Statistical Process Control (SPC exercise)

Statistical Process Control is a very significant exercise in Lean Six Sigma. It helps in analysing the process behaviour to identify the stability & capability of the processes. SPC determines critical control points in a process which impacts the quality of a product. Statistical Control Charts can obtain signals about when the process needs attention and when the process is best left alone.

  • Monitor process behaviour and learn decision making based on analysis.
  • Effectively apply SPC techniques and calculations in the MEASURE, ANALYZE, and CONTROL phases of a process improvement project.
  • Use of appropriate control chart to determine upper and lower limits for a given process
  • Develop a sub-grouping strategy
  • Construct and interpret histogram, trend chart, process control charts for variable and attribute data
  • Ability to track process performance on a real-time basis, allowing for corrective actions to be taken before failure occurs.
  • Ability to understand metrics to aid in decision making
  • Apply techniques and tools for process improvement decisions
  • Ability to reduce variability in the process
  • Anyone who wish to understand & implement SPC techniques in a process
  • QA team – QA managers, Quality engineers, Quality analysts, Quality auditors, Quality technicians and SPC coordinators.
  • Manufacturing engineers, Technical warranty managers, CQI coordinators

Statistical process control

Statistical process control
Introduction to SPC
Purpose & Terminology
Overview of process variation through simulation
Understanding Normal distribution and variation
Types of Data
Control charts – Continuous data charts & variable data charts including CUSUM &EWMA exercises
Introduction to Minitab 17 Software
Control chart exerises using Minitab 17 software
Process capabilty analysis- Cp,Cpk,Pp,Ppk
Process capabilty analysis exercise using Minitab

Measurement System Analysis (MSA Simulation)

MSA is a technique to find out the credibility of the data used for analysis. This tools helps to identify measurement variation during the data collection process. MSA simulation course enables to understand the calculation methodologies, measurement errors. In this course, one can learn the basics of measurements, quantifying variation, errors, sources of errors and eliminate them.

  • Learn about measurement uncertainty and sources of error
  • Theoretical and practical MSA fundamentals for Continuous & Discrete data
  • Learn sources of variation, gauging R&R(repeatability and reproducibility) and tools to determine these factors
  • Ability to understand and quantify the variation in measurement systems.
  • Apply this data to identify measurement variation.
  • Apply this knowledge for measurement improvement
  • Quality Managers, Quality Engineers and Lab Technicians, those interested in auditing MSA
  • Team members involved in planning, using and maintaining measurement systems.
  • Engineers and those responsible for process improvements

Measurement System Analysis

Measurement System Analysis
Introduction to MSA
Purpose & Terminology
Statistical properties of Measurement systems
Understanding Normal distribution and variation
Types of Data
Overview of control charts. Average & Range charts, Capabilty analysis
Measurement Equipment analysis. Bias, Accuracy, Linearity & Stabilty
Introduction to Minitab Software
Gage R&R. (Averge & Range method) Anova method
Operational Definition, Data Collection Plan
Attribute Agreement Analysis.

Lean Workshop

Lean workshop is meant for individuals keen on understanding and implementing Lean principles which deals with identifying and eliminating waste processes and improving process efficiency by doing only what is required at the right time. Unnecessary tasks, labor, inventory and costs are avoided using these principles.

  • Comprehend the concept of Lean and its principles
  • Learn and understand Lean tools and methods
  • Classify roles and responsibility of various team members
  • Understanding significance of implementing Lean principles in an organization
  • Case studies to understand theoretical and practical knowledge of Lean principles
  • Impediments while applying lean principles in a process and solutions for the same
  • Proficiency in Lean principles, terminology and concepts
  • Hands on knowledge of using tools learnt through simulations
  • Ability to implement the concepts in process improvement
  • Beginners to intermediate level individuals interested in process improvement
  • Any team member contributing to process efficiency improvement irrespective of seniority

