Time Allocation in Minutes Description Category Delivery Method

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1 Course Name 5S Pre-Score 5S 5S Foundational 5S ANOVA - Analysis of Variance ANOVA Part I ANOVA Part II Time Allocation in Minutes Description Category Delivery Method 1 hr. 10 min. 5S is a Lean method designed to eliminate waste by establishing a place for everything and putting everything in its place. The five S s represent Sorting, Storing, Shining, Standardizing and Sustaining. Each of these activities is carefully explained during this course so that students understand what 5S is or is not, as well as the benefits of 5S. Examples and an interactive simulation help illustrate 5S in the workplace. Experienced Participant will be able to define 5s (Sort, Store, Shine, Standardize, Sustain) and the purpose to prepare a work area for improvement. Visual Control will be introduced as well to ensure visual signals are developed to provide an 1 hr. immediate understanding of the area by employees to be used by employees. Basic Participants will be able to describe the benefits of 5s, state what 5s is and what it is not, how to complete a 5s event and understand the key methods Classroom 1 hr. 30 min. for sustaining 5s Basic Classroom Participants will be know what 5s is, what it looks like, and the main tools of 5s: Shadow Boards,Point of Use Tools, Color Codes, 5s Zone Map, 5s Improvement Plan, 5s Plus Audit, and Radar Charts. Participants will also 1 hr. learn about the daily 5s Genba walks. Basic Classroom 1 hr. Concepts covered in this course include ANOVA (also called Analysis of Variance), sum of squares, and mean square error. A detailed process for executing a successful ANOVA is demonstrated and calculations are practiced using Minitab. Advanced At the end of this module, participants will be able to discuss the key concepts of Analysis of Variance (ANOVA) sum of squares and mean square error and the purpose of the technique when you have more than 2 levels for an X factor. Participants will demonstrate calculating an ANOVA table by hand to develop an understanding of how the variation is partitioned to construct the 1 hr. 30 min. table followed by Minitab examples. Experienced Classroom Similar to ANOVA Part I, emphasis in this module will be on evaluating the 1 hr. residuals to ensure a good model. Experienced Classroom

2 Attribute Measurement Systems Basic Attribute Measurement Systems Measurement Systems Analysis Variable Measurement Systems (Basic) Variable Measurement Systems Analysis (Level 2) Basic Capability Analysis This module explains how to assess the capability of a measurement system and why this task is critical to measurement success. Participants learn about Attribute R&R and where Gage R&R fits in the DMAIC roadmap. This course is ideal for introducing measurement system concepts to all levels of your 1 hr. 12 min. organization or as a refresher course for Six Sigma practitioners. Advanced This module introduces Attribute Repeatability & Reproducibility, and explains how to assess the capability of a measurement system and why this task is 33 min. critical to measurement success. Experienced 2 hr. 30 min. At the end of the module, participants will be able to define Measurement Systems Analysis and explain the fundamental measurement concepts including accuracy, precision(reproducibility & repeatability) and resolution. Participants will perform measurement studies for both attribute and continuous data including analysis and interpretation. Experienced Classroom This modules provides an overview of Variable Repeatability & Reproducibility concepts. The Variable R&R tool is used when operators are measuring continuous or variable data such as time, height, weight, and pressure. These studies are used to prove whether an individual can repeat the same measurement process, and if a different individual will be able reproduce the same measurement process. Variable Measurement Systems are also used to identify whether the variation observed within data is due to the process itself or the way in which the process is being measured. 15 min. Experienced This module introduces Variable Repeatability & Reproducibility measurement systems and the related concepts of Accuracy, Resolution and 1 hr. 22 min. Precision. Advanced This module provides a thorough understanding of what it means to perform a capability analysis, and the benefits that can be gained from quantifying the capability of a process. The course covers several concepts such as shortterm vs. long-term capability, various capability metrics, and a four-step process for calculating capability for both attribute and variable performance characteristics. 1 hr. 14 min. Experienced

3 Capability Analysis 2 hr. 7 min. This module provides a thorough understanding of what it means to perform a capability analysis and the benefits that can be gained from quantifying the capability of a process. It covers several concepts such as short-term vs. longterm capability, various capability metrics, and a four step process for calculating capability for attribute and variable performance characteristics. Experienced Process Capability Capability Basic Factorial Experiments Full Factorial Experiments 2 hr. 30 min. By the end of this module, participants will be able to discuss the fundamental concepts of process capability including short term & long term, Capability Metrics, and establishing average baseline performance versus entitlement on their projects. Participants will practice caculating Process Capabiity using Mintab for attribute data (binomial, Poisson) and continuous data (individual, subgroups, normal and non-normal data). As an option, participants can learn about other Capability Metrics (Cp, Cpk, Pp,PpK). Basic Classroom Participants will understand fundamental process capability concepts including VOP vs. VOC, Short term vs. Long term, 1.5 Sigma shift, and rational subgroups. Process capability metrics will be calculated to demonstrate process performance as it relates to customer requirements (DPMO, PPM, Sigma Level, dpu & RTY). Participants will calculate process 3 hr. capability for both discrete and continuous situations. Basic Classroom This course covers Full Factorials and introduces 2K Factorials. General factorial experiment design and analysis are demonstrated, and several concepts are introduced including main effects and interactions, as well as key DOE terms. In addition, this course shows how to derive Y as a function of X. This module is intended for Six Sigma practitioners, team members, and process owners. Introduction to DOE is a required prerequisite for this course. 1 hr. 36 min. Advanced 1 hr. 30 min. At the end of the module, participants will be able to demonstrate factorial experiment set-up and analysis including the concepts of main effects and interactions. Participants will also practice using ANOVA to analyze a full factorial and will be familiar with additional DOE terms and definitions. Experienced Classroom

