• برامج إدارة الجودة

    Lean Six Sigma Yellow Belt Training Course برنامج لين 6 سيقما الحزام الاصفر   Yellow Belt Certificate Overview: Lean Six Sigma Yellow Belt training provides insight to the techniques of Six Sigma, its metrics, and basic improvement methodologies. A yellow belt certifies knowledge of how to integrate Six Sigma methodologies for the improvement of production and transactional systems to better meet customer expectations and bottom-line objectives of their organization.   The Responsibilities of a Yellow Belt: A Yellow Belt typically has a basic knowledge of Six Sigma, but does not lead projects on their own. They are often responsible for the development of process maps to support Six Sigma projects. A Yellow Belt participates as a core team member or subject matter expert (SME) on a project or projects. In addition, Yellow Belts may often be responsible for running smaller process improvement projects using the PDCA (Plan, Do, Check, Act) methodology. PDCA, often referred to as the Deming Wheel, enables Yellow Belts to identify processes that could benefit from improvement. These smaller Yellow Belt projects often get escalated to the Green Belt or Black Belt level where a DMAIC methodology is used to maximize cost savings using Statistical Process Control.   What Training Provides: Lean Six Sigma Yellow Belt training provides an introduction to process management and the basic tools of Six Sigma, giving employees a stronger understanding of processes, enabling each individual to provide meaningful assistance in achieving the organization’s overall objectives. Our Six Sigma Yellow Belt certification also improves: §The effectiveness of employees in their support role of Six Sigma §Personnel buy-in of Six Sigma §Day-to-day workplace activities (resulting in a reduction of cycle times, improved quality, and less waste).   Introductory Training in the Fundamentals of Lean Six Sigma: The Yellow Belt gathers data, participates in problem-solving exercises and adds their personal experiences to the exploration process. Not only do Yellow Belts gain the skills necessary to identify, monitor and control profit-eating practices in their own processes, but they are also prepared to feed that information to Black Belts and Green Belts working on larger system projects. Program Language: üAll Material in English üSome explanation in Arabic   Program Date, Duration & Venue: Date: Determine later Duration: 3 days (21 hour) Venue: Khartoum – Sudan     Lean Six Sigma Green Belt Training Course برنامج لين 6 سيقما الحزام الاخضر Overview: If you asking for: Higher Customer Satisfaction, Shorter Lead Time, Higher Flexibility, Higher Quality, Lower Costs and Higher Employee Satisfaction. And you need to: Reduced cycle times (product development and production), Increased quality, Reduced costs and inventory, Increased capacity potential, Improved customer service, High levels of worker, involvement, ownership and commitment and Improved financial returns .. go lean … go green. Green Belt is not just a role, it is also a competency required for leadership positions at many top companies. This learning series is designed to enable participants to fulfill the important role of a Lean Six Sigma Green Belt and to incorporate the Lean Six Sigma mindset into their leadership skills. Participants will learn how to collect data and turn it into useful information using Minitab – software. Using a real world project focus, the series will teach the fundamental methodology, tools and techniques of the Define, Measure, Analyze, Improve and Control (DMAIC) Process Improvement Methodology.   The Program teaches the fundamentals, techniques and follow-up skills necessary to achieve measurable results from the shop floor to the top floor. The program is conducted in a dynamic learning environment using performance and process simulation, lecture, , videos, selected hands-on activities and case study discussions. During the course, students complete a group/individual project focused on actual workplace application of the lean principles. Upon completion, students will possess a complete framework for the successful lean implementation and deployment within their own operation. Program Objectives: To give a basic understanding of: §Overview of Lean Six Sigma Methodology §To understand a common definition and concepts of Lean Manufacturing §To understand Benefits of Lean Manufacturing and Lean principles §Be able to identify manufacturing system wastes §To provide an overview of the Lean tools and techniques §Analyze data Using Minitab statistical software §Six Sigma projects selection and implementation §Over view of Six Sigma Project execution (DMAIC) (Define-Measure-Analyze-Improve & Control) §Define tools such as Identify Project CTQs, Team Charter, High Level Process Maps etc., §Type of Data, Sample Size determination for a given confidence level and Data Collection, Planning including use of Prioritization Matrix and/or FMEA, Customer QFD etc., §Measurement System Evaluation (Gauge R&R) for variables as well as attribute data. §Understanding variation-special causes vs. common causes §Analyze tools -Evaluation of Process Capability and assessment of Sigma level §Process Mapping including, identification of value added and non value added activities §Organizing for potential causes using XY Matrix, cause and effect, FMEA & Tree Diagram §Concept of correlation and Regression and use of the same in validating causes §Select and prioritize solutions for the validated causes including concept of Risk Analysis using FMEA. §Develop plan for pilot and full scale implementation §Control tools -Concept and Examples of Poke Yoke, Visual Workplace and 5S §Evaluation and monitoring mechanism (like control chart for controlling purposes, Process audit, Surveillance) of results after implementation of the solutions §Institutionalization and integration of the solution     Contents: §Introduction to Lean Six Sigma vSix sigma foundation vValue of Six Sigma vOrganizational drivers and metrics vOrganizational goals and six sigma projects vLean concepts and tools vValue-added and non-value-added activities vLean Six Sigma combination §Define phase vIdentify customers vCollect customer data vAnalyze customer data vTranslate customer requirements vCustomer Voice Chart vKano Model vCTQ Matrix vCTB Matrix vProject charter and problem statement vProject scope, metrics, and planning vSIPOC vProcess Mapping vVSM (Value Stream Mapping) §Measure phase vProcess modeling vProcess inputs and outputs v Basic probability concepts vTypes of data and measurements scales vData collection methods vTechniques for assuring data accuracy And integrity vDescriptive statistics vProbability distributions vMeasurement system analysis vProcess capability and performance vProcess capability studies vProcess performance vs. specification vProcess capability indices vProcess performance indices vShort-term vs. long-term capability vProcess capability for attributes data   §Analysis phase vIntroduction to Analyze vRoot Cause Analysis v5 whys vGraphs & Histograms vPareto Analysis vCause and effect diagram vBrain Storming vBenchmarking vUse of matrix v Failure Modes & Effects Analysis vCorrelation and Regression §Improve phase vIntroduction to Improve phase vDetermine the Vital Few X’s vList Solutions for all Critical Inputs vPilot Solutions v5 S and Visual management vPilot Solutions vJIT (Just in Time) Production vStandard work vTakt time vKanban – Pull production vSEMD vEvaluation vHypothesis Testing vDesign of experiments DOE §Control phase vIntroduction to control phase vEstablish and implement Six Sigma Control Plan vTraining Plan vDocumentation Plan vMonitoring Plan vResponse Plan vStatistical Process Control vPoka Yoke vTotal Productive Maintenance vVisual board, Obeya v(Jidoka) – Root Cause Analysis vKaizen (continuous improvement) vAligning Systems & Structures vSix Sigma Project closing   Who Should Attend This course is suitable for quality professionals, six sigma change agents, lean practitioners, Departmental Managers, Industrial engineers and analysts, Maintenance engineers, Design and manufacturing and production engineers, Quality inspectors and managers, Machine operators and producers, Lean enterprise champions and drivers and support staff who require a basic understanding of Statistical Process Control tools and techniques and the potential benefits (supported by examples) of understanding process behavior.     Program Date, Duration & Venue: Date: Determine later Duration: 8 days (56 hour) Khartoum – Sudan     Lean Six Sigma Black Belt Training Course برنامج لين 6 سيقما الحزام الاسود   Overview: The overarching learning objective of this course is to develop a comprehensive set of skills that will allow you to function effectively as a Six Sigma Black Belt. The Black Belt body of knowledge includes techniques for both quantitative and non-quantitative analysis, as well as the team leadership skills necessary to get projects across the goal line. This course cover the Six Sigma DMAIC methodology and integrated lean tools and techniques. Program Objectives: ØEmploy your Lean Six Sigma skills to successfully lead a process improvement project that delivers meaningful results to your organization. ØCommunicate using Lean Six Sigma concepts. ØThink about your organization as a collection of processes, with inputs that determine the output. ØRelate Lean Six Sigma concepts to the overall business mission and objectives. ØUnderstand and apply the five-step D-M-A-I-C model as a framework to organize process improvement activities. ØEmploy a wide range of process improvement techniques, including design of experiments. ØRecognize the organizational factors that are necessary groundwork for a successful Lean Six Sigma effort. Contents: §Introduction to Lean Six Sigma vThe Basics of Six Sigma vMeanings of Six Sigma vGeneral History of Six Sigma & Continuous Improvement vThe Fundamentals of Six Sigma vBasic Six Sigma Metrics va. including DPU, DPMO, FTY, RTY Cycle Time, … vCost of Poor Quality (COPQ) vThe Problem Solving Strategy Y = f(x) vThe Lean Enterprise vUnderstanding Lean vThe History of Lean vThe Seven Elements of Waste vOverproduction, Correction, Inventory, Motion, Overprocessing, Conveyance, Waiting. vLean & Six Sigma vLean Six Sigma Roles & Responsibilities vSelecting Lean Six Sigma Projects vDeveloping Project Metrics vDeliverables of a Lean Six Sigma Project vFinancial Evaluation & Benefits Capture   §Define phase: oA. Voice of the customer vCustomer identification - Segment customers for each project and show how the project will impact both internal and external customers. (Apply) vCustomer feedback -Identify and select the appropriate data collection method (surveys, focus groups, interviews, observation, etc.) to gather customer feedback to better understand customer needs, expectations and requirements. Ensure that the instruments used are reviewed for validity and reliability to avoid introducing bias or ambiguity in the responses. (Apply) vCustomer requirements -Define, select and use appropriate tools to determine customer requirements, such as CTQ flow-down, quality function deployment (QFD) and the Kano model. (Apply) oB. Project charter vProblem statement -Develop and evaluate the problem statement in relation to the project’s baseline performance and improvement goals. (Create) vProject scope -Develop and review project boundaries to ensure that the project has value to the customer. (Analyze) vGoals and objectives -Develop the goals and objectives for the project on the basis of the problem statement and scope. (Apply) vProject performance measures -Identify and evaluate performance measurements (e.g., cost, revenue, schedule, etc.) that connect critical elements of the process to key outputs. (Analyze) oC. Project tracking -Identify, develop and use project management tools, such as schedules, Gantt charts, toll-gate reviews, etc., to track project progress. (Create) - §Measure phase: oA. Process characteristics vInput and output variables -Identify these process variables and evaluate their relationships using SIPOC and other tools. (Evaluate) vProcess flow metrics -Evaluate process flow and utilization to identify waste and constraints by analyzing work in progress (WIP), work in queue (WIQ), touch time, takt time, cycle time, throughput, etc. (Evaluate) vProcess analysis tools -Analyze processes by developing and using value stream maps, process maps, flowcharts, procedures, work instructions, spaghetti diagrams, circle diagrams, etc. (Analyze) oB. Data collection vTypes of data - Define, classify and evaluate qualitative and quantitative data, continuous (variables) and discrete (attributes) data and convert attributes data to variables measures when appropriate. (Evaluate)   vMeasurement scales - Define and apply nominal, ordinal, interval and ratio measurement scales. (Apply) vSampling methods - Define and apply the concepts related to sampling (e.g., representative selection, homogeneity, bias, etc.). Select and use appropriate sampling methods (e.g., random sampling, stratified sampling, systematic sampling, etc.) that ensure the integrity of data. (Evaluate) vCollecting data -Develop data collection plans, including consideration of how the data will be collected (e.g., check sheets, data coding techniques, automated data collection, etc.) and how it will be used. (Apply) oC. Measurement systems vMeasurement methods - Define and describe measurement methods for both continuous and discrete data. (Understand) vMeasurement systems analysis - Use various analytical methods (e.g., repeatability and reproducibility (R&R), correlation, bias, linearity, precision to tolerance, percent agreement, etc.) to analyze and interpret measurement system capability for variables and attributes measurement systems. (Evaluate) v Metrology -Define and describe elements of metrology, including calibration systems, traceability to reference standards, the control and integrity of standards and measurement devices, etc. (Understand). oD. Basic statistics vBasic terms - Define and distinguish between population parameters and sample statistics (e.g., proportion, mean, standard deviation, etc.) (Apply) vCentral limit theorem - Describe and use this theorem and apply the sampling distribution of the mean to inferential statistics for confidence intervals, control charts, etc. (Apply) vDescriptive statistics - Calculate and interpret measures of dispersion and central tendency and construct and interpret frequency distributions and cumulative frequency distributions. (Evaluate) vGraphical methods - Construct and interpret diagrams and charts, including box-and-whisker plots, run charts, scatter diagrams, histograms, normal probability plots, etc. (Evaluate) vValid statistical conclusions -Define and distinguish between enumerative (descriptive) and analytic (inferential) statistical studies and evaluate their results to draw valid conclusions. (Evaluate) oE. Probability vBasic concepts Describe and apply probability concepts such as independence, mutually exclusive events, multiplication rules, and complementary probability, joint occurrence of events, etc. (Apply) vCommonly used distributions - Describe, apply and interpret the following distributions: normal, Poisson, binomial, chi square, Student’s t and F distributions. (Evaluate) vOther distributions