This document provides an overview of a Lean Six Sigma Green Belt training course. It covers quality approaches over the years including quality circles, statistical process control, ISO 9000, reengineering, benchmarking, balanced scorecard, and Lean Manufacturing. It defines Six Sigma as a philosophy, set of tools, methodology, and metrics focused on reducing process variation. The training covers voice of the customer methods, project selection, the DMAIC problem-solving approach, and phase deliverables/tools.
This slide deck will help you appreciate the application of statistics (and now data science) in the field of Quality Management and Process Improvement. And why is there a need to produce a consistent "in spec" product at 99.9997% of the time.
Six Sigma (Quality Management System)
Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects.
Six sigma process is one in which 99.9999966% of the products manufactured are statistically expected to be free of defects.
Six sigma is a very clever way of branding and packaging many aspects of TOTAL QUALITY MANAGEMENT.
Basic overview six sigma, Six Sigma is a production philosophy that uses data, processes, and tools to nearly eliminate defects and bring performance close to perfection. Specifically, achieving Six Sigma means that no more than 3.4 defects occur per one million “opportunities” to create an acceptable output
This slide deck will help you appreciate the application of statistics (and now data science) in the field of Quality Management and Process Improvement. And why is there a need to produce a consistent "in spec" product at 99.9997% of the time.
Six Sigma (Quality Management System)
Six Sigma seeks to improve the quality of process outputs by identifying and removing the causes of defects.
Six sigma process is one in which 99.9999966% of the products manufactured are statistically expected to be free of defects.
Six sigma is a very clever way of branding and packaging many aspects of TOTAL QUALITY MANAGEMENT.
Basic overview six sigma, Six Sigma is a production philosophy that uses data, processes, and tools to nearly eliminate defects and bring performance close to perfection. Specifically, achieving Six Sigma means that no more than 3.4 defects occur per one million “opportunities” to create an acceptable output
Show drafts
volume_up
Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Lean Six Sigma- Internal Training Slides-2.pptx
1. Lean Six Sigma
Internal Training Course
Epyllion Limited
Scope : Green Belt
Trainer – Debasish Dey
DM- QAD, CLSSGB
Day: 2
Module : Introduction-2
Duration : 2 Hours
2. Quality Approaches Over the Years
What is Six Sigma-Definitions, Interpretation, Symbols
VOC, Way of collecting VOC
Project Selection
Introduction -2
3. Serial Quality Approach Time Frame Short Description
1 Quality Circles 1979-1981
Quality improvement or self-improvement study groups composed of a small number of
employees (10 or fewer) and their supervisor. Quality circle originated in Japan. Where they
are called "Quality Control Circles"
2 Statistical Process control Mid-1980s
The application of statistical techniques to control a process. Also called "Statistical quality
control"
3 ISO 9000 1987- Present
A set of international standards on quality management and quality assurance developed to
help companies effectively document the quality elements to be implemented to maintain an
efficient quality system. The standards underwent revisions in 2000, 2008 and 2015 and now
comprise ISO 9000 (Definition) 9001 (Requirements) 9004 (Continuous Improvement)
4 Reengineering 1996-1997
A breakthrough approach involving the restructuring of an entire organization and its
processes
5 Benchmarking 1988-1996
An improvement process in which a company measures its performance against that of best-
in-class companies, determines how those companies achieved their performance levels, and
uses the information to improve their performance .The subjects that can be benchmarked
include strategies, operations, processes and procedure.
6 Balanced Score Card 1990- Present
A management concept that helps managers at all levels monitor their results in their key
areas.
7 Six-Sigma 1995- Present
A methodology to reduce process/defect variation and increase financial benefit of the
organization.
8 Lean Manufacturing 2000-Present A methodology to reduce waste and increase efficiency.
Quality Approaches Over the Years
4. What is Six Sigma
Sigma is a statistical term that refers to the
standard deviation of a process around it’s
mean versus the methodology of problem
solving that has been labeled “Six Sigma”.
Common
Threads
those
defines
“Six Sigma”
Use of teams that are assigned well-defined projects that have direct impact on the
organization’s bottom line.
Training in “Statistical thinking” at all levels and providing key people with extensive
training in advanced statics and project management called as Black belts.
Emphasis on the DMAIC approach to problem solving ;Define, Measure, Analyze,
Improve, and control.
Continual effort to reduce variation in all processes within organization.
5. Six Sigma a Philosophy: The philosophical perspective views all work as
processes that can be defined ,measured, analyzed, improved and controlled
(DMAIC).Processes require inputs and produce outputs. If we can control inputs
then output also can be controlled. This is expressed as Y=f(X).
Six Sigma a set of tool: Six sigma as a set of tool includes all the
qualitative and quantitative techniques used by Six sigma expert to drive
process improvement. Tools include- SPC, Control charts, FMEA, Process
mapping ..etc
Six Sigma a Methodology: This view of Six sigma recognizes the
underlying and rigorous approach known as DMAIC. Starting with
identifying the problem and ending with the implementation of long
lasting solutions.
Six Sigma a Metrics: In simple terms, six sigma quality performance
means 3.4 defects per million opportunities.
( Account for 1.5 sigma shift in the mean)
What is Six Sigma.. Continues ….
7. What is Six Sigma.. Continues ….
The Target of Six Sigma is to achieve “Bottom Line Result”
8. Why Six Sigma
Customer Satisfaction
at Lowest Cost
Defeat competition by
understanding and then
exceeding customer
expectation.