4 2K Factorials Introduction to Design of Experiments DOE Intro Fractional Factorials Attribute DOE Participants will learn about and practice two-level factorial designs. 2k factorial notation will be explained and using contrasts for calculating main effects and interactions will be demonstrated. In completing the analysis for a 2k factorial experiment, participants will calculate % Sum of Square, use the mathematical model and learn about the optimizer to help with various 1 hr. 30 min. scenerios. Advanced Classroom This module introduces the basic concepts behind Design of Experiments (DOE). It covers strategies for determining the critical inputs to drive the important outputs, the DOE method, and possible barriers to applying DOE in the real world. 49 min. Advanced Participants will be able to define the concept of statistically designed experiments and how it is more effective and efficient than "one factor at a time" or "guessing". A receipe for conducting an experiment will be demonstrated using a simple golf example (club and ball type). Participants 1 hr. will be aware of the terminology used in DOE. Experienced Classroom By the end of this module, participants will be able to understand the concept of a Fractional Factorial design as well as its advantages (similar results with less implementation costs) and disadvantages (confounding, alias). Emphasis will be on the when to apply Fractional Factorials (screening). Participants will also demonstrate and practice the complete design and 1 hr. 30 min. analysis of fractional factorials. Experienced Classroom Participants will be able to define Y=f(x) with catdgorical dependent variables. Analysis of Means (ANOM) provides an approach for evaluating proportions sorted by levels of an X. Other options will be reviewed including 2k factorial designs for simple experiments as well as introducing Binary Logistic 1 hr. 30 min. Regression Experienced Classroom Basic Statistics 1 hr. 4 min. This comprehensive module discusses data types, introduces populations versus samples, and describes measures of central tendency and variation. This module also covers frequency distributions and discusses long-term versus short-term variation, DPMO, and DPU. Experienced

5 Basic Statistics Basic Statistics 2 Introduction to Statistics Basic Tests of Hypotheses Statistical Analysis At the end of this module, participants will define and use examples to demonstrate the different types of data, continuous and discrete and learn the difference between population data sets and samples. Participants will be able to calculate the measures of central tendency (mean, median & mode), measures of spread (range, variance, standard deviation) and concepts of shape (frequency distribution and normal distribution). Module will introduce 2 hr. 30 min. control charts as the tool to determine process behavior. Basic Classroom At the end of the module, participants will be able to define the fundamental measures of central tendency (mean, median & mode) and measure of variation (range, variance and standard deviation). Time series plots will be introduced as an approach for determining process stability. Participants will be introduced to Normal Distribution and measures of shape (Anderson- Darling Test for Normality, Skewness, Kurtosis)as well as probability and other probability distributions Binomial, Poisson, Exponential and Gamma 2 hr. 30 min. distributions. Experienced Classroom The ability to understand and use statistical data is crucial to the success of any Lean Six Sigma project. This module introduces basic statistical concepts including populations and sampling, measures of central tendency, and measures of variation. 1 hr. 37 min. Advanced This module introduces the concept of statistical hypothesis testing, defines the null and alternate hypotheses, provides a general method for constructing a hypothesis test and demonstrates how to use MINITAB for hypothesis testing. This module is intended for Six Sigma practitioners, team members and process owners. 1 hr. 31 min. Advanced Participants will be introduced to the fundamentals of Hypothesis Testing including defining the null and alternate hypothesis. Use of the Hypothesis Testing Roadmap to select the appropriate hypothesis test will be emphasized. Participants will complete the fundamental hypothesis tests including 2 sample proportion test, contingency analysis, 2 sample t-test, 2 hr. 30 min. ANOVA and simple linear regression. Basic Classroom