Describe when and how to use the following distributions: hypergeometric, bivariate, exponential, lognormal and Weibull. (Apply). - - - oC. Measurement systems vMeasurement methods - Define and describe measurement methods for both continuous and discrete data. (Understand) vMeasurement systems analysis - Use various analytical methods (e.g., repeatability and reproducibility (R&R), correlation, bias, linearity, precision to tolerance, percent agreement, etc.) to analyze and interpret measurement system capability for variables and attributes measurement systems. (Evaluate) v Metrology -Define and describe elements of metrology, including calibration systems, traceability to reference standards, the control and integrity of standards and measurement devices, etc. (Understand). oF. Process capability vProcess capability indices - Define, select and calculate Cp and Cpk to assess process capability. (Evaluate) vProcess performance indices - Define, select and calculate Pp, Ppk and Cpm to assess process performance. (Evaluate) vShort-term and long-term capability - Describe and use appropriate assumptions and conventions when only short-term data or attributes data are available and when long-term data are available. Interpret the relationship between long-term and short-term capability. (Evaluate) vProcess capability for non-normal data - Identify non-normal data and determine when it is appropriate to use Box-Cox or other transformation techniques. (Apply) vProcess capability for attributes data - Calculate the process capability and process sigma level for attributes data. (Apply) vProcess capability studies - Describe and apply elements of designing and conducting process capability studies, including identifying characteristics and specifications, developing sampling plans and verifying stability and normality. (Evaluate) vProcess performance vs. specification -Distinguish between natural process limits and specification limits, and calculate process performance metrics such as percent defective, parts per million (PPM), defects per million opportunities (DPMO), defects per unit (DPU), process sigma, rolled throughput yield (RTY), etc. (Evaluate)   §Analysis phase o A. Measuring and modeling relationships between variables vCorrelation coefficient - Calculate and interpret the correlation coefficient and its confidence interval, and describe the difference between correlation and causation. (Analyze) vRegression - Calculate and interpret regression analysis, and apply and interpret hypothesis tests for regression statistics. Use the regression model for estimation and prediction, analyze the uncertainty in the estimate, and perform a residuals analysis to validate the model. (Evaluate) vMultivariate tools - Use and interpret multivariate tools such as principal components, factor analysis, discriminant analysis, multiple analysis of variance (MANOVA), etc., to investigate sources of variation. (Analyze)   vMulti-vari studies - Use and interpret charts of these studies and determine the difference between positional, cyclical and temporal variation. (Analyze) vAttributes data analysis -Analyze attributes data using logistic regression, etc., to investigate sources of variation. (Analyze)   oB. Hypothesis testing vTerminology - Define and interpret the significance level, power, type I and type II errors of statistical tests. (Evaluate) vStatistical vs. practical significance - Define, compare and interpret statistical and practical significance. (Evaluate) vSample size - Calculate sample size for common hypothesis tests (e.g., equality of means, equality of proportions, etc.). (Apply) vPoint and interval estimates - Define and distinguish between confidence and prediction intervals. Define and interpret the efficiency and bias of estimators. Calculate tolerance and confidence intervals. (Evaluate) vTests for means, variances and proportions - Use and interpret the results of hypothesis tests for means, variances and proportions. (Evaluate) vAnalysis of variance (ANOVA) - Select, calculate and interpret the results of ANOVAs. (Evaluate) vGoodness-of-fit (chi square) tests - Define, select and interpret the results of these tests. (Evaluate) vNon-parametric tests -Select, develop and use various non-parametric tests, including Mood’s Median, Levene’s test, Kruskal-Wallis, Mann-Whitney, etc. (Evaluate)   oC. Failure mode and effects analysis (FMEA) -Describe the purpose and elements of FMEA, including risk priority number (RPN), and evaluate FMEA results for processes, products and services. Distinguish between design FMEA (DFMEA) and process FMEA (PFMEA), and interpret results from each. (Evaluate)   oD. Additional analysis methods vGap analysis - Use various tools and techniques (gap analysis, scenario planning, etc.) to compare the current and future state in terms of pre-defined metrics. (Analyze) vRoot cause analysis - Define and describe the purpose of root cause analysis, recognize the issues involved in identifying a root cause, and use various tools (e.g., the 5 whys, Pareto charts, fault tree analysis, cause and effect diagrams, etc.) for resolving chronic