Acronym stands
1.MIG = Metal Inert Gas
2.GMAW = Gas Metal Arc Welding
3.FCAW = Flux Cored Arc Welding
4.Dual Shielding = GMAW-G+S, or MIG welding with Gas Shielding and Flux Cored wire.
5.SMAW = Shielded Metal Arc Welding
6.CFH (AKA cfh) = Cubic Feet per Hour
7.IPM = Inches Per Minute
Welding Defects
Common weld defects include:
•Lack of fusion
•Lack of penetration or excess penetration
•Porosity
•Inclusions
•Cracking
•Undercut
•Lamellar tearing
Tuesday, April 6, 2010
Friday, March 26, 2010
PPAP Requirments...
2.2.1 Design Record
2.2.2 Authorized Engineering Change Documents
2.2.3 Customer Engineering Approval
2.2.4 DFMEA
2.2.5 Process Flow Diagram
2.2.6 PFMEA
2.2.7 Control Plan
2.2.8 Measurement System Analysis
2.2.9 Dimensional Results
2.2.10 Records Of Material / Perforamance Test Results
2.2.11 Initial Process Studies
2.2.12 Quality Laboratory Documentation
2.2.13 Appearance Approval Report
2.2.14 Sample Production Parts
2.2.15 Master Sample
2.2.16 Checking Aids
2.2.17 Customer Specific Requirements
2.2.18 Parts Submission Warrant
2.2.2 Authorized Engineering Change Documents
2.2.3 Customer Engineering Approval
2.2.4 DFMEA
2.2.5 Process Flow Diagram
2.2.6 PFMEA
2.2.7 Control Plan
2.2.8 Measurement System Analysis
2.2.9 Dimensional Results
2.2.10 Records Of Material / Perforamance Test Results
2.2.11 Initial Process Studies
2.2.12 Quality Laboratory Documentation
2.2.13 Appearance Approval Report
2.2.14 Sample Production Parts
2.2.15 Master Sample
2.2.16 Checking Aids
2.2.17 Customer Specific Requirements
2.2.18 Parts Submission Warrant
Tuesday, March 23, 2010
GLOSSARY OF QUALITY IMPROVEMENT TERMS
Common-Cause Variation: Any normal variation inherent in a work process. (See also Special-Cause Variation.)
Complexity: Unnecessary work; any activity that makes a work process more complicated without adding value to the resulting product or service.
Continuous Improvement Process: The ongoing enhancement of work processes for the benefit of the customer and the organization; activities devoted to maintaining and improving work process performance through small and gradual improvements as well as radical innovations.
Control Chart: A line graph that identifies the variation occurring in a work process over time; helps distinguish between common-cause variation and special-cause variation.
Cost of Quality: A term used by many organizations to quantify the costs associated with producing quality products. Typical factors taken into account are prevention costs (training, work process analyses, design reviews, customer surveys), appraisal costs (inspection and testing), and failure costs (rework, scrap, customer complaints, returns).
Cross Functional: Involving the cooperation of two or more departments within the organization (e.g., Marketing and Product Development).
Customer: Any person or group inside or outside the organization who receives a product or service.
Customer Expectations: The "needs" and "wants" of a customer that define "quality" in a specified product or service.
Deming Cycle (also known as Shewart's Wheel): A model that describes the cyclical interaction of research, sales, design, and production as a continuous work flow, so that all functions are involved constantly in the effort to provide products and services that satisfy customers and contribute to improved quality. (See also PDCA.)
Department Improvement Team: Made up of all members of a department and usually chaired by the manager or supervisor, department improvement teams function as a vehicle for all employees to continuously participate in ongoing quality improvement activities.
Executive Steering Committee (or Executive Improvement Team): Includes top executives and is chaired by the CEO; encourages and participates in a quality initiative by reviewing, approving, and implementing improvement activities.
Fitness-For-Use: Juran's definition of quality suggesting that products and services need to serve customers' needs, instead of meeting internal requirements only.
Improving Steering Council (also known as Quality Steering Committee): A group of people with representation from all functions in the organization, usually drawn from management levels, chartered to develop and monitor a quality improvement process in their own functions. This group is often responsible for deciding which improvement projects or work processes will be addressed and in what priority.
Internal Customer: Anyone in the organization who relies on you for a product or service. (See also Customer.)
Internal Supplier: Anyone in the organization you rely on for a product or service. (See also Supplier.)
Juran Trilogy: The interrelationship of three basic managerial processes with which to manage quality, quality control, and quality improvement.
Just-In-Time (JIT): A method of production and inventory cost control based on delivery of parts and supplies at the precise time they are needed in a production process.
Kaizen: Japanese term meaning continuous improvement involving everyone-managers and employees alike.
Key Expectations: The requirements concerning a specified product or service that a customer holds to be most important.
PDCA Cycle: An adaptation of the Deming Cycle, which stresses that every improvement activity, can best be accomplished by the following steps: plan, do, check, etc. (See Deming Cycle.)
Process Improvement Team: Includes experienced employees from different departments who solve problems and improve work processes that go across-functional lines. (Also known as Service Improvement Team, Quality Improvement Team, or Corrective Action Team.)
Quality: a customer's perception of the value of a product or service; organizations, theorists, and dictionaries define it differently. Well-known definitions include:
"conformance to requirements" (Crosby)
"the efficient production of the quality that the market expects" (Deming)
"fitness for use"; "product performance and freedom from deficiencies" (Juran)
"the total composite product and service characteristics of marketing, engineering, manufacturing, and maintenance through which the product and service in use will meet the expectations of the customer" (Felgenbaum)
"anything that can be improved" (Imal)
"meeting or exceeding customer expectations at a cost that represents value to them" (Harrington)
"does not impart loss to society" (Taguchi)
"the totality of features and characteristics of a product or service that bear on its ability to satisfy a given need" (American Society for Quality Control)
"degree of excellence" (Webster's Third New International Dictionary)
Quality Circle: A small group of employees organized to solve work-related problems; often voluntarily; usually not chaired by a department manager.
Quality Initiative: A formal effort by an organization to improve the quality of its products and services; usually involves top management development of a mission statement and long-term strategy.
Special-Cause Variation: Any violation arising from circumstances that are not a normal part of the work process. (See also Common-Cause Variation.)
Supplier: Any person or group inside or outside the organization that produces a product or service. Suppliers improve quality by identifying customer expectations and adjusting work processes so that products and services meet or exceed those expectations. (See also Customer.)
Task Force: An ad hoc, cross-functional team formed to resolve a major problem as quickly as possible; usually includes subject matter experts temporarily relieved of their regular duties.
Total Quality Control (TQM): A management approach advocating the involvement of all employees in the continuous improvement process-not-just quality control specialists.
Work Partnership: A mutually beneficial work relationship between internal and external customers and suppliers.
