&R standard deviation of 0.003 mm against a 0.10 mm tolerance is what %R&R of tolerance (6σ basis)?
3. USL 0.15 mm, mean 0.112 mm, s = 0.0141 mm. What is Cpu (two decimals)?
4. The gap capability predicted 0.4 % beyond the specification but the leak rate was 4 %. The reconciliation was
5. The sectioning study found leaking joints had gaps 25 µm larger (p < 0.0001). This shows
6. In the 2³ experiment the AB interaction was significant. Its practical meaning was
7. Before and after: 259 of 6,037 versus 49 of 6,037. The right proof is
8. The after leak rate is 0.81 % with a 95 % interval of 0.61 to 1.07 % against a goal of 1.0 %. The honest statement is
9. The control plan freezes the gap chart's limits at the values from the after study. They may be recomputed when
10. Who computes the financial benefit in the closure report?
Answer key
  1. b. Stable, common cause.
  2. 18 %.
  3. 0.90.
  4. c. Wrong limit for the physics.
  5. a. Association; the DOE establishes causation.
  6. d. Clamp can stay.
  7. b. Two-proportion test with interval and charts.
  8. c. Met at the point estimate; interval reported.
  9. a. After a verified deliberate change.
  10. d. Finance.

Key takeaways

References

All web sources accessed 2026-09-09 or 2026-09-10. The datasets on this page are constructed; the only real-world case cited is [1], quoted with its published figures. Standards are paraphrased.

  1. Sharma, G. V. S. S., and Rao, P. S. "A DMAIC approach for process capability improvement an engine crankshaft manufacturing process." Journal of Industrial Engineering International 10:65, 2014 (open access). https://link.springer.com/article/10.1007/s40092-014-0065-7 (abstract read; the published figures are cited exactly, not recomputed)
  2. Module 3 of this course, the project charter for the same line (baseline 42 per 1,000 cores; goal 10 per 1,000), whose arithmetic is verified by the same harness as this page.
  3. AIAG. Measurement Systems Analysis (MSA) Reference Manual, 4th ed., 2010. https://www.aiag.org/training-and-resources/manuals/details/MSA-4 (catalogue; the %R&R bands and ndc ≥ 5 are cited as guidelines, confirmed through secondary sources as recorded in Module 4)
  4. AIAG and VDA. FMEA Handbook, 1st ed., 2019. https://www.aiag.org/training-and-resources/manuals/details/FMEAAV-1 (catalogue; the action-priority logic in place of RPN, as taught in Module 10)
  5. AIAG. Control Plan, 1st ed., March 2024 (catalogue CP-1). https://www.aiag.org/training-and-resources/manuals/details/CP-1 (catalogue; structure of the control plan used in Table 10)
  6. Biswas, P. "IATF 16949:2016 Clause 9.1.1.1 Monitoring and measurement of manufacturing processes." 6 August 2023. https://preteshbiswas.com/2023/08/06/iatf-169492016-clause-9-1-1-1-monitoring-and-measurement-of-manufacturing-processes/ (commentary on the clause: process studies, reaction when unstable or not capable, records of significant events; the standard itself is the primary source)
  7. AIAG & VDA. Statistical Process Control (SPC) Manual, 1st ed., February 2026. The capability conventions, stability criteria and chart methods used throughout, as cited in Modules 7, 8, 16 and 17. Page-wide source; no single claim on this page rests on it alone. https://www.aiag.org/training-and-resources/manuals/details/SPCAV-1 (licensed copy read by the author)
  8. NIST/SEMATECH. e-Handbook of Statistical Methods: 6.1.6 (capability), 6.3.2 and 6.3.3 (control charts), 7.2.2 and 7.2.4 (comparisons and proportions), 5.3.3 (design of experiments). Page-wide source; no single claim on this page rests on it alone. https://www.itl.nist.gov/div898/handbook/
  9. Wasserstein, R. L., and Lazar, N. A. "The ASA's Statement on p-Values: Context, Process, and Purpose." The American Statistician 70(2):129 to 133, 2016. The wording of every p-value sentence on this page; page-wide source rather than a single-claim citation. https://www.stat.berkeley.edu/~aldous/Real_World/ASA_statement.pdf

Further reading