Quality Management - Quality Tools and Philosophies

Quality and Productivity Productivity = Production Output ($ created) Production Input ($ consumed) Materials + Direct Labor + Indirect Labor + Capital + Service Scrap Scrap Rework Rework Inspection Inspection Machine Machine Warranty Warranty Labor hours / vehicle Productivity vs. Quality in Automobile Assembly US/NA NIC J/J J/NA EU 50 40 30 20 0 20 40 60 80 100 120 140 160 Assembly Defects per 100 Vehicles 180 Statistical Process Control (Shewhart) Control Charts X Charts (“X bar Chart”) 1. 2. 3. 4. Periodical Random Samples xi of n items x1 + x2 + .... + xn x= n Assume µ, σ are known UCL = µ + 3 ⋅ σ x ⇒σx = σ n LCL = µ − 3 ⋅ σ x 5. Plot x ' s 6. Is Process out of Control ? Tests For Control 4/5 in B 6 in row 15 in C UCL A B C µ C B A LCL 2/3 in A 9 below 14 alt. IF µ and σ are unknown „ Use Average of Sample Means x for µ Instead of σ: „ If n ≤ 10 (typically) „ „ Use Average Sample Range R „ or Use Average Standard Deviation of Samples s „ UCL = x + A3 ⋅ s , „ UCL = x + A2 ⋅ R , IF n > 10 „ „ UCL = x + 3⋅ s , c4 ⋅ n LCL = x − A2 ⋅ R LCL = x − A3 ⋅ s LCL = x − 3⋅ s c4 ⋅ n R and s Charts „ „ „ Measure Process Variability Same Idea as X Chart Control Limits for R-chart „ „ UCL = D4 * R, LCL = D3 * R Control Limits for s-chart „ UCL = B4 * s, LCL = B3 * s Parameter Values For X Chart n 2 3 4 5 6 7 8 9 10 15 20 25 R-based A2 1.880 1.023 0.729 0.577 0.483 0.419 0.373 0.337 0.308 0.223 0.180 0.153 s-based A3 2.659 1.954 1.628 1.427 1.287 1.182 1.099 1.032 0.975 0.789 0.680 0.606 For R Chart D3 0 0 0 0 0 0.076 0.136 0.184 0.223 0.348 0.414 0.459 D4 3.267 2.575 2.282 2.115 2.004 1.924 1.864 1.816 1.777 1.652 1.586 1.541 For s Chart B3 0 0 0 0 0.03 0.118 0.185 0.239 0.284 0.428 0.510 0.565 B4 3.267 2.568 2.266 2.089 1.970 1.882 1.815 1.761 1.716 1.572 1.490 1.435 To estimate σ C4 0.7979 0.8862 0.9213 0.9400 0.9515 0.9594 0.9650 0.9693 0.9727 0.9823 0.9869 0.9896 X vs. Wandering of Mean R and s Charts Spreading of Variance 6 Sigma “From 99.73 % To 99.99966 %” Companies Implementing Six Sigma „ „ „ „ „ „ „ „ Motorola Texas Instruments ABB AlliedSignal GE Bombardier Nokia Toshiba „ „ „ „ „ „ „ DuPont American Express BBA Ford Dow Chemical Johnson Controls Noranda Machine Capability Index Specification Width Specification Width σ σ 2σ 6σ Specification Width cp = =1 Process Width [6σ ] 2σ 6σ Specification Width cp = =2 Process Width [6σ ] 6-Sigma and Learning Specification Width Baldridge Award Winners Year M a n u f a c t r u r in g 1999 • • • D a n a C o rp o ra tio n K A R LEE C om p. S T M ic ro e le c tro n ic s 1998 • B o e in g A irlift & T a n k e r S o la r T u rb in e s , 3 M D e n ta l P ro d u c ts S o le c tro n A D A C L a b o ra to rie s A rm s tro n g W o rld In d . C o rn in g In c , T e le c o m m . 2000 1997 1996 1995 • • • • • • 1994 1993 1992 1991 1990 1989 1988 • • • • • • • • • • • E a s tm a n C h e m ic a l A T & T N e tw o rk S y s te m s (N o w L u c e n t) T I (D e fe n s e S y s te m s ) S o le c tro n C o rp . Z y te c C o rp . C a d illa c M o to r C a r IB M R o c h e s te r M illik e n & C o m p a n y X e ro x (B u s in e s s P ro d u c ts & S y s te m s ) M o to ro la W e s tin g h o u s e E le x tric (N u c le a r F u e l) S e r v ic e s S m a ll B u s in e s s e s • O p e ra tio n s M g m t. I n te rn a tio n a l • L o s A la m o s N a tio n a l B a n k • • BI R itz -C a rlto n H o te ls • S u n n y F resh F o o d s • T e x a s N a m e p la te s • M e rrill L y n c h C re d it • X e ro x B u s in e s s S e rv ic e s • D a n a C o m m e rc ia l C re d it C o rp . • T rid e n t P re c is io n • • • • • A T & T C o n su m e r C o m m . S e rv . G T E D ire c to rie s C o rp . • W a in w rig h t I n d u s tr ie s • • A m e s R u b b e r C o rp . G ra n ite R o c k C o m p a n y • M a rlo w In d u s trie s • W a lla c e C o . A T & T U n iv e rs a l C a rd S e rv ic e s R itz -C a rlto n H o te ls • • F e d e ra l E x p re ss • • • • G lo b e M e ta llu rg ic a l Research On Quality Award Winners „ Hendricks & Singhal Management Science, 43, 9, Sep 1997 „ 107% (mean) 48% (median) higher Operating Income „ 64% (24%) higher Change in Sales Management Science, 47, 3, Mar 2000 „ 36% to 46% better Stock Performance Overview of Approaches „ „ „ „ „ Crosby: Juran: General Road Map for Mgmt. Conceptual Model for Costs of Quality Deming: SPC - Application for Shop Taguchi: Finding the right Specs 6-Sigma: Narrowing down on Specs Approach to Q-Improvement 1. 2. 3. 4. 5. 6. Map Customer Needs to Product Specs Optimize Design Parameters (Taguchi) Get Consistent Inputs (weeks) Get in Control (SPC) (months) Get Capable (Kaizen) (year, ongoing) If not capable, then radical Improvement What it takes „ „ „ „ „ „ „ Understanding of Process Understanding of Customer Culture of Trust Quality Incentives Standardized Methods Education & Training Support Systems