Lean Master Tool Kit

Lean Master Tool Kit
Lean History/ Lean Motive: Order to Cash Cycle
Lean Basic Principles
A3 Report
Value Series Taichi Ohno Circle
Genchi Genbutsu
Muri – Mura – Muda
Current and Future State VSM
Value Waste Analysis
Value Stream Mapping Value added activities
Value Enabling
Standardization
Standard Sequence, Standard WIP
Takt Time
Time Analysis Time Trap Analysis / Constraint Analysis
Little’s Law – Lead Time Calculations
Process Cycle Efficiency
Cellular Manufacturing
Control Jidoka, Poka Yoke
Levels, Outcomes
Flow Management Line Balancing
Inventory Management
Visual Management and Work Place Organization
Super Market Pull, FIFO Pull
Pull Khanban, Khanban card calculation
Heijunka – Level Pull
SMED
Perfection Just In Time – System Integration
Kaizen – Process and Flow

Managerial Statistics for Decision making

Decision making in any organization is done based on thorough statistical analysis. This requires individuals involved in decision making to have a strong base on concepts such as probability, statistics, estimation, hypothesis, sampling distributions, regression and so on.

  • Understand terminology and concepts involved in managerial statistics
  • Implement the statistical calculations to extrapolate managerial decisions
  • Determine correlation or regression in process to suggest steps for process excellence.
  • Develop critical and integrative thinking to effectively sum up the solution to the problem in the process
  • Contribute towards decision making by analysing and developing statistical data
  • Ability to make sound decisions based on calculated statistics
  • Analyze and collect data that is required for process improvement
  • Management trainees, team members contributing to decision making process
  • Team members involved in process excellence

MS Modules

MS Modules
Stem and Leaf Display
Histogram and Frequency Polygon for Variables
Basic Statistical Concepts Measures of Central
Tendency
Coefficient of Variation
Box Plot
Probability Distributions
Null and Alternative Hypothesis
Steps in Hypothesis Testing
Tests for Population Mean
Hypothesis Testing Hypothesis Testing for the Equality of Two Means
Hypothesis Testing for the Equality of Two Variables
Hypothesis Testing for the Equality of Two Proportions
Chi Square (x2) Tests of Hypothesis
Multi collinearty
Matrix Plot
Correlation-Regression Analysis Linear Regression and
Multiple Regression
Logistic Regression
Logistic Regression
One-way Analysis of Variance
Analysis of Variance Two-way Analysis of
Variance
Two-way Analysis of Variance
Software Applications
Decision Theory

Design of experiments

In order to identify factors and variables that can significantly impact the quality of the process, a scientific method should be adopted while designing an experiment for the same. When a strategically planned experiment with closely monitored variables is conducted, one can generate lot of information that is required for optimizing the process for improving process efficiency. This is possible through design of experiments (DOE)

  • Identify variables and other essentials that need to be varied for the experiment
  • Construct an experiment model
  • Identify potential errors, probability and effects
  • Understand and apply experiment fundamentals
  • Graphical representation to analyze data
  • Ability to design and implement experiments for required factor
  • Analyze the effects of the experiment to tabulate results
  • Enable decision making based on results of experiment
  • Quality managers, quality engineers, SPC coordinators
  • Consultants, design engineers, R&D personnel and product/process engineers.

DOE Modules

Design of Experiments (DOE)
History of DoE
Data Collection, Operational Definition
Pre DoE Repeatability and Reproducibility
Study
Hypothesis Testing Fundamentals
Basic Hypothesis Test Experiments and Regression Model
Key Terminologies of DoE, Screening, Refining and Optimizing Designs
Steps to Conduct an Experiment, Full Factorial and Fractional Factorial Experiments
DoE Analyze Output and Graphs: Factorial Design, Factorial Plots and Interaction Plots
Response Surface Designs & Response Optimizer
Taguchi Desgins Overview

Failure mode & effect analysis

Failure mode & effect analysis (FMEA) enables the team to identify possible failures in the existing process or a new one. The cause, impact and resolution for the failure can then be evaluated and corrected. FMEA involves following certain methods, procedures, documentation and software which enables failure detection and analysis.