To achieve ambitious
process excellence
To Improve Internal and
external metrics
CTQs
• Delivery
• Price
• Quality
External Metrics
Internal Metrics
• Cycle Time
• Cost
• Defects
CTPs
Simplify processes to reduce cycle time
Reduce cost by increasing efficiency and
eliminating non value added steps
Eliminate Variation
Target/AIM
12. Define Phase
a) Problem Definition
Tree
b) SIPOC Analysis
c) financial benefit
assessment
d) Project Charter
Measure Phase
a) Process Mapping
b) Operational
definition
c)Basic statistics &
Graphical data analysis
d)Measurement
system analysis
e) Process Stability
f) Process baseline
Analyze Phase
a) Cause & effect
diagram
b) 5 why analysis
c)Failure modes and
effects analysis
d) Pareto chart
e) Hypothesis Testing
f) Gap Analysis
Improve Phase
a) Generate Solution
ideas
b) Select best solution
c) Implementation plan
d) Pilot Results
e) Lean tools for
improvement
Control Phase
a) Control method
b) Statistical process
control
c) Other lean tools for
control
d) Control plan
e) Project Closure
Understanding-DMAIC
13. Why Listen to Customers?
Relationship - Customer Satisfaction And Loyalty In Highly Competitive Industries
As satisfaction goes up, so does loyalty – but the relation is not simple.
• Any drop from total satisfaction results in major drop in loyalty.
• In competitive markets, there is a tremendous difference between the loyalty of satisfied and completely satisfied
customers. This difference is hard to achieve and is a moving target.
• It is more effective to move customers from Satisfied to Completely Satisfied than to focus on customers who are
below Dissatisfied.
14. Most Defecting Customers Were “Satisfied“
• Customers Want To Be Completely Satisfied. When They Aren’t Completely Satisfied, They Have Reasons…
• Most Managers Should Be Concerned If The Majority Of Their Customers Fall Into The Satisfied Category
• The Key To Keeping, Finding, And Winning Customers Is To Understand What Customers Are Saying. . .
Why Listen to Customers?
15. Core Customer Research Methods
• A Voice of the
Customer
Listening Process
• Developing a
Listening
Strategy
• Listening to
Customers
• Organize and
Analyze Data
• Communicate
the Learning
• Drive Business
Activities
Methods of Listening to Customers
16. A Voice-Of-The-Customer Listening Process
The VOC Process Is A Continuous, Strategy-Driven Set Of Activities Focused On Establishing A Learning
Relationship Between Providers And Customers That Drives Business Results
What to do to set up a Successful VOC Process:
By Knowing
key
Customers.
We Know
How Satisfied
Current
Customers
are with
business
products and
Services.
Listening
Process
Provides The
Data To
Support Our
Business
Strategy.
By Knowing
Why
Customers
Like Products
And Services
From Our
Competitors.
By Knowing
What
Information
We Already
Have About
Customers.
By Knowing
How To
Gather And
Translate
Customer
“Noise” Into
Meaningful
Data.
By Having A
Strategy For
Sharing
Learning
About
Customers
With
Customer –
Both External
And Internal.
By
Establishing
A VOC
Listening
Process In
Place That
Links
Listening To
Business
Improvement
And
Innovation.
17. Collecting Voice of Customer
Base Line
Research
Interviews
Focus Groups
Surveys
Understand Scope
Customer issues & needs
Customer issues & needs
Customer issues & needs
19. Project Selection
VOC: Voice of Customer
VOP: Voice of Process
VOB: Voice of Business
VOE: Voice of Employees
Projects
20. Examples of Projects
COPQ Reduction
Defect Reduction
Cycle Time Reduction
Productivity Improvement
Customer Retention
Project Selection
Process
Make a list of “Pain
Areas”/KPI derived from Data
Use appropriate selection
criteria for the final choices
Apply the criteria and select
the project
Evaluate the set of projects
against pressing business
needs
Draft Charter for each
selected Project
21. Phase Wise Deliverables & Tools
Serial Phase Deliverables Tools
1 Define
1.Voice of the customer
2. Project CTQ
3. Project Charter
4. Project Description
5. Financial Benefits
6.Team Kick off
7. Tollgate Reviews
1.Problem Definition tree
2.SIPOC Analysis
3.Affinity Diagram
4.Kano Analysis
2 Measure
1. Process Mapping
2. Operational Definition & Data Collection /Types of Data
3. Basic Stat & Graphical analysis
4. Measurement Analysis System
5. Process Stability
6. Process Baseline
7. Tollgate Review
1. Process Flow Chart
2. Value Stream Map
3. Graphical Analysis through Minitab- Histogram, Individual Value
plot, Box plot, Bar Chart, Pie Chart, Probability distribution plot
4. MSA through Minitab
3 Analyze
1. Cause & Effect Analysis
2. 5 Why Analysis
3. FMEA
4. Pareto Chart
5. Hypothesis Testing
6. Gap Analysis
7. Tollgate Review
1.Root Cause analysis tools
2. Minitab for hypothesis testing
A. 1 Sample t test
B. Normality Test
C. Two Sample vs each other
D. 2 Sample t test E. 2 Sample standard deviation F. Paired t Test. G
Anova test. H. 1/2 Sample % defective test. I. Chi square test. J.
Regression Test. K. Correlation Test
4 Improve
1. Generate Solution ideas
2. Select Best solution
3. Implementation plan
4.Pilot Results
5. Lean Tools for improvement
6. Toll gate review
1. Six thinking hat
2. Brainstorming
3. Multi Voting
4. Solution Selection Matrix
5. Lean ( Wastes minimization/ Kaizen)
5 Control
1. Control Methods
2. Statistical Process Control
3. Lean tool for control
4.Control plan
1. Poka-yoke
2. Control Charts ( I-MR Chart, X-Bar Chart, U control Chart, P Control
Chart )