6 Mean and Variance Tests Proportion Tests Hypothesis Testing Introduction to Hypothesis Testing Brainstorming Techniques Generating Solution Ideas Generate Solutions Building a C&E Matrix At the end of this module, participants will be able to use Minitab for conducting hypothesis tests for means and variances. Starting with one data set compared to a target, one sample t test and one sample variance will be shown. Emphasis will be on comparing two data sets to each other (two sample t test, test for equal variances) as a common technique for making comparisons in process improvement as well as the unique situation when items can be paired appropriated (paired t test). In all cases, Minitab will be used to determine appropriate sample sizes based on risk tolerance and 2 hr. practical aspects. Experienced Classroom Participants will learn about and practice hypothesis tests for proportions including 1-proportions test, 2-proportions test and multiple proportions test 2 hr. using Analysis of Means (ANOM) Experienced Classroom Using Hypothesis Testing, practitioners learn how to prove and disprove 44 min. theories, leading to more sound and statistically-based decisions. Advanced Participants will learn about the fundamentals of Hypothesis Testing and why it is used for analysis. Using the legal system, a method will be demonstrated and practiced for Hypothesis Testing stressing the correct definition of the null and alternate hypothesis. A Roadmap will be introduced as a job aide for Hypothesis Testing and a couple of examples wil be demonstrated using the 1 hr. 30 min. roadmap. Advanced Classroom Brainstorming is one of the key tools used to generate ideas and solutions. In this course, students will learn about six types of brainstorming techniques: Imaginary Brainstorming, HIT Matrix, Concept Tree, SCAMPER, Brainwriting 37 min and Random Stimulus. Basic In this course, students will learn a variety of tools used to produce solutions aimed at reducing the effects of root cause issues. Techniques explored include brainstorming, benchmarking, open innovation, and biomimicry. Students will also learn how to group and clarify ideas in preparation for 24 min. evaluating solutions. Experienced Participants will learn about and practice a variety of brainstorming tools to generate solutions. Basic creative thinking techniques will be described and 2 hr. demonstrated by participants. Basic Classroom 15 min. This course describes how to build and analyze a cause and effect matrix, or C&E Matrix. The C&E matrix links the critical-to-quality aspects of a process to the previously identified causes and effects. It is a very useful tool for prioritizing the factors that have the highest impact on customer satisfaction, and choosing the correct factors that require further measurement. Basic

7 Identify X's CE Tools Fishbone Diagrams 1 hr. 30 min. Participants will learn and construct various approaches to identifying potential causes. Methods include the Cause & Effect Diagram ("fishbone") to identify potential X's asking "5 Whys", and using a Cause and Effect Matrix to link potential process X's to key customer requirements. Basic Classroom Participants will learn and construct various approaches to identifying potential causes. Methods include the Cause & Effect Diagram ("fishbone") to identify potential X's and using a Cause and Effect Matrix to link potential process X's to key customer requirements. A Tree Diagram approach will be 1 hr. 30 min. introduced as a visual method for converting goals into actionable items. Basic Classroom This module introduces the Fishbone Diagram, its purpose, and its 14 min. application. It also explains how to construct a Fishbone Diagram. Basic Control Plans 1 hr. 30 min. Participants will practice developing a control plan to plan, execute and monitor the process. Plans to transition the improvement to the appropriate process owner will be made using the Project Transition Action Plans (PTAP). Basic Classroom Building a Control Plan Intro to Control Building an FMEA 25 min. The control plan is one of the most essential tools in process excellence. It allows practitioners to gain buy-in for the solution, establish sustainable improvements, and transition ownership of the process back to the team. In this module, students will learn how to complete this document. Basic At the end of beginning of this module, participants will develop a control plans to initiate systems to maintain the improvement. Emphasis will be made on completing a Project Transition Action Plan (PTAP) as a means of effectively transitioning the changes to the operational personnel and Process Owner. Module will conclude with an introduction to 4th Generation 1 hr. Management Concepts including the use of the Joiner Triangle. Experienced Classroom The Failure Modes and Effects Analysis, or FMEA, identifies key errors, assigns severity, determines occurrence, and identifies the ease of detection of those errors. In this module, students will learn to use the risk assessment tool to identify critical "failure modes" so that potential issues can be 30 min. prioritized and resolved. Basic

8 FMEA Chi Square Test Contingency Tables Sample Size Confidence Intervals Confidence Intervals 1 hr. 30 min. Participants will learn about a structured technique referred to as Failure Modes and Effects Analysis (FMEA) The tool is used by a group to evaluate each step in a process and assess potential risk by evaluating what could go wrong, its impact and what is used to detect or control the risk. Participants will explain the fields on a FMEA tool and practice creating several rows of a FMEA tool. learn the technique and practice Basic Classroom This module discusses how to deal with hypothesis tests when both the X and Y are attribute or discrete data and the levels of interest are greater than 2. It demonstrates how to select the appropriate test, how to arrange the data and perform the test in MINITAB, and how to interpret the results. Contingency tables and chi-square tests are among the most simple hypothesis tests. However, they provide the same values to the business as more 17 min. sophisticated tests, such as ANOVA or Regression Analysis. Advanced Participants will be able to discuss contingency table analysis for attribute data and demonstrate manual calculation. Minitab will then be used to practice contingency table analysis to determine if factors are independent (Ho) or dependent (Ha). Participants will also practice using chi-square Goodness of Fit analysis used to determine if the data follows an assumed 2 hr. distribution or not. Experienced Classroom Participants will be introduced to sample size considerations for estimation (how many do I need to estimate a population parameter). The different types of hypothesis testing errors (Type I-alpha & Type II-Beta) will be reviewed from a practical standpoint along with the fundamental terminology for sample size (power, critical difference, delta and specific test). Using Minitab, participants will practice calculating sample sizes for estimation, 1 & 2 sample 2 hr. t tests, 1 & 2 proportions test and 1-2 sample variance tests Experienced Classroom This module on confidence intervals introduces several approaches for quantifying the statistical uncertainty of sampling. It explains how to use sample statistics to calculate and interpret confidence intervals for the population mean, the population standard deviation, and the population 52 min. proportion. Advanced By the end of this module, participants wil be able to describe the difference between populations and samples and understand how statistics vary around the parameter they estimate. Participants will practice the most common methods of estimating confidence intervals for means, standard deviations 1 hr. 30 min. and proportions. Experienced Classroom

