Chapter 4 Quality Improvement.

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1 Chapter 4 Quality Improvement

2 Traditional Economic Model of Quality of Conformance
Total cost Cost due to nonconformance Cost of quality assurance 100% “optimal level” of quality

3 Modern Economic Model of Quality of Conformance
Total cost Cost due to nonconformance Cost of quality assurance 100%

4 Problem Solving Problem: any deviation between what “should be” and what “is” that is important enough to need correcting Structured Semistructured Ill-structured Problem Solving: the activity associated with changing the state of what “is” to what “should be”

5 Quality Problem Types Conformance problems
Unstructured performance problems Efficiency problems Product design problems Process design problems

6 Problem Solving Process
Redefining and analyzing the problem Generating ideas Evaluating and selecting ideas Implementing ideas

7 The Deming Cycle Act Plan Study Do
Sürekli İyileştirmede Deming Döngüsü Planlama aşaması, kaliteye ilişkin amaç ve standartların tanımlandığı aşamadır. Birinci aşamada iyileştirme yapılacak alan ve bu alanın sorunları belirlenir. Bu aşama mevcut durumun incelenmesinden ve sürecin tanımlanmasından oluşur. Sürecin girdileri, çıktıları, müşterileri ve tedarikçileri tanımlanır. Buna ek olarak müşteri beklentileri belirlenir, veri toplanır, sorunların neler olduğu ortaya konulur, nedenlere ilişkin kuramlar test edilir ve çözümler ve eylem planları geliştirilir. Burada iyileştirme alternatifleri arasından en iyi olanlar seçilmeli ve önerilerin uygulanmasını sağlayan bir plan geliştirilmelidir. İkinci aşamada belirlenen plan uygulamaya konulmalı ve uygulamanın durumu izlenerek sonuçları ölçülmelidir. Uygulama ya da yapma aşamasında plan deneme düzeyinde uygulanır. Bu bir laboratuarda olabileceği gibi, bir pilot üretim sürecinde ya da küçük bir müşteri grubu üzerinde olabilir ve bu yolla önerilen çözüm değerlendirilir ve objektif veriler toplanır. Çözümün deneysel düzeyde uygulamaya konulmasından veriler toplanır ve belgelenir.

8 Juran’s Improvement Program
Proof of the need Project identification Organization for breakthrough Diagnostic journey Remedial journey Holding the gains İncelemeden oluşan üçüncü aşamada ise denenen iyileştirme önerisinin olumlu bir farka yol açıp açmadığı belirlenmektedir. Burada, sonuçlar değerlendirilir, gerçekleşen öğrenme kaydedilir ve ele alınması gereken başka konuların ve fırsatların olup olmadığı belirlenir. Böylece deneme planının iyi işleyip işlemediği tesbit edilir. Genellikle ilk çözüm üzerinde değişiklik yapılması ya da bu çözümün bir kenara bırakılması gerekebilecektir. Bu aşamada uygulama aşamasına geri dönülerek yeni çözümler önerilir ve değerlendirilir. Düzeltme eyleminden oluşan dördüncü aşamada ise, elde edilen sonuca göre davranılır. Bir önceki aşamada elde edilen sonuç olumlu ise, bu önerinin günlük işlemlerle bütünleştirilerek sisteme sokulmasına ilişkin çalışmalar gerçekleştirilmektedir. Eğer elde edilen sonuç olumsuz ise, bu döngü yeniden işletilmeye başlanarak yeni bir önerinin planlanıp aynı şekilde uygulamaya konulması, sonuçların kontrol edilmesi ve düzeltme eyleminde bulunulması şeklindeki aşamalar tekrarlanır. Bu aşamada iyileştirmeler standart hale getirilir ve son plan “mevcut en iyi uygulama” olarak uygulamaya konulur ve örgütün tamamına iletilir. Bu süreç daha sonra planlama aşamasına geri döner ve başka iyileştirme fırsatlarının ve olanaklarının belirlenmesine yönelir.