Work Process: A series of work steps that produce a particular product or service for the customer.
Zero Defects: An approach to quality based on prevention of errors; often adopted as a standard for performance or a definition of quality (notably in Crosby Quality Training).
Complexity: Unnecessary work; any activity that makes a work process more complicated without adding value to the resulting product or service.
Continuous Improvement Process: The ongoing enhancement of work processes for the benefit of the customer and the organization; activities devoted to maintaining and improving work process performance through small and gradual improvements as well as radical innovations.
Control Chart: A line graph that identifies the variation occurring in a work process over time; helps distinguish between common-cause variation and special-cause variation.
Cost of Quality: A term used by many organizations to quantify the costs associated with producing quality products. Typical factors taken into account are prevention costs (training, work process analyses, design reviews, customer surveys), appraisal costs (inspection and testing), and failure costs (rework, scrap, customer complaints, returns).
Cross Functional: Involving the cooperation of two or more departments within the organization (e.g., Marketing and Product Development).
Customer: Any person or group inside or outside the organization who receives a product or service.
Customer Expectations: The "needs" and "wants" of a customer that define "quality" in a specified product or service.
Deming Cycle (also known as Shewart's Wheel): A model that describes the cyclical interaction of research, sales, design, and production as a continuous work flow, so that all functions are involved constantly in the effort to provide products and services that satisfy customers and contribute to improved quality. (See also PDCA.)
Department Improvement Team: Made up of all members of a department and usually chaired by the manager or supervisor, department improvement teams function as a vehicle for all employees to continuously participate in ongoing quality improvement activities.
Executive Steering Committee (or Executive Improvement Team): Includes top executives and is chaired by the CEO; encourages and participates in a quality initiative by reviewing, approving, and implementing improvement activities.
Fitness-For-Use: Juran's definition of quality suggesting that products and services need to serve customers' needs, instead of meeting internal requirements only.
Improving Steering Council (also known as Quality Steering Committee): A group of people with representation from all functions in the organization, usually drawn from management levels, chartered to develop and monitor a quality improvement process in their own functions. This group is often responsible for deciding which improvement projects or work processes will be addressed and in what priority.
Internal Customer: Anyone in the organization who relies on you for a product or service. (See also Customer.)
Internal Supplier: Anyone in the organization you rely on for a product or service. (See also Supplier.)
Juran Trilogy: The interrelationship of three basic managerial processes with which to manage quality, quality control, and quality improvement.
Just-In-Time (JIT): A method of production and inventory cost control based on delivery of parts and supplies at the precise time they are needed in a production process.
Kaizen: Japanese term meaning continuous improvement involving everyone-managers and employees alike.
Key Expectations: The requirements concerning a specified product or service that a customer holds to be most important.
PDCA Cycle: An adaptation of the Deming Cycle, which stresses that every improvement activity, can best be accomplished by the following steps: plan, do, check, etc. (See Deming Cycle.)
Process Improvement Team: Includes experienced employees from different departments who solve problems and improve work processes that go across-functional lines. (Also known as Service Improvement Team, Quality Improvement Team, or Corrective Action Team.)
Quality: a customer's perception of the value of a product or service; organizations, theorists, and dictionaries define it differently. Well-known definitions include:
"conformance to requirements" (Crosby)
"the efficient production of the quality that the market expects" (Deming)
"fitness for use"; "product performance and freedom from deficiencies" (Juran)
"the total composite product and service characteristics of marketing, engineering, manufacturing, and maintenance through which the product and service in use will meet the expectations of the customer" (Felgenbaum)
"anything that can be improved" (Imal)
"meeting or exceeding customer expectations at a cost that represents value to them" (Harrington)
"does not impart loss to society" (Taguchi)
"the totality of features and characteristics of a product or service that bear on its ability to satisfy a given need" (American Society for Quality Control)
"degree of excellence" (Webster's Third New International Dictionary)
Quality Circle: A small group of employees organized to solve work-related problems; often voluntarily; usually not chaired by a department manager.
Quality Initiative: A formal effort by an organization to improve the quality of its products and services; usually involves top management development of a mission statement and long-term strategy.
Special-Cause Variation: Any violation arising from circumstances that are not a normal part of the work process. (See also Common-Cause Variation.)
Supplier: Any person or group inside or outside the organization that produces a product or service. Suppliers improve quality by identifying customer expectations and adjusting work processes so that products and services meet or exceed those expectations. (See also Customer.)
Task Force: An ad hoc, cross-functional team formed to resolve a major problem as quickly as possible; usually includes subject matter experts temporarily relieved of their regular duties.
Total Quality Control (TQM): A management approach advocating the involvement of all employees in the continuous improvement process-not-just quality control specialists.
Work Partnership: A mutually beneficial work relationship between internal and external customers and suppliers.
Work Process: A series of work steps that produce a particular product or service for the customer.
Zero Defects: An approach to quality based on prevention of errors; often adopted as a standard for performance or a definition of quality (notably in Crosby Quality Training).
Saturday, March 20, 2010
101 Things A Six Sigma Black Belt Should Know By Thomas Pyzdek
1. In general, a Six Sigma Black Belt should be quantitatively oriented.
2. With minimal guidance, the Six Sigma Black Belt should be able to use data to convert broad generalizations into actionable goals.
3. The Six Sigma Black Belt should be able to make the business case for attempting to accomplish these goals.
4. The Six Sigma Black Belt should be able to develop detailed plans for achieving these goals.
5. The Six Sigma Black Belt should be able to measure progress towards the goals in terms meaningful to customers and leaders.
6. The Six Sigma Black Belt should know how to establish control systems for maintaining the gains achieved through Six Sigma.
7. The Six Sigma Black Belt should understand and be able to communicate the rationale for continuous improvement, even after initial goals have been accomplished.
8. The Six Sigma Black Belt should be familiar with research that quantifies the benefits firms have obtained from Six Sigma.
9. The Six Sigma Black Belt should know or be able to find the PPM rates associated with different sigma levels (e.g., Six Sigma = 3.4 PPM)
10. The Six Sigma Black Belt should know the approximate relative cost of poor quality associated with various sigma levels (e.g., three sigma firms report 25% COPQ).
11. The Six Sigma Black Belt should understand the roles of the various people involved in change (senior leader, champion, mentor, change agent, technical leader, team leader, facilitator).
12. The Six Sigma Black Belt should be able to design, test, and analyze customer surveys.
13. The Six Sigma Black Belt should know how to quantitatively analyze data from employee and customer surveys. This includes evaluating survey reliability and validity as well as the differences between surveys.
14. Given two or more sets of survey data, the Six Sigma Black Belt should be able to determine if there are statistically significant differences between them.