9 Central Limit Theorem Constructing Control Charts Introduction to SPC Introduction to SPC Introduction to SPC Variable SPC Participants will learn about and experience the Central Limit Theorem(CLT), a fundamental theorem in statistics. Session will confirm the validity of the CLT with both normal and non-normal data. Applications of the CLT will be 1 hr. 30 min. demonstrated using Control Charts and MSA. Experienced Classroom This module describes the types of Control Charts used in monitoring and controlling a process, including Xbar-R, I-MR, P and NP, and U and C charts. The module explains how to manually construct each chart by calculating control limits, setting zones and plotting data, and demonstrates how to create each chart type in Minitab. In addition, the module discusses the guidelines for selecting the appropriate chart type and how to interpret chart results. 1 hr. 39 min. Advanced From the history of SPC to the difference between common cause and special cause variation, this course describes how to use SPC to measure and control process variation. Run Charts and Control Charts are illustrated and defined, and the rules for interpreting the charts are described in detail. Finally, the course discusses how Control Charts can be used to assess 59 min. variation and take action to improve processes. Advanced Participants will learn about the history of Statistical Process Control and the appropriate use of control charts to control the X's and monitor the Y's. Using Minitab, participants will practice constructing and interpreting (standard rules of interpretation) of continuous and discrete control charts. Emphasis on using control charts to detemine the four stages of a process control vs. 2 hr. process capability. Basic Classroom Participants will learn about the history of Statistical Process Control and the guidelines for using control charts to control the X's and monitor the Y's. Participants will practice using the Shewhart PDSA cycle, run charts and X-R 1 hr. 30 min. control charts. Basic Classroom 1 hr. 30 min. Initially, participants will be able to interpret control charts using the 8 Control Chart rules. Appropriate action based on special or common cause will be emphasized concerning the strategy for improvement. Participants will practice constructing and interpreting an X-R chart as well as discussing indepth rational subgrouping. The Individual Measurement Moving Range Chart will be introduced as an alternative for individual points that cannot be subgrouped appropriatedly. Basic Classroom

10 Attribute SPC Control Methods Mistake Proofing Mistake Proofing Mistake Proofing Preventing Human Error Participants will practice using a roadmap for control chart selection to be able to select the correct chart. During the remainder of the module, participants will practice constructing and interpreting Attribute Control Charts 1 hr. (p,np,c,u). Basic Classroom The purpose of control methods is to reduce the potential for any defect to occur. This module will review a variety of control methods, as well as their 18 min. ability to detect and prevent defects. Experienced By the end of this module, participants will be able to define mistake proofing as well as describe the benefits. Participants will learn a specific steps for 1 hr. 30 min. mistake proofing and practice applying the technique Experienced Classroom Mistake proofing is based on the concept that errors can be avoided if the appropriate mistake proofing techniques are used. This module reviews the techniques that can be used to mistake proof a process as well as the eight behaviors that lead to mistakes. This module also compares mistake proofing 25 min. to the common types of control methods. Experienced At the end of the module, participants will be able to explain why mistake proofing is better than inspection. Different types of mistake proofing 2 hr. techniques will be practiced to demonstrate utility. Basic Classroom 50 min. This course explains how human factors result in errors. It presents three modes of human behavior and the most typical errors that humans make when operating in these modes. The course also explains ways in which to prevent human error. Basic Creating Pareto Charts 17 min. This module introduces the Pareto Principle, which suggests that a large majority of problems (80%) are produced by a few key causes (20%). It also demonstrates how to construct and analyze a Pareto Chart. Experienced Current State Value Stream Maps Value Stream Map Future State This course explains a primary Lean concept, value stream mapping, and its role in identifying waste in and between processes. The course explores the aspects of a value stream -- all actions and process steps, both value-add and non-value-add -- required to create a product or service. Concepts such as SIPOC, top down flow chart, process flow mapping, and RBWA are discussed in the 8-step process to creating a value stream map. The course 41 min. requires an understanding of process flow mapping. Experienced Participants will be able to answer questions concerning the demand, material flow, information flow and supporting improvements. Using a case study, participants will learn about and practice answering 8 questions as a logical 2 hr. approach for determining the Future State. Experienced Classroom