9 Bethesda Hospital Model
Start Review current situation Describe process Explore cause theories Collect and analyze data Improvement? Generate solutions Plan Do Check Improvement? Act no no yes yes

10 Crosby Quality Improvement Program
Management commitment Quality improvement team Quality measurement Cost of quality evaluation Quality awareness Corrective action Zero defect committee Supervisor training Zero defects day Goal setting Error cause removal Recognition Quality councils Do it over again

11 Creative Problem Solving
Mess Finding – identify symptoms Fact Finding – gather data; operational definitions Problem Finding – find the root cause Idea Finding – brainstorming Solution Finding – evaluate ideas and proposals Implementation – make the solution work

12 SIX SIGMA IS.. A performance goal, representing 3.4 defects for every million opportunities to make one. A series of tools and methods used to improve or design products, processes, and/or services. A statistical measure indicating the number of standard deviations within customer expectations. A disciplined, fact-based approach to managing a business and its processes. A means to promote greater awareness of customer needs, performance measurement, and business improvement. Six Sigma approach aims to reduce defect levels to only a few parts per millon for an organization’s key products and processes. Accomplishing this hard task requires effectice implementation of statistical principles and various tools for diagnosing quality problems and facilitating imprevement.

13 Six Sigma can be described as a business improvement approach that seeks to find and eliminate causes of defects and errors in manufacturing and service processes by focusing on outputs that are critical to customers and a clear financial return for the organization. The term six sigma is based on a statistical measure that equates to 3.4 or fewer errors or defects per million opportunities. A philosophy and set ofmethods companies use to eliminate defects in their products and processes Seeks to reduce variation in the processes that lead to product defects The name, “six sigma” refers to the variation that exists within plus or minus three standard deviations of the process outputs.

14 What’s in a name? Sigma is the Greek letter representing the standard deviation of a population of data. Sigma is a measure of variation (the data spread) σ μ

15 What does variation mean?
Variation means that a process does not produce the same result (the “Y”) every time. Some variation will exist in all processes. Variation directly affects customer experiences. Customers do not feel averages!

16 Measuring Process Performance The pizza delivery example. . .
Customers want their pizza delivered fast! Guarantee = “30 minutes or less” What if we measured performance and found an average delivery time of 23.5 minutes? On-time performance is great, right? Our customers must be happy with us, right?

17 Managing Up the Sigma Scale
% Good % Bad DPMO 1 30.9% 69.1% 691,462 2 308,538 3 93.3% 6.7% 66,807 4 99.38% 0.62% 6,210 5 99.977% 0.023% 233 6 % % 3.4

18 Performance Standards
 PPM Yield 2 3 4 5 6 308537 66807 6210 233 3.4 69.1% 93.3% 99.38% 99.977% % Current standard World Class Process performance Defects per million Long term yield

19 Examples of the Sigma Scale
In a world at 3 sigma. . . There are 964 U.S. flight cancellations per day. The police make 7 false arrests every 4 minutes. In MA, 5,390 newborns are dropped each year. In one hour, 47,283 international long distance calls are accidentally disconnected. In a world at 6 sigma. . . 1 U.S. flight is cancelled every 3 weeks. There are fewer than 4 false arrests per month. 1 newborn is dropped every 4 years in MA. It would take more than 2 years to see the same number of dropped international calls.

20 Six-Sigma Quality Ensuring that process variation is half the design tolerance (Cp = 2.0) while allowing the mean to shift as much as 1.5 standard deviations. Some of the contrasting features between TQM and Six Sigma include: TQM is based largely on worker empowerment and teams; Six Sigma is owned by business leader champions. TQM activities generally occur within a function, process, or individual workplace; Six Sigma projects are truly cross-functional. TQM training is generally limited to simple improvement tools and concepts; Six Sigma focuses on a more rigorous and advanced set of statistical methods and DMAIC methodology. TQM is focused on improvement with little financial accountability; Six Sigma requires a verifiable return on investment and focus on the bottom line.

21 Six-Sigma Metrics Defects per unit (DPU) = number of defects discovered  number of units produced Defects per million opportunities (dpmo) = DPU  1,000,000  opportunities for error

22 k-Sigma Quality Levels
Six sigma results in at most 3.4 defects per million opportunities A six sigma quality level corresponds to a process variation equal to half of the design tolerance while allowing the mean to shift as much as 1.5 standard deviations from the target. A k-sigma quality level satisfies the equation: k × process standard deviation = tolerance range/2

23 Six-Sigma Implementation
Emphasize dpmo as a standard metric Provide extensive training Focus on on corporate sponsor support Create qualified process improvement experts Ensure identification of appropriate metrics Set stretch objectives Projects are the vehicles that are used to organize team efforts and to implement the DMAIC process. Being able to manage a large portfolio of projects, as would be found in Six Sigma environments, is vital to organizational success. Project teams are a vital part of Six Sigma efforts and are comprised of champions, master black belts, black belts, green belts, other team members, who each provide different levels of knowledge and expertise in solving problems. Factors that should be considered when selecting Six Sigma projects are: financial return, as measured by costs associated with quality and process performance, and impacts on revenues and market share, impacts on customers and organizational effectiveness, probability of success, impact on employees, and fit to strategy and competitive advantage.

