Lean Six Sigma Green Belt

Lean Six Sigma Green Belt  (self-paced, online)

   Winter course: Dec. 16, 2020 - Jan. 19, 2021

REGISTER HERE

This course is offered by the Systems Science and Industrial Engineering (SSIE) Department at Binghamton University.  Pre-requisite statistics instruction also offered. This course includes: 

  • Twelve 90-minute pre-recorded lectures and includes soft copies of presentation slides. (A prerequisite statistics day of instruction which is comprised of four addition 90-minute pre-recorded lectures is available to those without experience with probability, statistics and/or quality control.)
  • A take-home examination with a 70-percent minimum passing grade within 5 weeks of the start of the course.
  • Support via access to virtual office hours and email contacts to the professor and teaching assistant
  • Links to the pre-recorded sessions and slides will be sent out at the start of the course.
  • An open-book take-home exam will be distributed by the end of the first week of the course.
  • Allot 30-40 hours for completing the exam.
  • Exam will be due by Jan. 19, 2021 11:59 p.m.
  •  A Micro-credential in the form of a Lean Six Sigma Green Belt digital badge and Green Belt Certificate will be provided to those who successfully complete the course.
Open to
  • Current Binghamton and non-Binghamton students
  • Binghamton alumni
  • Members of industry, non-profit and government agencies 
Requirements
  • Knowledge/experience/education in probability & statistics is required.  Students without this background are strongly encouraged to consider the statistics refresher.
  • Binghamton students: Some examples of courses that fulfill this prerequisite include ISE 261, ISE 362, SSIE 505 or CSQ 112.
  • Computer with a high-speed internet connection and audio. Microsoft Excel is also required.
  • A trial version (free for 30 days) of the Minitab software (for statistical analysis) at the start of the training program. Minitab is available for free for all Binghamton students
  • Updated version of JAVA
  • Headset with microphone may be useful but not necessary.
Materials Provided
  • Instruction via pre-recorded lectures
  • Soft copies of slides.
  • Support via virtual office hours and email with the instructor and teaching assistant.
  • Grading of take-home exam
  • Lean Six Sigma Green Belt Certificate of Completion

Prerequisite Statistics: Four 90-minute lectures

For those who do not have prerequisite coursework in statistics

Session 1 - Course Introduction, Course Outline, Fundamental of Problem Solving, Introduction to Statistics, Sampling Process, Introduction to Minitab

Session 2 - Basic Statistics: Measures of Location, Measures of Variability, Data Visualization, Coefficient of Variation, Dot Plot, Histogram, Stem And Leaf, Box Plot

Session 3 - Basic Statistics: Random Distribution, Variables Types, T test, Z test, Statistical Tables, Confidence Intervals for Mean, Confidence Interval for Proportions, Confidence Interval for Standard Deviation

Session 4 - Advanced Statistics: Compare Means, Compare Variances, Compare Proportions, Rejection Region, Fail to Reject, Type 1 error and Type 2 error, Power and Sample Size, P-value

Green Belt: Twelve 90-minute lectures

Several case studies and applications of lean six sigma concepts will be presented throughout the course. 

  • Continuous process improvement (CPI) with emphasis on both lean and six sigma concepts and methodologies;
  • Lean concepts and its applications, such as 5s, waste reduction, value stream mapping, and error proofing;
  • DMAIC (Define, Measure, Analyze, Improve, and Control) to solve issues and transition CPI projects from one phase to another
  • Basic statistical analysis methods, tools, and control charts used to determine key relationships between inputs and outputs;
  • The integration of both lean and six sigma for achieving data-driven process improvement results
  • Team dynamics and leadership to provide effectively successful projects.
Course Outline

Session 1 - Course Introduction, Meet the Instructor, Training Objectives, Training Outline, Fundamental Concepts, Flow Charts, Process Maps

Session 2 - Pareto Charts, Cause and Effect Diagram or Fishbone (Ishikawa), Optimizing Process Flow, Bottle Necks, Forecasting Demand