11 Future State Value Stream Maps Define As IS Define the As-Is VSM High-Level Process Maps Mid-Level Process Maps Process Analysis Tools Spaghetti Diagrams This module explains the concept of a "Future State" Value Stream Map. It discusses how to design the Future, or Ideal, State of a process using Lead Time, Cycle Time, and Takt Time. It also describes methods to achieve the Future State, including Spaghetti Diagrams, Cellular Layout, 5S, and Visual 29 min. Controls. Experienced Participants will be able to develop various types of process maps (Macro map, Process Flow Diagram, Value Stream Map & Spaghetti Diagram) to clarify the current state. Identify and see waste in a process (WORMPIIT) and to clarify value-added and non-value added activites(hidden factory) will 2 hr. 30 min. be emphasized. Basic Classroom Participants will review the various approaches to mapping a process (Macro, SIPOC, Process Map with Swim Lanes, and Detailed Process Map). Emphasis will be on the creation of Lean Value Stream Map and how to use it 1 hr. 30 min. effectively for improvement. Basic Classroom In this module, students are introduced to high-level process maps, specifically Macro Maps and SIPOC Diagrams. Coverage includes the purpose of each map, the steps necessary to create each map, and a 24 min. demonstration of how to apply each map. Experienced Mid-level process maps provide a clear and in-depth understanding of a process in order to improve it. In this module, students learn how to create a Process Flow Diagram that leverages Value Add/Non-Value Add analysis, and also how to create a Swimlane Map that correlates process steps with 31 min. accountability. Experienced 31 min. 17 min. This module explains the purpose of process analysis tools and examines when they should be used. It includes specific instructions for how to create a Detailed Process Map and Standard Work Combination Sheet, two widelyused approaches to process analysis. Experienced Spaghetti Diagrams are used to document the movement of people and resources during a process. This module explains how to create a Spaghetti Diagram, as well as how to analyze the results to reduce wasted movement. Experienced Data Collection 39 min. Proper data collection is critical to the correct analysis and reporting of key business metrics. The fundamental topics covered in this module include, discrete vs. continuous data types, scales of measurement, specific data collection principles, converting attribute data to variable data, sample size considerations, sampling strategies and data gathering strategies. Experienced

12 Data Collection DMAIC for Teams Evaluating Solution Ideas Evaluate Solutions Flow Flow 1 hr. Participants will be able to the importance of using data in each of the DMAIC phases. Emphasis will be on clarifying the purpose of data collection and utilizing key data collection principles including attribute & continuous data, considerations for sample size and sampling strategies(random, stratified random, systematic, clustered) and data collection methods (manual and automatic). Basic Classroom This course examines team member responsibilities and project objectives in each phase of the Six Sigma process. It is designed specifically for 1 hr. 16 min. individuals who will be participating on a Six Sigma project team. Basic Evaluating and prioritizing ideas is key to understanding which solutions should be implemented for long-term success. This module includes a review of the solution selection process and discusses several tools that can be used to prioritize and evaluate ideas. It also addresses ways to gain agreement 26 min. within an organization. Experienced 2 hr. 39 min. 2 hr. This module will emphasize various approaches for narrowing down the list of solutions using group techniques to gain a shared understanding and commitment. Affinity Diagrams will be used to group and clarify solution ideas and clarify selection criteria. Various prioritization techniques will be introduced and practiced (n/3, Impact/Ease matrix, Pugh selection matrix and EPIC Matrix) as well as gaining agreement using facilitation skills. Basic Classroom This module introduces the concept of Flow, which is the balancing of internal resources to meet external demand. Topics include Takt Time, Cycle Time, Lead Time, Work Flow Balance, Standard Work and Cellular Design. Experienced Participants will be able to define the concept of flow and how it applies to their projects. Emphasis will be on practicing and demonstrating the use of the tools required to implement flow including Takt time, standardized work, and workload balancing. Kanban, as a pull technique where one flow is not possible,will be demonstrated with emphasis Kanban squares and kanban signals, including practicing a method for Kanban calculation. Experienced Classroom

13 Lean Process Analysis Inside the Innovation Elite Introduction to Innovation Introduction to Lean Introduction to Lean Six Sigma Introduction to Minitab At the end of the module, participants will know about the key lean approaches for creating the Future State. Starting with creating a "Visual Factory", 5s and Visual Management as the foundation of a lean environment. Improving flow will be stressed included the elements of Takt Time, Line Balancing, Standardized Work and Changing Work Layout. Participants will also gain an awareness of the tools used to control flow, push 3 hr. versus pull, Kanban, FIFO, and the use of supermarkets. Basic Classroom Inside the Innovation Elite briefs business leaders on the exciting developments of standout performers in innovation, and demonstrates proven methods that create successful, sustainable innovation programs. This online executive briefing reveals the five disciplines that firms in the forefront of innovation use to drive growth, meet the ever-changing needs of customers, and revitalize internal processes to embrace change. This briefing is ideal for C-level executives who are concerned about their company's ability to stimulate organic growth. 41 min. Experienced 23 min. 41 min. In this introductory course, students will learn why innovation is critical to the long-term success of their business. They will also learn the key principles of innovation and how it works with existing process improvement programs. Basic Appropriate for all levels of the organization, this introductory course provides a high-level, interactive overview of the fundamental concepts of Lean. Approaching the topic from both a practical and a historical perspective, the course introduces Lean s central tenet the elimination of waste and the identification of value-added activities. Students will also learn how the origins of Lean influenced other key concepts including value, flow and pull. Basic Appropriate for all levels of the organization, this introductory course provides a high-level overview of the fundamental concepts of Lean Six Sigma. It describes the Lean Six Sigma methodology, the role of a Lean Six Sigma 50 min. Black Belt, and what it takes to create a successful Lean Six Sigma culture. Basic This introductory Minitab course introduces Windows, Toolbars, Projects, Worksheets, Data Types, and Basic Functionality. It includes a project example. 45 min. Advanced