24 GE’s Six-Sigma Problem Solving Approach
DefineWhat is the critical-to-quality characteristic? The CTQ (critical-to-quality) characteristic in this case is the weight of the cereal in the box. 2. MeasureHow would we measure to evaluate the extent of the problem? What are acceptable limits on this measure? 3. Analyze Decrease Variation Center Process Increase Specifications 4. Improve 6s minimum from process center to nearest spec 5. Control Statistical Process Control (SPC) Use data from the actual process Estimate distributions Look at capability - is good quality possible Statistically monitor the process over time DMAIC Define, Measure, Analyze, Improve, and Control (DMAIC) Developed by General Electric as a means of focusing effort on quality using a methodological approach Overall focus of the methodology is to understand and achieve what the customer wants A 6-sigma program seeks to reduce the variation in the processes that lead to these defects DMAIC consists of five steps….

25 Six Sigma: DMAIC DEFINE MEASURE ANALYZE IMPROVE CONTROL 67,000 DPMO
cost = 25% of sales 3.4 DPMO

26 DMAIC – The Improvement Methodology
Define Measure Analyze Improve Control Objective: DEFINE the opportunity MEASURE current performance ANALYZE the root causes of problems IMPROVE the process to eliminate root causes CONTROL the process to sustain the gains. Key Define Tools: Cost of Poor Quality (COPQ) Voice of the Stakeholder (VOS) Project Charter As-Is Process Map(s) Primary Metric (Y) Key Measure Tools: Critical to Quality Requirements (CTQs) Sample Plan Capability Analysis Failure Modes and Effect Analysis (FMEA) Key Analyze Tools: Histograms, Boxplots, Multi-Vari Charts, etc. Hypothesis Tests Regression Analysis Key Improve Tools: Solution Selection Matrix To-Be Process Map(s) Key Control Tools: Control Charts Contingency and/or Action Plan(s) Most of the tools used in DMAIC have been around for a long time. They include elementary statistical tools, advanced statistical tools, product design and reliability, measurement, process control, process improvement, and implementation and teamwork.

27 Black Belts and Green Belts
project leader Master Black Belt a teacher and mentor for Black Belts Green Belts project team members

28 Tools for Six-Sigma and Quality Improvement
Elementary statistics Advanced statistics Product design and reliability Measurement Process control Process improvement Implementation and teamwork

29 The Seven QC Tools Flowcharts Check sheets Histograms
Cause-and-effect diagrams Pareto diagrams Scatter diagrams Control charts

30 Flowcharts Shows unexpected complexity, problem areas, redundancy, unnecessary loops, and where simplification may be possible Compares and contrasts actual versus ideal flow of a process Allows a team to reach agreement on process steps and identify activities that may impact performance Serves as a training tool

31 Run Chart Monitors performance of one or more processes over time to detect trends, shifts, or cycles Allows a team to compare performance before and after implementation of a solution to measure its impact Focuses attention on truly vital changes in the process * * * * * *

32 Control Chart Focuses attention on detecting and monitoring process variation over time Distinguishes special from common causes of variation Serves as a tool for on-going control Provides a common language for discussion process performance * * * * * *

33 Check Sheet Creates easy-to-understand data
Builds, with each observation, a clearer picture of the facts Forces agreement o the definition of each condition or event of interest Makes patterns in the data become obvious quickly xx xxxxxx x

34 Pareto Diagram Helps a team focus on causes that have the greatest impact Displays the relative importance of problems in a simple visual format Helps prevent “shifting the problem” where the solution removes some causes but worsens others

35 Histogram Displays large amounts of data that are difficult to interpret in tabular form Shows centering, variation, and shape Illustrates the underlying distribution of the data Provides useful information for predicting future performance Helps to answer the question “Is the process capable of meeting requirements?

36 Cause and Effect Diagram
Enables a team to focus on the content of a problem, not on the history of the problem or differing personal interests of team members Creates a snapshot of collective knowledge and consensus of a team; builds support for solutions Focuses the team on causes, not symptoms Effect Cause

37 Scatter Diagram Supplies the data to confirm a hypothesis that two variables are related Provides both a visual and statistical means to test the strength of a relationship Provides a good follow-up to cause and effect diagrams * * * * *