15. The Six Sigma Black Belt should be able to quantify the value of customer retention.
16. Given a partly completed QFD matrix, the Six Sigma Black Belt should be able to complete it.
17. The Six Sigma Black Belt should be able to compute the value of money held or invested over time, including present value and future value of a fixed sum.
18. The Six Sigma Black Belt should be able to compute present value and future value for various compounding periods.
19. The Six Sigma Black Belt should be able to compute the break even point for a project.
20. The Six Sigma Black Belt should be able to compute the net present value of cash flow streams, and to use the results to choose among competing projects.
21. The Six Sigma Black Belt should be able to compute the internal rate of return for cash flow streams and to use the results to choose among competing projects.
22. The Six Sigma Black Belt should know the COPQ rationale for Six Sigma, i.e., he should be able to explain what to do if COPQ analysis indicates that the optimum for a given process is less than Six Sigma.
23. The Six Sigma Black Belt should know the basic COPQ categories and be able to allocate a list of costs to the correct category.
24. Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the trend.
25. Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the distribution of costs among the various categories.
26. Given a list of tasks for a project, their times to complete, and their precedence relationships, the Six Sigma Black Belt should be able to compute the time to completion for the project, the earliest completion times, the latest completion times and the slack times. He should also be able to identify which tasks are on the critical path.
27. Give cost and time data for project tasks, the Six Sigma Black Belt should be able to compute the cost of normal and crash schedules and the minimum total cost schedule.
28. The Six Sigma Black Belt should be familiar with the basic principles of benchmarking.
29. The Six Sigma Black Belt should be familiar with the limitations of benchmarking.
30. Given an organization chart and a listing of team members, process owners, and sponsors, the Six Sigma Black Belt should be able to identify projects with a low probability of success.
31. The Six Sigma Black Belt should be able to identify measurement scales of various metrics (nominal, ordinal, etc).
32. Given a metric on a particular scale, the Six Sigma Black Belt should be able to determine if a particular statistical method should be used for analysis.
33. Given a properly collected set of data, the Six Sigma Black Belt should be able to perform a complete measurement system analysis, including the calculation of bias, repeatability, reproducibility, stability, discrimination (resolution) and linearity.
34. Given the measurement system metrics, the Six Sigma Black Belt should know whether or not a given measurement system should be used on a given part or process.
35. The Six Sigma Black Belt should know the difference between computing sigma from a data set whose production sequence is known and from a data set whose production sequence is not known.
36. Given the results of an AIAG Gage R&R study, the Six Sigma Black Belt should be able to answer a variety of questions about the measurement system.
37. Given a narrative description of "as-is" and "should-be" processes, the Six Sigma Black Belt should be able to prepare process maps.
38. Given a table of raw data, the Six Sigma Black Belt should be able to prepare a frequency tally sheet of the data, and to use the tally sheet data to construct a histogram.
39. The Six Sigma Black Belt should be able to compute the mean and standard deviation from a grouped frequency distribution.
40. Given a list of problems, the Six Sigma Black Belt should be able to construct a Pareto Diagram of the problem frequencies.
41. Given a list which describes problems by department, the Six Sigma Black Belt should be able to construct a Crosstabulation and use the information to perform a Chi-square analysis.
42. Given a table of x and y data pairs, the Six Sigma Black Belt should be able to determine if the relationship is linear or non-linear.
43. The Six Sigma Black Belt should know how to use non-linearity's to make products or processes more robust.
44. The Six Sigma Black Belt should be able to construct and interpret a run chart when given a table of data in time-ordered sequence. This includes calculating run length, number of runs and quantitative trend evaluation.
45. When told the data are from an exponential or Erlang distribution the Six Sigma Black Belt should know that the run chart is preferred over the standard X control chart.
46. Given a set of raw data the Six Sigma Black Belt should be able to identify and compute two statistical measures each for central tendency, dispersion, and shape.
47. Given a set of raw data, the Six Sigma Black Belt should be able to construct a histogram.
48. Given a stem & leaf plot, the Six Sigma Black Belt should be able to reproduce a sample of numbers to the accuracy allowed by the plot.
49. Given a box plot with numbers on the key box points, the Six Sigma Black Belt should be able to identify the 25th and 75th percentile and the median.
50. The Six Sigma Black Belt should know when to apply enumerative statistical methods, and when not to.
51. The Six Sigma Black Belt should know when to apply analytic statistical methods, and when not to.
52. The Six Sigma Black Belt should demonstrate a grasp of basic probability concepts, such as the probability of mutually exclusive events, of dependent and independent events, of events that can occur simultaneously, etc.
53. The Six Sigma Black Belt should know factorials, permutations and combinations, and how to use these in commonly used probability distributions.
54. The Six Sigma Black Belt should be able to compute expected values for continuous and discrete random variables.
55. The Six Sigma Black Belt should be able to compute univariate statistics for samples.
56. The Six Sigma Black Belt should be able to compute confidence intervals for various statistics.
57. The Six Sigma Black Belt should be able to read values from a cumulative frequency ogive.
58. The Six Sigma Black Belt should be familiar with the commonly used probability distributions, including: hypergeometric, binomial, Poisson, normal, exponential, chi-square, Student's t, and F.
59. Given a set of data the Six Sigma Black Belt should be able to correctly identify which distribution should be used to perform a given analysis, and to use the distribution to perform the analysis.
60. The Six Sigma Black Belt should know that different techniques are required for analysis depending on whether a given measure (e.g., the mean) is assumed known or estimated from a sample. The Six Sigma Black Belt should choose and properly use the correct technique when provided with data and sufficient information about the data.
61. Given a set of subgrouped data, the Six Sigma Black Belt should be able to select and prepare the correct control charts and to determine if a given process is in a state of statistical control.
62. The above should be demonstrated for data representing all of the most common control charts.
63. The Six Sigma Black Belt should understand the assumptions that underlie ANOVA, and be able to select and apply a transformation to the data.
64. The Six Sigma Black Belt should be able to identify which cause on a list of possible causes will most likely explain a non-random pattern in the regression residuals.
65. If shown control chart patterns, the Six Sigma Black Belt should be able to match the control chart with the correct situation (e.g., an outlier pattern vs. a gradual trend matched to a tool breaking vs. a machine gradually warming up).
66. The Six Sigma Black Belt should understand the mechanics of PRE-Control.
67. The Six Sigma Black Belt should be able to correctly apply EWMA charts to a process with serial correlation in the data.
68. Given a stable set of subgrouped data, the Six Sigma Black Belt should be able to perform a complete Process Capability Analysis. This includes computing and interpreting capability indices, estimating the % failures, control limit calculations, etc.
69. The Six Sigma Black Belt should demonstrate an awareness of the assumptions that underlie the use of capability indices.
70. Given the results of a replicated 22 full-factorial experiment, the Six Sigma Black Belt should be able to complete the entire ANOVA table.