14 Intro to Minitab Minitab Part 2 Job To Be Done Jobs to be Done Job Scoping Kanban Kanban Kano Analysis 1 hr. Participants will be introduced to MINITAB structure(main windows,menu structure,tool bars and keyboard commands)and how to navigate. Participants will learn to use various data entry and manipulation techniques as well as the preferred data structure for analysis (stacked), Construction and interpretation of basic graphs will be introduced at this time. Basic Classroom Participants will create and interpret core(graphs menu) and convenience(stat Menu) graphs in Minitab. Use of the Brushing function supporting data analysis and interpretation will be demonstrated. Participants will practice customizing graphs through both dialog box and graph editing 1 hr. 30 min. tools as well as storing a graph layout in a data window. Experienced Classroom The Innovation job to be done is the key to fulfilling client needs. In this course, students will learn how to identify and understand the jobs their 20 min. customers want done, as well as a process to articulate those desires. Experienced A key first step in all innovation efforts is to define the "Job to be Done" from the customer perspective. Module Participants will learn about identifying JTBD and describing different types of jobs (Main, Functional, Personal & Social), explore the use of a customer Job Stream Map and using the structure of job statements to clarify the JTBD. Module also includes a method of identifying innovation opportunities based on customer JTBDs and 45 min. how important and satisfied they are with these JTBD. Experienced Classroom Module will introduce the Job Scoping method as an approach for redefining and scoping the JTBD. It also will enable the participant to see different 45 min. perspectives and the nature behind the problem. Experienced Classroom This course discusses the concept of Kanban which simply means visual signal. It introduces how to use Kanban to control the movement and 27 min. production of new inventory. Experienced Participants will be able to define Kanban and know the different types of Kanban (Kanban Square, Signal, Production, withdrawal and supplier kanbans will be reviewd. Participant will be able to calculate Kanban sizes 1 hr. 30 min. and will be introduced to Little's Law as a way to determine lead time. Experienced Classroom This module outlines the purpose of the Kano model and how it links customer requirements to customer satisfaction in products or services. In addition, this module outlines how the Kano model helps create differentiation and a competitive advantage. 9 min. Experienced

15 Outcome Expectations Outcome Expectations Project Closure Project Closure Project Definition Determine Project Objectives Project Identification Project Prioritization 15 min. Outcome expectations are the expectations that surround an innovation job to be done. In this course, students will learn how to identify the outcome expectations for a specific job to be done, how to measure importance and satisfaction for outcome expectations and how to calculate and prioritize new opportunities that are the result of understanding outcome expectations. Basic Module will define Outcome Expectations, point out the different types of Outcome Expectations, and provide a sentence structure for forming good Outcome Expectations. Participants will learn a method for Identifying Opportunities and identifying outcome expectations that are underserved. Customer Segmentation based on outcome expectation groups will be 45 min. introduced as an alternative to demographic segmentation. Experienced Classroom Effectively driving projects to closure is critical to sustaining gains long-term. This course details the key steps to successful project closure, including closing and handing-off projects, understanding and embracing solutions, and tracking project gains. It describes best practices, including an industry-tested 38 min. project closure process. Basic Participants will learn about appropriate project closure including ensuring project transition (PTAP form) as well as reviewing the major elements of the 1 hr. final report submitted for certification. Basic Classroom This course explains the metrics necessary to create well-defined projects, including primary and consequential metrics, baselines, entitlements and targets. The course also describes the process for writing an appropriate 1 hr. 30 min. objective statement and how to quantify the financial impact of a project. Experienced To ensure an improvement project is off to a good start, participant will focus on determining project metrics (primary, secondary, consequential) and establish a baselinefor the project primary metric. The problem and objective statements will be established for participant's project and an estimated 1 hr. 30 min. financial benefit. Basic Classroom through the application of business metrics. This module introduces the importance of accurately identifying and scoping projects and the tools necessary to accomplish those tasks. This course is designed for anyone 55 min. who is involved in identifying, scoping and prioritizing projects. Experienced This course introduces a powerful process for recognizing and prioritizing projects using a Cause & Effect Matrix. 1 hr. 27 min. Experienced

