Company Wide Quality ControlWe are building... Elegant home of the Century

Nakayama Technology Corporation

APPLICATION TO QUALITYTOWARDS A SYSTEMATIC REDUCTION OF VARIABILITY What is your objective for sampling ?

DATA TYPESVariable data are those obtained as a result of measurement, e.g.,TimeDimensionsWeight

Non-measurable parameters where each outcome are logged in one of two possibilities, e.g., Head or TailAccept or RejectYes or NoATTRIBUTE DATAVARIABLE DATA

Testing is destructive

Cost of 100% inspection is high

100% inspection causes too much product handling that may cause damage due to mishandling

When is Acceptance Sampling Useful?

ACCEPTANCE SAMPLINGADVANTAGES

Less handling damage

Fewer inspectors, thereby simplifying the recruiting and training problem

ACCEPTANCE SAMPLINGADVANTAGES

Upgrading the inspection job from monotonous piece-by-piece decisions to lot-by-lot decisions

Applicability to destructive testing with a quantified level of assurance of lot quality

ACCEPTANCE SAMPLINGDISADVANTAGES

There are risks of accepting bad lots and rejecting good lots

There is added planning and documentation

What Is Risk Management?

Expect the unexpectedHope for the bestPlan for the worst (financial and action plans)Have plans B and C ready. D and more if the stakes are highHave redundancy in the system (more that one person should be able to perform any task)Assign ownership to each risk, and hold the owner to it!MonitorReview, modify and improveLead!!!!!Communicate!!!!

Some Benefits of Risk ManagementMinimize management by crisisMinimize surprises and problemsGain competitive advantageDecrease project variancesIncrease probability of project successImprove financial performance of project

Risk Management is a Balancing Act

It measures performance of an acceptance sampling plan

It plots probability of accepting the lot versus lot fraction defective (p)

It shows the probability of accepting a lot submitted with certain fraction defectiveOperating Characteristic (OC) Curve

Operating Characteristic Curve

Operating Characteristic Curve

Ideal OC Curve The ideal OC curve could be realized by 100% inspection/testing which are error-free.

In practice, the ideal OC curve almost never happens.

And Now that Youve Learned Little of Everything.

BALLMILLSLURRYSPRAY DRYERSILOBPTTILE FORMINGPass/Fail ?Pass/Fail ?Pass/Fail ?Pass/Fail ?Pass/Fail ?GLAZE PREPARATIONPilot Run (Slide test)Pilot Run (Powder test)

Pass/Fail ?VARIABLE & ATTRIBUTE INSPECTION

For 1 hour operation = 2,500 ~3,000 tiles (30 trials)

2 samplings in 1 hour with 20 sub-sample every 30 minutes

6 = PASSAbove 6 =FAIL (FOR 100% SORTING)

.Appendix 2Master Table for Normal Inspection- Single Sampling (MIL STD 105E, Table II-A)

BALLMILLSLURRYSPRAY DRYERSILOBPTTILE FORMINGPass/Fail ?Pass/Fail ?Pass/Fail ?Pass/Fail ?Pass/Fail ?GLAZE PREPARATIONPilot Run (Slide test)Pilot Run (Powder test)ASSEMBLY

Pass/Fail ?VARIABLE & ATTRIBUTE INSPECTION

If NC > 1.5%, what to do?

Change LOT ( tiles )Change MODEL

IN-ComingProcessFinalManufacturingPass/Fail ?Pass/Fail ?Pass/Fail ?Pass/Fail ?ASSEMBLYCutting SectionNTC SYSTEM REDUCING OF VARIABILITY

.Appendix 2Master Table for Normal Inspection- Single Sampling (MIL STD 105E, Table II-A)

IN-ComingProcessFinalManufacturingConnectionConnectionASSEMBLYBATCH PROGRAMEDSEPTEMBER 2004Cutting SectionNTC BATCH / LOT SYSTEMLOT TRACEABILTYAUGUST 2005LOT TRACEABILTYAPRIL 2005EXPORT

PROBLEM SOLVING APPROACH Traditional Supernatural Intuition

Manufacturing Product ControlAssume Fraction defective, p=0.01 ( Best Practice! )Sample size, n = 89Acceptance number, c = 2

The probability of accepting (Pa) the lot can be computed with Binomial or Poisson approximation: Pa = 0.938

Note: 1. Mathematical formula is not emphasized. 2. Comparison of Binomial & Poisson approx.

Poisson Table

Sheet1

d

np012345678910

0.029801000

0.049619991000

0.069429981000

0.089239971000

0.19059951000

0.158619909991000

0.28199829991000

0.257799749981000

0.37419639961000

0.357059519941000

0.46709389929991000

0.456389259899991000

0.56079109869981000

0.555778949829981000

0.65498789779971000

0.655228619729969991000

0.74978449669949991000

0.754728279599939991000

0.84498099539919991000

0.854277919459899981000

0.94077729379879981000

0.953877549299849971000

13687369209819969991000

d

np012345678910

1.13336999009749959991000

1.23016638799669929981000

1.32736278579579899981000

1.42475928339469869979991000

1.52235588099379819969991000

1.62025257839219769949991000

1.71834937579079709929981000

1.81654637318919649909979991000

1.91504347048759569879979991000

21354066778579479839959991000

2.21113356238199289759939981000

2.4913085707799049649889979991000

2.6742675187368779519839959991000

2.8612314696928489359769929989991000

3501994236478159169669889969991000

3.2411713806037818959559839949981000

3.433147340558744871942977992997999

3.627126303515706844927969988996999

3.822107269473668816909960984994998

41892238433629785889949979992997

4.21578210395590753867936972989996

4.41266185359551720844921964985994

4.61056163326513686818905955980992

4.8848143294476651791887944975990

d

np012345678910

5740125265440616762867932968986

5.2634109238406581732845918960982

5.452995213373546702822903951977

5.642482191342512670797886941972

5.832172170313478638771867929965

621762151285446606744847916957

6.221554134259414574716826902949

0.421246119235384542687803886939

6.611040105213355511658780869927

6.8193493192327480628755850915

7173082173301450599729830901

7.2162572156276420569703810887

7.4152263140253392539676788871

7.6141955125231365510648765854

7.8041648112210338481620741835

8031442100191313453593717816

Sheet2

Sheet3

An assumption in the construction of OC curve is that the submitted lot is from a steady stream of product which the population can be considered to be infinite and therefore the binomial distribution can be used for the probability calculations.Problem solving are important skills that every successful individual should possess.At home or work, all of us are expected and essentially to be a problem solvers (irrespective good or bad)

Scientific Approach is a systematic way of reflective thinking comprised of:Reasoning - Why not? When not? Where not?Questioning - 5W1HReview of what is known about the questionsData collection and experiment.

The Binomial and Poisson approximation to compute the probability of acceptance is not emphasized here. Computer software can perform this. Its interpretation is emphasized instead.Doty(364-366)