71. The Six Sigma Black Belt should understand the basic principles of planning a statistically designed experiment. This can be demonstrated by critiquing various experimental plans with or without shortcomings.
72. Given a "clean" experimental plan, the Six Sigma Black Belt should be able to find the correct number of replicates to obtain a desired power.
73. The Six Sigma Black Belt should know the difference between the various types of experimental models (fixed-effects, random-effects, mixed).
74. The Six Sigma Black Belt should understand the concepts of randomization and blocking.
75. Given a set of data, the Six Sigma Black Belt should be able to perform a Latin Square analysis and interpret the results.
76. Ditto for one way ANOVA, two way ANOVA (with and without replicates), full and fractional factorials, and response surface designs.
77. Given an appropriate experimental result, the Six Sigma Black Belt should be able to compute the direction of steepest ascent.
78. Given a set of variables each at two levels, the Six Sigma Black Belt can determine the correct experimental layout for a screening experiment using a saturated design.
79. Given data for such an experiment, the Six Sigma Black Belt can identify which main effects are significant and state the effect of these factors.
80. Given two or more sets of responses to categorical items (e.g., customer survey responses categorized as poor, fair, good, excellent), the Six Sigma Black Belt will be able to perform a Chi-Square test to determine if the samples are significantly different.
81. The Six Sigma Black Belt will understand the idea of confounding and be able to identify which two factor interactions are confounded with the significant main effects.
82. The Six Sigma Black Belt will be able to state the direction of steepest ascent from experimental data.
83. The Six Sigma Black Belt will understand fold over designs and be able to identify the fold over design that will clear a given alias.
84. The Six Sigma Black Belt will know how to augment a factorial design to create a composite or central composite design.
85. The Six Sigma Black Belt will be able to evaluate the diagnostics for an experiment.
86. The Six Sigma Black Belt will be able to identify the need for a transformation in y and to apply the correct transformation.
87. Given a response surface equation in quadratic form, the Six Sigma Black Belt will be able to compute the stationary point.
88. Given data (not graphics), the Six Sigma Black Belt will be able to determine if the stationary point is a maximum, minimum or saddle point.
89. The Six Sigma Black Belt will be able to use a quadratic loss function to compute the cost of a given process.
90. The Six Sigma Black Belt will be able to conduct simple and multiple linear regression.
91. The Six Sigma Black Belt will be able to identify patterns in residuals from an improper regression model and to apply the correct remedy.
92. The Six Sigma Black Belt will understand the difference between regression and correlation studies.
93. The Six Sigma Black Belt will be able to perform chi-square analysis of contingency tables.
94. The Six Sigma Black Belt will be able to compute basic reliability statistics (mtbf, availability, etc.).
95. Given the failure rates for given subsystems, the Six Sigma Black Belt will be able to use reliability apportionment to set mtbf goals.
96. The Six Sigma Black Belt will be able to compute the reliability of series, parallel, and series-parallel system configurations.
97. The Six Sigma Black Belt will demonstrate the ability to create and read an FMEA analysis.
98. The Six Sigma Black Belt will demonstrate the ability to create and read a fault tree.
99. Given distributions of strength and stress, the Six Sigma Black Belt will be able to compute the probability of failure.
100. The Six Sigma Black Belt will be able to apply statistical tolerancing to set tolerances for simple assemblies. He will know how to compare statistical tolerances to so-called "worst case" tolerancing.
101. The Six Sigma Black Belt will be aware of the limits of the Six Sigma approach.
Project Requirements:
Final project submissions should include documentation to show mastery of the following body of knowledge:
Process Step Requirement
Project Results Summary statement of project results tying metric performance back to the Charter statement mission.
Prioritize and Define Project Charter (Mandatory)
Thought Process Map (Mandatory)
S-I-P-O-C Process Flow Chart (Mandatory)
Pareto Chart (Mandatory)
Gantt Chart (Mandatory)
CTQC Tree Diagram (Mandatory)
CTQC's Identified with Operational Definition (Mandatory)
Measure Measurement System Analysis (Mandatory)
Trend Chart (Mandatory)
Defect Opportunities Defined (Mandatory)
DPMO Baseline and Sigma Level (Mandatory)
Histogram (Mandatory)
Statistical Process Control (Mandatory)
Capability Analysis (Mandatory)
Analyze Any FOUR of the following tools:
Cause & Effect Diagram
5-Why, 1-How Analysis
FMEA - Failure Mode and Effects Analysis
Regression & Correlation Analysis
One-Way Anova
Hypothesis Testing (Mandatory)
Design of Experiments (Mandatory):
Full or Fractional Factorial Design
Improve Any FOUR of the following tools:
Brainstorming
Error-Proofing
System Dynamics
Solution Selection Matrix
Corrective Action Matrix
Piloting Changes
Control Any THREE of the following tools:
Control Plan
SPC
5-S
Total Productive Maintenance
Best Practices - Improvement Integration
Black Belt Course Content and Outline
Introduction:
What is Six Sigma? Input/Output (X and Y) Relationship
Defects Per Million Opportunities Metric (DPMO)
Success Stories
Six Sigma History
D-M-A-I-C Process
Thought Process Mapping
Six Sigma Organizational Structure
Role of the Black Belt
Six Sigma and Lean Enterprise
Exercises and Quiz
Define I - Prioritize:
Process Thinking
Process Mapping
Flow Charts, Value-Added Flow Charts
Balanced Scorecard
Pareto Chart
Project Selection
Project Charter
Project Tracking - Gantt Chart
Stakeholder Analysis
Exercises and Quiz
Define II - Voice of the Customer:
Customer Satisfaction & Kano Model
Sample Surveys
Survey Construction
Margin of Error
Affinity Diagrams
CTQC Tree Diagrams, Critical to Quality Characteristics (CTQC's)
Setting Specifications
Quality Function Deployment
Operational Definition
Exercises and Quiz
Measure I:
Variable and Attribute Data
Sampling Plan
Measurement System Analysis
Data Collection - Check Sheet
Benchmarking
Baseline DPMO & Sigma Conversion
Rolled Throughput Yield
Exercises and Quiz
Measure II:
Trend Chart
Histograms
Measuring Process Variability
Statistical Process Control
Rational Subgrouping
X and Moving Range Control Charts
Attribute Control Charts
X-bar and R Control Charts
Process Capability
Exercises and Quiz
Analyze I - Potential Root Cause
Cause and Effect Diagrams (Fishbone Charts)
Five-Why, One-How
FMEA
Scatter Plots
Regression and Correlation Analysis
Multiple Regression
Logistic Regression
Exercises and Quiz
Analyze II - Hypothesis Testing
Introduction to Hypothesis Testing
Confidence Intervals and Hypothesis Testing
Comparison of Two Treatments: Z-test, F-Test, t-test
Comparison of Multiple Treatments - ANOVA, Chi-Square for Multiple Proportions
Comparison of Variances - Chi-Square Test
Hy-Court TV TM Learning Lab
Exercises and Quiz
Analyze III - Design of Experiments
Introduction to Design of Experiments
Single Factor Experiments
Full Factorial Experiments
Fractional Factorial Experiments
Experiment Simulations
Advanced Topics
Exercises and Quiz
Improve
Design for Manufacturability/Serviceability/Repairability (DFSS)
Brainstorming
Narrowing the List of Ideas
FMEA
Error-proofing
Corrective Action Matrix
Piloting a Solution
System Dynamics
Exercises and Quiz
Control:
Control Plan
SPC Revisited
FMEA Revisited
Visual Control - 5-S
CHECK Process
Total Productive Maintenance
Best Practices - Integrating Success
Exercises and Quiz
Tools for Success
Leadership
Team Development
Leading Teams
Leading Change
Exercises and Quiz
2. With minimal guidance, the Six Sigma Black Belt should be able to use data to convert broad generalizations into actionable goals.