16 Project Scoping Define Scope Provocation and Movement Sustainable and Predictable Innovation for Organic Growth Roadmap for Innovation Process & Techniques Pull Pull Pull In order to be successful, projects must be properly scoped to the right level of complexity before being handed over to a project team. This course uses a real-world example to illustrate the project scoping process, which includes defining the business issue and scoping it into a project idea. 1 hr. 22 min. Experienced A key aspect of every improvement project is to scope it properly. This module enables participants to identify the business gap, create Macro and SIPOC diagrams, and translate the "Voice of the Customer" into outcome expectations. Qualitative and quanititive tools will be introduced to help with 2 hr. scoping the project. Basic Classroom Provocation and Movement is designed to shock people out of their standard pattern of thinking. This course will demonstrate the Provocation and Movement technique and provide the steps necessary to conduct it within a 26 min. team. Basic 1 hr. 45 min. 32 min. Participants will be able to define Innovation and learn about key innovation principles (Job to be Done, Outcome expectations), processes, tools & techniques. You will also be able to assess your innovation portfolio and understand the Four(4) Growth Strategies for organic innovative growth. Basic Classroom Participants will learn about execution phases of an innovation project (Define, Discover, Develop, Demonstrate), the substeps under each of the four phases,and the tools and techniques to consider using during the innovation effort. Module provides the framework for the entire workshop Basic Classroom This module defines the Lean concept of Pull, and how to build a Pull system to regulate the flow of production. As part of the discussion, it covers how to calculate lead time and work-in-process, Little's Law, and Kanban. Experienced At the end of the module, participants will be able to describe the concept of Pull and why it is better than the traditional push systems. The advantages and disadvantages will be contrasted between single piece and batch flow with strong emphasis on reducing batch size. Participants will experience a simulation that provides practical experience as it relates to high inventory 1 hr. and process steps with extensive variation (Folders) Experienced Classroom By the end of this module, participants will be able to define a Pull System, distinguish between a Push and Pull system, calculate a reorder point, and 1 hr. 30 min. calculate an Economic Order Quanity Experienced Classroom

17 Reducing Setup Time Set-up Reduction Simple Linear Regression and Correlation Regression & Correlation Advanced Regression Intro to Logistic Regression Creating a Pilot Plan LSS Pilot and Implement Reducing the time it takes to move from one process to another is critical to improving productivity, quality and customer satisfaction. In this module, students will learn the best method to document long setups, as as well as 31 min. the 5-step process for reducing setup time. Experienced By the end of this module, participants will be able to define Set-up Time and 1 hr. complete a Set-up Time Reduction Chart Basic Classroom This module introduces simple Linear Regression and how it can be used to study the relationship between a continuous Y and continuous X variable. It discusses how the regression line can be used to predict the value of Y for a given value of X. 48 min. Advanced Participants will become familiar with simple linear modeling and practice using Minitab (and Excel) for construcing least squares model. Interpretation of the output (scatter diagram with best fit line, regression equation, R- squared) will be emphasized as an approach for estimating Y=f(x). Module will conclude with an introduction to correlation (strength of the linear 2 hr. relationship) and how it relates to regression. Experienced Classroom At the end of beginning of this module, participants will review and practice simple linear regression with emphasis on predicting and forecasting with regression models. Higher order models (curvature) will also be reviewed. Participants will be able to complete a Multiple Regression Analysis using multiple X's and practice observing models for Multicollinearity and selecting the best model. Automatic methods (Best Subsets and Stepwise) will be 2 hr. 30 min. reviewed as well as multiple binary logistic regression. Experienced Classroom Participants will be able to define Binary Logistic Regression and know when to use (discrete Y). Participants will also develop an awareness for the purpose of the tool and why it was necessary. Participants will practice with data sets using Binary Logistic Regression with emphasis on interpretation 1 hr. 30 min. and implications of the analysis. Experienced Classroom A pilot allows teams to test and revise solutions before deploying them across an organization.the focus of this module is the 8-step roadmap 18 min. recommended for piloting solutions. Basic 1 hr. After reviewing the benefits of piloting, participants will describe and create a Pilot Implementation Plan using the Implementation Roadmap. The importance of confirming the solutions and tips for full scale implementation will stressed. Basic Classroom

18 Six Sigma from 50,000 Feet Six Sigma Literally Speaking Six Sigma Metrics Process Metrics Six Sigma Roles and Phases Roles Standard Work Appropriate for all levels of the organization, this introductory course provides a high-level overview of the fundamental concepts of Six Sigma. It describes the Six Sigma methodology in detail, the meaning of the Six Sigma Black 1 hr. Belt, what it takes to create a Six Sigma culture and why Six Sigma works. Basic This course explores the meaning behind the phrase "Six Sigma." It illustrates how Six Sigma can be put to practical use inside an organization to affect change, and describes the fundamental concept of variation. In addition, the course explores the cost of poor quality to an organization. The concepts are explained in a simple-to-understand format appropriate for all levels of the organization. 46 min. Basic This module describes the key concepts and metrics used when defining a performance improvement project. Concepts covered include the four types of project metrics, calculations for baseline, entitlement and benchmark, defects vs. defectives, classical yield vs. rolled throughput yield, and the role of DPMO and sigma levels. 1 hr. 12 min. Experienced Participants will learn about selecting the right types of metrics for their projects. The 5 key types of Project Metrics (Primary, Secondary, Consequential, Business, Financial) and good characteristic of process metrics (meaningful, actionable, timely, critical few, not complex)will be discussed. Emphasis will be on both Lean( Lead time, cycle time, space utilization,etc.) and Six Sigma metrics (yield, dpu,dpmo,etc.) will be defined 2 hr. 30 min. and reviewed in depth. Experienced Classroom Designed for executives and managers, this courses describes the key roles individuals play during the phases of the Six Sigma process. Every individual responsible for deploying Six Sigma within an organization should view this 50 min. course. Basic By the end of this module, participants will be able to describe the roles and responsibilities of the various functions inside a Lean organization. For each role, the roles and responsibilities are highlighted, training required and some 30 min. pitfalls to avoid. Basic Classroom 36 min. This module addresses three different components of standard work: TAKT time or customer demand; Work in Process (WIP), which is the minimum amount of inventory needed in order to achieve a smooth flow; and Standard Operating Procedures (SOPs) to document standard routines or procedures. Experienced