problems. (Evaluate) vWaste analysis - Identify and interpret the 7 classic wastes (overproduction, inventory, defects, over-processing, waiting, motion and transportation) and other forms of waste such as resource under-utilization, etc. (Analyze) -   - §Improve phase oA. Design of experiments (DOE) vTerminology - Define basic DOE terms, including independent and dependent variables, factors and levels, response, treatment, error, etc. (Understand) vDesign principles - Define and apply DOE principles, including power and sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, resolution, etc. (Apply) vPlanning experiments - Plan, organize and evaluate experiments by determining the objective, selecting factors, responses and measurement methods, choosing the appropriate design, etc. (Evaluate) vOne-factor experiments - Design and conduct completely randomized, randomized block and Latin square designs and evaluate their results. (Evaluate) vTwo-level fractional factorial experiments - Design, analyze and interpret these types of experiments and describe how confounding affects their use. (Evaluate) vFull factorial experiments -Design, conduct and analyze full factorial experiments. (Evaluate) oB. Waste elimination -Select and apply tools and techniques for eliminating or preventing waste, including pull systems, Kanban, 5S, standard work, poka-yoke, etc. (Analyze). oC. Cycle-time reduction -Use various tools and techniques for reducing cycle time, including continuous flow, single-minute exchange of die (SMED), etc. (Analyze) oD. Kaizen and kaizen blitz - Define and distinguish between these two methods and apply them in various situations. (Apply) oE. Theory of constraints (TOC) -Define and describe this concept and its uses. (Understand) oF. Implementation -Develop plans for implementing the improved process (i.e., conduct pilot tests, simulations, etc.), and evaluate results to select the optimum solution. (Evaluate) oG. Risk analysis and mitigation -Use tools such as feasibility studies, SWOT analysis (strengths, weaknesses, opportunities and threats), PEST analysis (political, environmental, social and technological) and consequential metrics to analyze and mitigate risk. (Apply)   §Control phase: oA. Statistical process control (SPC) vObjectives - Define and describe the objectives of SPC, including monitoring and controlling process performance, tracking trends, runs, etc., and reducing variation in a process. (Understand) vSelection of variables - Identify and select critical characteristics for control chart monitoring. (Apply) vRational subgrouping - Define and apply the principle of rational subgrouping. (Apply) - - - - - § - vControl chart selection - Select and use the following control charts in various situations: X¯ – R, X¯ – s, individual and moving range (ImR), p, np, c, u, short-run SPC and moving average. (Apply) vControl chart analysis -Interpret control charts and distinguish between common and special causes using rules for determining statistical control. (Analyze) oB. Other control tools vTotal productive maintenance (TPM) - Define the elements of TPM and describe how it can be used to control the improved process. (Understand) vVisual factory - Define the elements of a visual factory and describe how they can help control the improved process. (Understand) oC. Maintain controls v Measurement system re-analysis - Review and evaluate measurement system capability as process capability improves, and ensure that measurement capability is sufficient for its intended use. (Evaluate) vControl plan - Develop a control plan for ensuring the ongoing success of the improved process including the transfer of responsibility from the project team to the process owner. (Apply) oD. Sustain improvements vLessons learned - Document the lessons learned from all phases of a project and identify how improvements can be replicated and applied to other processes in the organization. (Apply) vTraining plan deployment - Develop and implement training plans to ensure continued support of the improved process. (Apply) vDocumentation - Develop or modify documents including standard operating procedures (SOPs), work instructions, etc., to ensure that the improvements are sustained over time. (Apply) vOngoing evaluation - Identify and apply tools for ongoing evaluation of the improved process, including monitoring for new constraints, additional opportunities for improvement, etc. (Apply)   Who Should Attend: This course is suitable for quality professionals, six sigma change agents, lean practitioners, Departmental Managers, Industrial engineers and analysts, Maintenance engineers, Design and manufacturing and production engineers, Quality inspectors and managers, Machine operators and producers, Lean enterprise champions and drivers and support staff who require a basic understanding of Statistical Process Control tools and techniques and the potential benefits (supported by examples) of understanding process behavior. § -Program Date, Duration & Venue: Date: Determine later Duration: 20 days (140 hour) Khartoum – Sudan            

تسجيل الدورة

الاسم بالكامل

البريد الإلكتروني

الرسالة