3. The Six Sigma Black Belt should be able to make the business case for attempting to accomplish these goals.
4. The Six Sigma Black Belt should be able to develop detailed plans for achieving these goals.
5. The Six Sigma Black Belt should be able to measure progress towards the goals in terms meaningful to customers and leaders.
6. The Six Sigma Black Belt should know how to establish control systems for maintaining the gains achieved through Six Sigma.
7. The Six Sigma Black Belt should understand and be able to communicate the rationale for continuous improvement, even after initial goals have been accomplished.
8. The Six Sigma Black Belt should be familiar with research that quantifies the benefits firms have obtained from Six Sigma.
9. The Six Sigma Black Belt should know or be able to find the PPM rates associated with different sigma levels (e.g., Six Sigma = 3.4 PPM)
10. The Six Sigma Black Belt should know the approximate relative cost of poor quality associated with various sigma levels (e.g., three sigma firms report 25% COPQ).
11. The Six Sigma Black Belt should understand the roles of the various people involved in change (senior leader, champion, mentor, change agent, technical leader, team leader, facilitator).
12. The Six Sigma Black Belt should be able to design, test, and analyze customer surveys.
13. The Six Sigma Black Belt should know how to quantitatively analyze data from employee and customer surveys. This includes evaluating survey reliability and validity as well as the differences between surveys.
14. Given two or more sets of survey data, the Six Sigma Black Belt should be able to determine if there are statistically significant differences between them.
15. The Six Sigma Black Belt should be able to quantify the value of customer retention.
16. Given a partly completed QFD matrix, the Six Sigma Black Belt should be able to complete it.
17. The Six Sigma Black Belt should be able to compute the value of money held or invested over time, including present value and future value of a fixed sum.
18. The Six Sigma Black Belt should be able to compute present value and future value for various compounding periods.
19. The Six Sigma Black Belt should be able to compute the break even point for a project.
20. The Six Sigma Black Belt should be able to compute the net present value of cash flow streams, and to use the results to choose among competing projects.
21. The Six Sigma Black Belt should be able to compute the internal rate of return for cash flow streams and to use the results to choose among competing projects.
22. The Six Sigma Black Belt should know the COPQ rationale for Six Sigma, i.e., he should be able to explain what to do if COPQ analysis indicates that the optimum for a given process is less than Six Sigma.
23. The Six Sigma Black Belt should know the basic COPQ categories and be able to allocate a list of costs to the correct category.
24. Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the trend.
25. Given a table of COPQ data over time, the Six Sigma Black Belt should be able to perform a statistical analysis of the distribution of costs among the various categories.
26. Given a list of tasks for a project, their times to complete, and their precedence relationships, the Six Sigma Black Belt should be able to compute the time to completion for the project, the earliest completion times, the latest completion times and the slack times. He should also be able to identify which tasks are on the critical path.
27. Give cost and time data for project tasks, the Six Sigma Black Belt should be able to compute the cost of normal and crash schedules and the minimum total cost schedule.
28. The Six Sigma Black Belt should be familiar with the basic principles of benchmarking.
29. The Six Sigma Black Belt should be familiar with the limitations of benchmarking.
30. Given an organization chart and a listing of team members, process owners, and sponsors, the Six Sigma Black Belt should be able to identify projects with a low probability of success.
31. The Six Sigma Black Belt should be able to identify measurement scales of various metrics (nominal, ordinal, etc).
32. Given a metric on a particular scale, the Six Sigma Black Belt should be able to determine if a particular statistical method should be used for analysis.
33. Given a properly collected set of data, the Six Sigma Black Belt should be able to perform a complete measurement system analysis, including the calculation of bias, repeatability, reproducibility, stability, discrimination (resolution) and linearity.
34. Given the measurement system metrics, the Six Sigma Black Belt should know whether or not a given measurement system should be used on a given part or process.
35. The Six Sigma Black Belt should know the difference between computing sigma from a data set whose production sequence is known and from a data set whose production sequence is not known.
36. Given the results of an AIAG Gage R&R study, the Six Sigma Black Belt should be able to answer a variety of questions about the measurement system.
37. Given a narrative description of "as-is" and "should-be" processes, the Six Sigma Black Belt should be able to prepare process maps.
38. Given a table of raw data, the Six Sigma Black Belt should be able to prepare a frequency tally sheet of the data, and to use the tally sheet data to construct a histogram.
39. The Six Sigma Black Belt should be able to compute the mean and standard deviation from a grouped frequency distribution.
40. Given a list of problems, the Six Sigma Black Belt should be able to construct a Pareto Diagram of the problem frequencies.
41. Given a list which describes problems by department, the Six Sigma Black Belt should be able to construct a Crosstabulation and use the information to perform a Chi-square analysis.
42. Given a table of x and y data pairs, the Six Sigma Black Belt should be able to determine if the relationship is linear or non-linear.
43. The Six Sigma Black Belt should know how to use non-linearity's to make products or processes more robust.
44. The Six Sigma Black Belt should be able to construct and interpret a run chart when given a table of data in time-ordered sequence. This includes calculating run length, number of runs and quantitative trend evaluation.
45. When told the data are from an exponential or Erlang distribution the Six Sigma Black Belt should know that the run chart is preferred over the standard X control chart.
46. Given a set of raw data the Six Sigma Black Belt should be able to identify and compute two statistical measures each for central tendency, dispersion, and shape.
47. Given a set of raw data, the Six Sigma Black Belt should be able to construct a histogram.
48. Given a stem & leaf plot, the Six Sigma Black Belt should be able to reproduce a sample of numbers to the accuracy allowed by the plot.
49. Given a box plot with numbers on the key box points, the Six Sigma Black Belt should be able to identify the 25th and 75th percentile and the median.
