© 2002 Systex Services Capability and Improvement - from Cpk to Six Sigma

© 2002 Systex Services Capability & Improvement Manufacturing Processes Statistical Process Control Parts Continuous Improvement Processes People Six Sigma Business Processes Vital for credibility and results

© 2002 Systex Services Statistical Process Control - theory and practice

© 2002 Systex Services Use of Statistical Process Control Attributes and variables Attribute OK or Not OK Variable Measurable

© 2002 Systex Services SPC Application Initially applied to mechanical components –in mass production –as a control mechanism Subsequently applied to any measurable

© 2002 Systex Services Principles of SPC for Variable Data Rules apply when distribution is normal Bell Curve

© 2002 Systex Services Principles of SPC for Variable Data Rules do not apply when distribution is abnormal Skewed Multiple Truncated Random Selection

© 2002 Systex Services Principles of SPC for Variable Data Normal distribution has consistent variation Variation unit is ‘Standard Deviation’ -  (Sigma) Standard deviation is calculated using:  =  (  fx 2 /n) - x 2 (Root Mean Square method)

© 2002 Systex Services Principles of SPC for Variable Data Standard deviation :  =  (  fx 2 /n) - x 2 (Root Mean Square method) Forget it! - use MS Excel functions - STDEV, STDEVP - or specialist software

© 2002 Systex Services Principles of SPC for Variable Data Standard Deviation enables calculation of probability of defects Defects with spec. limits at: 1 sigma = 31.74% = 317,400 dpm 2 sigma = 4.56% = 45,560 dpm 3 sigma = 0.27% = 2,700 dpm

© 2002 Systex Services Principles of SPC for Variable Data Normal distribution relative to limits –forecasts scrap –defines process capability –enables process control ‘Normal’ distribution Upper control limitLower control limit Lower spec. limitUpper spec. limit

© 2002 Systex Services Capability Studies Process capability is relative to: –defined limits –location of process mean –spread of process LSL USL NOM Broad spread Good placement Moderate spread Moderate placement Narrow spread Poor placement

© 2002 Systex Services Capability Studies Purpose of capability studies –to define process capability –to help identify limiting causes –to demonstrate capability to customers –to improve process capability reduce defects, waste, cost, customer returns undertake higher spec. work –to employ statistical process controls

© 2002 Systex Services Capability Studies C p –spec. range  6  –no account of placement C pk –lower value of –(USL - X) / 3  or (X - LSL) / 3  Two basic measures of capability LSL USL X 3    Cp = (USL-LSL)/6   x   Cpk = (X-LSL)/3   x   0.667

© 2002 Systex Services Capability Studies What is a good Cpk ratio? Minimum normally 1.33 Cpk –based on 4 sigma spread –extra sigma compensates for larger spread over time & larger population particularly mean shift –equivalent to 63 DPM on centred process Many companies now looking for 2.0 Cpk –consistent with 6 sigma concept –equivalent to 0 DPM based on centred process allowing up to 2 sigma shift

© 2002 Systex Services Capability Studies Capability studies also indicate: –trends –cycles –other influences

© 2002 Systex Services X-Bar & Range Charts X-bar charts plot sample mean values

© 2002 Systex Services X-Bar & Range Charts Range charts plot sample range values

© 2002 Systex Services Capability Reports Capability study results required by many major customers

© 2002 Systex Services Six Sigma - achieving quantum leaps in competitiveness

© 2002 Systex Services Six Sigma Application Applies Statistical Process Control to ALL business process - not just manufacturing Combined with classical Continuous Improvement Techniques

© 2002 Systex Services Six Sigma Objective Service output Critical customer requirement e.g. 3 day delivery Defects: > 3 days Reduced variation

© 2002 Systex Services Six Sigma Example

© 2002 Systex Services 6 Sigma & Quality Loss Function Normal Distribution Quality Loss Function Taguchi: Quality Loss Function = k(x - T) 2 Where: k = constant for scrap value x = value of quality characteristic T = target

© 2002 Systex Services What is Six Sigma? Suppliers Inputs Processes Process outputs Critical customer requirements Markets Defects Variations in process output cause defects Root cause analysis of defects leads to permanent defect reduction Six Sigma Business Improvement... … a data driven approach to root cause analysis

© 2002 Systex Services Six Sigma Success Factors Committed Leadership Integration with top level strategy Business process framework Customer & market intelligence network Projects produce real savings or revenue Full time six sigma team leaders Incentives for all

© 2002 Systex Services 6 Sigma & Business Strategy Leadership Process Business Strategy Development Core business Process Key Performance Measures Process Output Measures Critical Customer Requirements Marketplace Process Sigma

© 2002 Systex Services 6 Sigma Process MEASUREMENT: - selection - measurability - acceptability ANALYSIS: - process capability - experimentation - root cause IMPROVEMENT: - actions - process trials - proving CONTROL: - selection - maintenance - reaction Project by project

© 2002 Systex Services Implementing 6 Sigma Organisational Assessment Appoint core team Process mapping Current measures Process owners Customer knowledge Customer surveys Current capabilities Competitive data Accountabilities Over 4 weeks Exec. Planning Workshop Vision/ goals/ 6 sigma Basis for improvement Tools & methods 5 year plan: net earnings growth improvements Opportunities Select pilot units Communication plan Leadership criteria Resource planning Commitment 2 days Pilot Business Unit Workshops Strategy outline 6 sigma methods Integration process Status assessment Identify projects Benefit targets Force field analysis Select leaders Training schedules Project milestone Set regular reviews 2 days 6 Sigma Leader Training High profile launch Interactive training Project definition Mapping Measurement Analysis Analytical tools Design of experiment Process sigma Apply Facilitate teams Measurable benefits weeks Typical time scales

© 2002 Systex Services 6 Sigma Roll Out Organisational Assessment Executive Workshop Pilot Unit Workshop Team Leader Training Unit Review Executive Review Projects Team Leader Training Unit Workshops

© 2002 Systex Services 6 Sigma Black Belt Training Green Belt Black Belt

© 2002 Systex Services 6 Sigma Comments Large cost reductions: –AlliedSignal $800M (95/7) –GE $600M (3Q97 gain) Performance bonus link Capability quantified Investors & stakeholders understand financial gain Customer needs measured Year one payback - ROI potential 20% + thereafter Large initial investment off putting Poor follow through Short term thinking Changed priorities New leadership ‘Tried that’ (no longer use it!) Fear of statistics BenefitsRisks