Session 3 - Capacity, Wait Times, Continuous Improvement, Kaizen, Deming, PDSA Cycle, Quality Circles, Quality Certifications and Awards - ISO 9000 and Malcolm Baldrige, Statistical Process Control

Session 4 - Lean, Six Sigma, TPS, Value Added vs. Non-Value Added, 7 Wastes/Muda (TIM WOOD), Production Systems (Craft, Mass, Lean), Lean Tools, House of Lean, Push/Pull, Visual Control, Kanban

Session 5 - Time & Motion, Takt Time, Throughput, Value-Added Time, Heijunka (Leveling), Standardized Work, Jikoda & Andon, Mistake Proofing (Poke-Yoke), SMED, 5Ss

Session 6 - Spaghetti Diagram, Value Stream Mapping, SIPOC, Projects and Case Studies, Intro to Six Sigma

Session 7 - Six Sigma, Lean Six Sigma, Kaizen Event, Six Sigma Model, Key Players in Six Sigma Program – Role and Responsibilities, DMAIC, Project Management, Decision Criteria and Decision Matrix

Session 8 - Project Scoping, Project Charter, Project Planning, 7 Basic Quality Tools, 7 New Quality Tools, Critical to Quality, Data Collection

Session 9 - Data Collection Methods, Sampling Methods, Basic Statistics, Measurement System Analysis, Gauge R&R

Session 10 - Process Capability, Benchmarking, Correlation Coefficient, Regression Analysis

Session 11 - Hypothesis Testing, Design of Experiment, ANOVA

Session 12 - FMEA, House of Quality, Quality Function Deployment, Control Charts: X-bar Chart, R Chart, Process Control Plan, Case Studies on DMAIC

Instructor

Dr. Khasawnweh

Mohammad T. Khasawneh

  • Professor and Chair in Systems Science & Industrial Engineering Department
  • Associate Director, Watson Institute for Systems Excellence
  • Director, Healthcare Systems Engineering Center
  • Director, Human Factors and Ergonomics Laboratory
  • Graduate Program Director, Executive Master of Science in Health Systems
  • SUNY Chancellor's Award for Excellence in Teaching
  • PhD, Industrial Engineering, Clemson University

 Teaching Assistant - TBD

Fees & Deadlines

Group pricing may be available upon request. 

We reserve the right to cancel our sessions.  

If canceled, fees will be refunded in full.

Registration is open until December 16, 2020

Registration closes on Date TBD at noon Eastern Time.

 

Green Belt Course Only 
(Twelve 90-minute Lectures)

 Prerequisite Statistics+Green Belt Course 
(Sixteen 90-minute Lectures)

 

Standard/Industry

$850

$950

 

Government/Binghamton Alumni, staff & faculty

Binghamton Alumni (graduated in Dec 2019 or prior)

 $650 $750

 

Current Binghamton students
and Binghamton Alumni (Graduating in May 2020 or after)

$350

$450
Non-Binghamton students

Please email proof that you are a matriculated student at a University (a screenshot of class schedule/ transcript wil work)

Email to: wtsnindy@binghamton.edu

 $450 $550
 

Registration

Registration confirmations will be sent by email. Detailed instructions about accessing the course is included in the email.

If you have not received confirmation within seven days of registering, please contact the Office of Industrial Outreach to make sure we received your registration.

Contact information:

Office of Industrial Outreach:
Astrid Stromhaug (Sr. Staff Assistant), wtsnindy@binghamton.edu, (607) 777-6241
Mike Testani (Director of Industrial Outreach) wtsnindy@binghamton.edu, (607) 777-6243
 

Cancellation and Refund Policy

  • All cancellations must be received in writing (email, fax or letter).
  • No refunds for cancellations or non-attendance after course starts.
  • Refunds are not issued after the course has begun. Substitutions may be made anytime before the beginning of the course by informing the Office of Industrial Outreach.
  • If the course is canceled, enrollees will be advised and receive a full refund.
Deadline

 

Decemver 16, 2020, 9 a.m. 
Administrative Fee $20