50. The Six Sigma Black Belt should know when to apply enumerative statistical methods, and when not to.
51. The Six Sigma Black Belt should know when to apply analytic statistical methods, and when not to.
52. The Six Sigma Black Belt should demonstrate a grasp of basic probability concepts, such as the probability of mutually exclusive events, of dependent and independent events, of events that can occur simultaneously, etc.
53. The Six Sigma Black Belt should know factorials, permutations and combinations, and how to use these in commonly used probability distributions.
54. The Six Sigma Black Belt should be able to compute expected values for continuous and discrete random variables.
55. The Six Sigma Black Belt should be able to compute univariate statistics for samples.
56. The Six Sigma Black Belt should be able to compute confidence intervals for various statistics.
57. The Six Sigma Black Belt should be able to read values from a cumulative frequency ogive.
58. The Six Sigma Black Belt should be familiar with the commonly used probability distributions, including: hypergeometric, binomial, Poisson, normal, exponential, chi-square, Student's t, and F.
59. Given a set of data the Six Sigma Black Belt should be able to correctly identify which distribution should be used to perform a given analysis, and to use the distribution to perform the analysis.
60. The Six Sigma Black Belt should know that different techniques are required for analysis depending on whether a given measure (e.g., the mean) is assumed known or estimated from a sample. The Six Sigma Black Belt should choose and properly use the correct technique when provided with data and sufficient information about the data.
61. Given a set of subgrouped data, the Six Sigma Black Belt should be able to select and prepare the correct control charts and to determine if a given process is in a state of statistical control.
62. The above should be demonstrated for data representing all of the most common control charts.
63. The Six Sigma Black Belt should understand the assumptions that underlie ANOVA, and be able to select and apply a transformation to the data.
64. The Six Sigma Black Belt should be able to identify which cause on a list of possible causes will most likely explain a non-random pattern in the regression residuals.
65. If shown control chart patterns, the Six Sigma Black Belt should be able to match the control chart with the correct situation (e.g., an outlier pattern vs. a gradual trend matched to a tool breaking vs. a machine gradually warming up).
66. The Six Sigma Black Belt should understand the mechanics of PRE-Control.
67. The Six Sigma Black Belt should be able to correctly apply EWMA charts to a process with serial correlation in the data.
68. Given a stable set of subgrouped data, the Six Sigma Black Belt should be able to perform a complete Process Capability Analysis. This includes computing and interpreting capability indices, estimating the % failures, control limit calculations, etc.
69. The Six Sigma Black Belt should demonstrate an awareness of the assumptions that underlie the use of capability indices.
70. Given the results of a replicated 22 full-factorial experiment, the Six Sigma Black Belt should be able to complete the entire ANOVA table.
71. The Six Sigma Black Belt should understand the basic principles of planning a statistically designed experiment. This can be demonstrated by critiquing various experimental plans with or without shortcomings.
72. Given a "clean" experimental plan, the Six Sigma Black Belt should be able to find the correct number of replicates to obtain a desired power.
73. The Six Sigma Black Belt should know the difference between the various types of experimental models (fixed-effects, random-effects, mixed).
74. The Six Sigma Black Belt should understand the concepts of randomization and blocking.
75. Given a set of data, the Six Sigma Black Belt should be able to perform a Latin Square analysis and interpret the results.
76. Ditto for one way ANOVA, two way ANOVA (with and without replicates), full and fractional factorials, and response surface designs.
77. Given an appropriate experimental result, the Six Sigma Black Belt should be able to compute the direction of steepest ascent.
78. Given a set of variables each at two levels, the Six Sigma Black Belt can determine the correct experimental layout for a screening experiment using a saturated design.
79. Given data for such an experiment, the Six Sigma Black Belt can identify which main effects are significant and state the effect of these factors.
80. Given two or more sets of responses to categorical items (e.g., customer survey responses categorized as poor, fair, good, excellent), the Six Sigma Black Belt will be able to perform a Chi-Square test to determine if the samples are significantly different.
81. The Six Sigma Black Belt will understand the idea of confounding and be able to identify which two factor interactions are confounded with the significant main effects.
82. The Six Sigma Black Belt will be able to state the direction of steepest ascent from experimental data.
83. The Six Sigma Black Belt will understand fold over designs and be able to identify the fold over design that will clear a given alias.
84. The Six Sigma Black Belt will know how to augment a factorial design to create a composite or central composite design.
85. The Six Sigma Black Belt will be able to evaluate the diagnostics for an experiment.
86. The Six Sigma Black Belt will be able to identify the need for a transformation in y and to apply the correct transformation.
87. Given a response surface equation in quadratic form, the Six Sigma Black Belt will be able to compute the stationary point.
88. Given data (not graphics), the Six Sigma Black Belt will be able to determine if the stationary point is a maximum, minimum or saddle point.
89. The Six Sigma Black Belt will be able to use a quadratic loss function to compute the cost of a given process.
90. The Six Sigma Black Belt will be able to conduct simple and multiple linear regression.
91. The Six Sigma Black Belt will be able to identify patterns in residuals from an improper regression model and to apply the correct remedy.
92. The Six Sigma Black Belt will understand the difference between regression and correlation studies.
93. The Six Sigma Black Belt will be able to perform chi-square analysis of contingency tables.
94. The Six Sigma Black Belt will be able to compute basic reliability statistics (mtbf, availability, etc.).
95. Given the failure rates for given subsystems, the Six Sigma Black Belt will be able to use reliability apportionment to set mtbf goals.
96. The Six Sigma Black Belt will be able to compute the reliability of series, parallel, and series-parallel system configurations.
97. The Six Sigma Black Belt will demonstrate the ability to create and read an FMEA analysis.
98. The Six Sigma Black Belt will demonstrate the ability to create and read a fault tree.
99. Given distributions of strength and stress, the Six Sigma Black Belt will be able to compute the probability of failure.
100. The Six Sigma Black Belt will be able to apply statistical tolerancing to set tolerances for simple assemblies. He will know how to compare statistical tolerances to so-called "worst case" tolerancing.
101. The Six Sigma Black Belt will be aware of the limits of the Six Sigma approach.
Project Requirements:
Final project submissions should include documentation to show mastery of the following body of knowledge:
Process Step Requirement
Project Results Summary statement of project results tying metric performance back to the Charter statement mission.