19 Standard Work Leadership Standard Work The Eight Types of Waste Wastes Value Introduction to SCORE Visual Management Rapid Problem Solving By the end of this module, participants will be able to define the components of Standard Work, and complete the following forms: Time Observation Sheet, Cycle Time Loading Chart, Standard Work Combination Sheet, 2 hr. Process Capacity Table, Standard Work Chart and a Cross Training Matrix Experienced Classroom Participants will learn about the what and why of Leadership Standard Work. Also, will be introduced to the "Tri-Fold" which will detail the daily, weekly and monthly responsibilites of each level of management including the Plant 1 hr. Manager, Team Leader and Production Supervisor Experienced Classroom This course explains why eliminating waste (non-value-added activities) relates directly to the five principles of Lean. In addition to learning how to identify each type of waste, students discover the three rules of waste and the three key questions that define value. A helpful acronym is included for recalling the eight types of waste. 43 min. Basic At the end of the module, participants will be able to define and identify examples of the Eight Types of Waste (Waiting, Over Production, Rework, Motion, Processing, Inventory, Intellect and Transportation). The key drivers of waste (overburden, unevenness and current process methods) will be 1 hr. 30 min. stressed as areas to address. Basic Classroom Participants will learn about and practice the definition of "Value" from a Lean perspective (Customer willing to pay, transform the shape or content of the input, right the first time). Participants will be required to examine a flowchart and determine which steps are "Value Added" and which steps are "Non Value Added". The what, how and why of SIPOC diagrams will be reviewed 1 hr. and participants will be able to construct one for their project. Basic Classroom At the end of this module, participants will be able to define what Kaizen is, describe the 5 steps of SCORE, explain how to do a SCORE event and be 45 min. prepared to run a simulation Experienced Classroom Participants will be able to define Visual management, describe what is required to establish process control, specify how visual management enables process control, learn about a 5 step process for impelementing 1 hr. 30 min. visual management, and observe application examples Basic Classroom 1 hr. 30 min. Participants will learn that Rapid Problem Solving is a simple thought process and a problem solving process using Post It Notes. It will include learning about the Basic Tools: Pareto Analysis, Fishbone Diagrams, the 5 Why's, Affinity Diagrams, Effort/Impact Matrix, Action Plans and the use of Visual Results Basic Classroom

20 Total Productive Maintenance The Five Principles of Lean By the end of this module, participants will be able to define Total Productive 1 hr. Maintenance (TPM) and complete the TPM templates Experienced Classroom This module explores the five Principles of Lean: Value, Value Stream Map, 38 min. Flow, Pull and Strive for Perfection. Basic Genba Accountability Genba Leadership Understanding Graphs Level 1 1 hr. 36 min. Understanding Graphs Level 2 2 hr. 26 min. Graphical Methods Participants will learn about Process Control and the daily, weekly, and monthly systematic use of Visual Management to support it. Module will include defining, displaying and using controllable metrics along with QDIP 1 hr. 30 min. boards (Quality, Delivery, Inventory and Productivity) to support the effort. Experienced Classroom Participants will learn the fundamental of Genba Leadership as a cascading daily management meeting structure and genba walks. Methods to implement Genba Leadership include having daily tiered meeting structures, assessing the quality of the daily meetings, and how to complete a daily operational 1 hr. genba walk. Experienced Classroom Graphing data is the best way to communicate results. This course explains how to understand data and convert it into useful, visual information. Individuals responsible for collecting, presenting, and/or analyzing data will find this module of great value. Basic 2 hr. Graphing data is the best way to communicate results. This course explains how to understand data and convert it into useful, visual information. Individuals responsible for collecting, presenting, and/or analyzing data will find this module of great value. Advanced Using Minitab, participants will be able to apply the standard tools for graphical analysis for individual points (Scatter plots, histograms, box plots, Individual value plots) and group averages (Main effects, Interaction Plots, Interval plots) Basic Classroom Introduction to Surveys Understanding What to Measure By the end of this module, participants will be able to define Survey Forms, Data Categories,Service Quality Dimensions, Survey Problems, Structured 1 hr. 30 min. and Open Ended Questions, Survey Sampling and Survey Analysis Experienced Classroom This module introduces a generic process model and discusses how a process transforms inputs into outputs. In others words, it illustrates how Output Y is a function of Input X. To measure process performance, the input, process and output variables should be documented to get the complete 13 min. picture. Experienced