Prioritize and Define Project Charter (Mandatory)
Thought Process Map (Mandatory)
S-I-P-O-C Process Flow Chart (Mandatory)
Pareto Chart (Mandatory)
Gantt Chart (Mandatory)
CTQC Tree Diagram (Mandatory)
CTQC's Identified with Operational Definition (Mandatory)
Measure Measurement System Analysis (Mandatory)
Trend Chart (Mandatory)
Defect Opportunities Defined (Mandatory)
DPMO Baseline and Sigma Level (Mandatory)
Histogram (Mandatory)
Statistical Process Control (Mandatory)
Capability Analysis (Mandatory)
Analyze Any FOUR of the following tools:
Cause & Effect Diagram
5-Why, 1-How Analysis
FMEA - Failure Mode and Effects Analysis
Regression & Correlation Analysis
One-Way Anova
Hypothesis Testing (Mandatory)
Design of Experiments (Mandatory):
Full or Fractional Factorial Design
Improve Any FOUR of the following tools:
Brainstorming
Error-Proofing
System Dynamics
Solution Selection Matrix
Corrective Action Matrix
Piloting Changes
Control Any THREE of the following tools:
Control Plan
SPC
5-S
Total Productive Maintenance
Best Practices - Improvement Integration
Black Belt Course Content and Outline
Introduction:
What is Six Sigma? Input/Output (X and Y) Relationship
Defects Per Million Opportunities Metric (DPMO)
Success Stories
Six Sigma History
D-M-A-I-C Process
Thought Process Mapping
Six Sigma Organizational Structure
Role of the Black Belt
Six Sigma and Lean Enterprise
Exercises and Quiz
Define I - Prioritize:
Process Thinking
Process Mapping
Flow Charts, Value-Added Flow Charts
Balanced Scorecard
Pareto Chart
Project Selection
Project Charter
Project Tracking - Gantt Chart
Stakeholder Analysis
Exercises and Quiz
Define II - Voice of the Customer:
Customer Satisfaction & Kano Model
Sample Surveys
Survey Construction
Margin of Error
Affinity Diagrams
CTQC Tree Diagrams, Critical to Quality Characteristics (CTQC's)
Setting Specifications
Quality Function Deployment
Operational Definition
Exercises and Quiz
Measure I:
Variable and Attribute Data
Sampling Plan
Measurement System Analysis
Data Collection - Check Sheet
Benchmarking
Baseline DPMO & Sigma Conversion
Rolled Throughput Yield
Exercises and Quiz
Measure II:
Trend Chart
Histograms
Measuring Process Variability
Statistical Process Control
Rational Subgrouping
X and Moving Range Control Charts
Attribute Control Charts
X-bar and R Control Charts
Process Capability
Exercises and Quiz
Analyze I - Potential Root Cause
Cause and Effect Diagrams (Fishbone Charts)
Five-Why, One-How
FMEA
Scatter Plots
Regression and Correlation Analysis
Multiple Regression
Logistic Regression
Exercises and Quiz
Analyze II - Hypothesis Testing
Introduction to Hypothesis Testing
Confidence Intervals and Hypothesis Testing
Comparison of Two Treatments: Z-test, F-Test, t-test
Comparison of Multiple Treatments - ANOVA, Chi-Square for Multiple Proportions
Comparison of Variances - Chi-Square Test
Hy-Court TV TM Learning Lab
Exercises and Quiz
Analyze III - Design of Experiments
Introduction to Design of Experiments
Single Factor Experiments
Full Factorial Experiments
Fractional Factorial Experiments
Experiment Simulations
Advanced Topics
Exercises and Quiz
Improve
Design for Manufacturability/Serviceability/Repairability (DFSS)
Brainstorming
Narrowing the List of Ideas
FMEA
Error-proofing
Corrective Action Matrix
Piloting a Solution
System Dynamics
Exercises and Quiz
Control:
Control Plan
SPC Revisited
FMEA Revisited
Visual Control - 5-S
CHECK Process
Total Productive Maintenance
Best Practices - Integrating Success
Exercises and Quiz
Tools for Success
Leadership
Team Development
Leading Teams
Leading Change
Exercises and Quiz
Friday, March 19, 2010
7 Steps to World Class Manufacturing
What does it mean to be a world-class Manufacturer?
It means being successful in your chosen market against any competition—regardless of size, country of origin or resources.
What does it mean to be a world-class Manufacturer?
It means matching or exceeding any competitor on
•Quality
•Innovation
•Lead-time
•Flexibility
•Cost
•Customer service
What does it mean to be a world-class Manufacturer?
It means you are in control and your competitors struggle to emulate your success.
What does it mean to be a world-class Manufacturer?
You are in in control—
·In control of your markets and customers
·In control of your processes &
·In control of your resources
Being in control doesn’t necessarily mean you make all the decisions, but it does mean you are prepared and will not be thrown by unexpected changes in demand, technology,circumstance or competition.
7 steps to world class Manufacturing
1. Focus on ‘Competitive Quality’
2. Implement Lean manufacturing
3. Achieve cost efficiency
4. Reduce Time-to-Market
5. Exceed Customer Expectations
6. Streamline Outsourcing Processes
7. Have a global perspective
1. Focus on ‘Competitive Quality’
Today’s dynamic and turbulent business environment has shifted the focus of the organizations from “Quality” to “Competitive quality”.With ever changing customer requirements, quality is no more a competitive weapon. Every organization has quality today.What separates a world class organization from others is -how better you are from the rest of your competitors. Everybody in the organization must think and demonstrate that they can do better.The need of the hour is to constantly challenge the status-quoand develop a constructive level of dissatisfaction with the present performance
2. Implement Lean Manufacturing systems
Lean manufacturing is an overall methodology that seeks to minimize the resources required for production by eliminating waste (non-value added activities) that inflate costs, lead times and inventory requirements, and emphasizing the use of preventive maintenance , quality improvement programs, pull systems and flexible work forces and production facilities. Principles of lean include zero waiting time, zero inventory, scheduling (internal customer pull instead of push system), batch to flow (cut batch sizes), line balancing and cutting actual process times.
3. Achieve cost efficiency
Although recent developments in planning and customer relationship management have focused more on top-line benefits (increased revenue), the bottom line is still greatly dependent on controlling costs. Companies with a lower operational cost structure enjoy an obvious advantage in profitability and the ability to adjust pricing to meet competitive pressures if necessary to maintain or gain market share. Costs are really just part of the scoreboard. When a company implements world-class operational processes, it improves multiple measurements simultaneously,including cost, lead times,inventory and customer service.
4. Reduce Time-to-Market
Customers now penalize suppliers that infringe on their time,
whether through delays, mistakes or inconveniences. Today’s
customers demand operations that are airborne, on-line and real-
time. Soon is not the answer the customers want to hear. They count the speed of response time as a Key Value Dimension.
Good ideas are not enough; well-managed processes for bringing
new products to market faster than the competitors can lead to
significant competitive advantages. Bringing products faster into
the market does represent some element of risk, which can be
properly evaluated.
Risk Analysis
Risk Management
Creativity & innovation
Time based competition
New product development
SCAMPER
Ten commandments of time
Niche Marketing
5. Exceed Customer Expectations
The ultimate key to success in any business enterprise is to please your customers. The most successful companies don’t just meet customer expectations, they exceed them and beat the competitionby setting the standards at a level that makes it difficult, if not impossible, for others to surpass.
6. Streamline Outsourcing ProcessesPrinciples
Outsourcing of manufacturing operations is a common practice today because it offers flexibility—the ability to change products or processes rapidly—and can often save money by exploiting economies of scale or other favorable cost factors the contractor has to offer. For manufacturers, the fastest and easiest way to achieve this goal is through partnershipswith companies that have attained superior capabilities in particular phases of the process-like production. By partnering with world-class contract manufacturers you can reap the benefits almost immediately—well-managed processes, high quality, on time deliveries—and increase your performance and deliver to meet your customer’s expectations.At the same time time you can focus your own resources on things that you do best-product innovation,design,marketing,distribution sales or manufacturing.
7. Have a Global perspective
There’s no question the world is shrinking, and virtually every business is now involved in some form of international trade—whether marketing and selling to customers in other countries or simply using parts or materials that are produced elsewhere. Customers today are looking for world class products. The companies wanting to become world class manufacturing must follow the international standards in quality. One of the best framework to follow in this regard is The Shingo Prizewhich is awarded to companies who have attained manufacturing excellence.
It means being successful in your chosen market against any competition—regardless of size, country of origin or resources.
What does it mean to be a world-class Manufacturer?
It means matching or exceeding any competitor on
•Quality
•Innovation
•Lead-time
•Flexibility
•Cost
•Customer service
What does it mean to be a world-class Manufacturer?
It means you are in control and your competitors struggle to emulate your success.
What does it mean to be a world-class Manufacturer?
You are in in control—
·In control of your markets and customers
·In control of your processes &
·In control of your resources
Being in control doesn’t necessarily mean you make all the decisions, but it does mean you are prepared and will not be thrown by unexpected changes in demand, technology,circumstance or competition.
7 steps to world class Manufacturing
1. Focus on ‘Competitive Quality’
2. Implement Lean manufacturing
3. Achieve cost efficiency
4. Reduce Time-to-Market
5. Exceed Customer Expectations
6. Streamline Outsourcing Processes
7. Have a global perspective
1. Focus on ‘Competitive Quality’
Today’s dynamic and turbulent business environment has shifted the focus of the organizations from “Quality” to “Competitive quality”.With ever changing customer requirements, quality is no more a competitive weapon. Every organization has quality today.What separates a world class organization from others is -how better you are from the rest of your competitors. Everybody in the organization must think and demonstrate that they can do better.The need of the hour is to constantly challenge the status-quoand develop a constructive level of dissatisfaction with the present performance
2. Implement Lean Manufacturing systems
Lean manufacturing is an overall methodology that seeks to minimize the resources required for production by eliminating waste (non-value added activities) that inflate costs, lead times and inventory requirements, and emphasizing the use of preventive maintenance , quality improvement programs, pull systems and flexible work forces and production facilities. Principles of lean include zero waiting time, zero inventory, scheduling (internal customer pull instead of push system), batch to flow (cut batch sizes), line balancing and cutting actual process times.
3. Achieve cost efficiency
Although recent developments in planning and customer relationship management have focused more on top-line benefits (increased revenue), the bottom line is still greatly dependent on controlling costs. Companies with a lower operational cost structure enjoy an obvious advantage in profitability and the ability to adjust pricing to meet competitive pressures if necessary to maintain or gain market share. Costs are really just part of the scoreboard. When a company implements world-class operational processes, it improves multiple measurements simultaneously,including cost, lead times,inventory and customer service.
4. Reduce Time-to-Market
Customers now penalize suppliers that infringe on their time,
whether through delays, mistakes or inconveniences. Today’s
customers demand operations that are airborne, on-line and real-
time. Soon is not the answer the customers want to hear. They count the speed of response time as a Key Value Dimension.
Good ideas are not enough; well-managed processes for bringing
new products to market faster than the competitors can lead to
significant competitive advantages. Bringing products faster into
the market does represent some element of risk, which can be
properly evaluated.
Risk Analysis
Risk Management
Creativity & innovation
Time based competition
New product development
SCAMPER
Ten commandments of time
Niche Marketing
5. Exceed Customer Expectations
The ultimate key to success in any business enterprise is to please your customers. The most successful companies don’t just meet customer expectations, they exceed them and beat the competitionby setting the standards at a level that makes it difficult, if not impossible, for others to surpass.
6. Streamline Outsourcing ProcessesPrinciples
Outsourcing of manufacturing operations is a common practice today because it offers flexibility—the ability to change products or processes rapidly—and can often save money by exploiting economies of scale or other favorable cost factors the contractor has to offer. For manufacturers, the fastest and easiest way to achieve this goal is through partnershipswith companies that have attained superior capabilities in particular phases of the process-like production. By partnering with world-class contract manufacturers you can reap the benefits almost immediately—well-managed processes, high quality, on time deliveries—and increase your performance and deliver to meet your customer’s expectations.At the same time time you can focus your own resources on things that you do best-product innovation,design,marketing,distribution sales or manufacturing.
7. Have a Global perspective
There’s no question the world is shrinking, and virtually every business is now involved in some form of international trade—whether marketing and selling to customers in other countries or simply using parts or materials that are produced elsewhere. Customers today are looking for world class products. The companies wanting to become world class manufacturing must follow the international standards in quality. One of the best framework to follow in this regard is The Shingo Prizewhich is awarded to companies who have attained manufacturing excellence.
KAIZEN - BUISNESS PROCESS
Twe word Kaizen is a combination of two Japanese symbols: change and good.
It is most commonly translated as "change for the better".
A kaizen event is aimed at creating fast, practical solutions for challenges, using cross functional teams who are empowered to make decisions and immediate changes.
Kaizen puts intellegence and decision-making responcibility squarely in the hands of the associate-experts, supported by actual observation of facts.
It is most commonly translated as "change for the better".
A kaizen event is aimed at creating fast, practical solutions for challenges, using cross functional teams who are empowered to make decisions and immediate changes.
Kaizen puts intellegence and decision-making responcibility squarely in the hands of the associate-experts, supported by actual observation of facts.
Manufacturing systems: The changing methods of manufacturing
Craft or Guild system
Putting-out system
English system of manufacturing
American system of manufacturing
Soviet collectivism in manufacturing
Mass production
Just In Time manufacturing
Lean manufacturing
Flexible manufacturing
Mass customization
Agile manufacturing
Rapid manufacturing
Prefabrication
Packaging and labeling
Ownership
Fabrication
Publication
Putting-out system
English system of manufacturing
American system of manufacturing
Soviet collectivism in manufacturing
Mass production
Just In Time manufacturing
Lean manufacturing
Flexible manufacturing
Mass customization
Agile manufacturing
Rapid manufacturing
Prefabrication
Packaging and labeling
Ownership
Fabrication
Publication
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