  • Learn the basics of FMEA, benefits, methods, tools

  • Understand usage and significance of Severity, Occurrence, Detection Scales
  • Calculation of Risk Priority Number (RPN) and how to Prioritize RPNs
  • Application of FMEA concepts in practical projects
  • Learn how to Discern Recommended Corrective Actions and Risk Mitigation
  • Ability to identify potential failure and it cause using FMEA tools and methods
  • Aid in cost saving and improving efficiency by capturing failure at the right time and stage of a process

  • Contribute towards preventive actions prior to actual occurrence of failure
  • Design/ process managers and engineers

  • Individuals in the fields of manufacturing, quality assurance, reliability research, development, and safety engineering.
  • Managers, supervisors and employees who are responsible for quality defect prevention
  • Team members involved in a support role

FMEA

FMEA
FMEA Process Overview Introduction and course objectives
The History and purpose of FMEA
FMEA in product development process
System/ subsystem/ component FMEA
FMEA Methodology FMEA development methodology- The three path model
Team structure and rules for efficiency
FMEA Linkage and Collaboration The link between Design and Process FMEA
What is Risk
RPN
Failure Mode Avoidance
Practical application of the Design FMEA technique Interface analysis/ Boundary Diagram
Parameter Diagram
DFMEA closure Design review integration
Test plan development
Failure Mode Avoidance

7 QC tools

7 QC tools or 7 Quality Check Tools have been in use since a few decades. Propagated by a Japanese professor, Kaoru Ishikawa, these tools are as follows:

  • Cause-and-effect diagram (also called Ishikawa or fishbone chart)
  • Check Sheet
  • Control charts
  • Histogram
  • Pareto chart
  • Scatter diagram
  • Stratification
  • Learn Cause and effect diagram: This aids in identifying possible causes for an issue. Further categorizes solutions and conclusions.
  • Learn updating a Check sheet: A sheet for collecting, tabulating and analysing data in order to study patterns, effects and design experiments.
  • Control chart design and development to study process changes over time.
  • Understanding how to develop Histogram to show frequency distributions
  • Learn to construct a Pareto chart indicating significant factors of a process on a bar graph
  • Develop a Scatter diagram which are graphs pairs of numerical data, one variable on each axis, to look for a relationship.
  • Learn stratification to identify patterns in various sources of data
  • Understand and master the 7 QC tools in order to contribute effectively in the process improvement projects

  • Become proficient in collecting and analyzing data and its patterns
  • QMR, QA Managers, QC Inspectors, QA Engineers, Inspectors, Quality Control Engineers

  • Those involved in MSA, SPC processes of six sigma
  • Production Engineers, Machinists, Supplier Quality personnel, Process Design Engineers, Executives and Process Owners from Manufacturing units etc.

7 QC

7 QC
Procedures for Problem solving Making use of data to increase productivity
Applying the 7 QC tools towards problem solving
Plotting Pareto Diagrams
The Pareto Diagram Classify the defects and display using Pareto Diagram
Identify the problems in their order of severity
Plotting Fishbone Diagram
Fishbone Diagram (Cause & Effect Diagram) Geberating probable causes for every defect
Brainstorm technique
Process Flow Chart Ploting Process Flow Chart
Interpretation of PFC
Design review integration
Method to note data Prevention of inspect slip-throughs
Plotting checksheet for convenient usage
Predict occurence of defects
Histogram Plotting Histogram
Interpretation of shapes in a distribution diagram
Scatter Diagram Plotting Scatter Diagram
Interpretation of Scatter Diagram
Control Charts Occurence of Defects
Interpretation of a process with control charts

5S

5S is a work place organization regime that ensures efficiency of process, labor, decision making by following the 5 principles – Sort (Seiri), Set In Order (Seiton), Shine(Seiso), Standardize (Seiketsu), Sustain (Shitsuke). Each of these help maintain and improvise a process and its corresponding workspace.

  • Understand and implement concepts of 5S
  • Learn concept of Sort (Seiri) wherein we sort out the process by identifying and removing unwanted material, process, labor, data, obstacles, etc
  • Learn concept of Set in Order (Seiton) which involves categorizing and filing items, files, processes, data and such materials that are critical in the process
  • Learn the concept of Shine (Seiso) which involves keeping the workspace clean and tidy
  • Learn the concept of Standardize (Seiketsu) which requires the process to have predefined methods, systematic procedures which need to followed in order to have a profitable and organized process
  • Learn the concept of Sustain (Shitsuke) which requires to maintain discipline, regular audits and training to keep the process and the team members updated and functioning soundly.
  • Get an all round idea of running a process effectively using concepts of 5S

  • Contribute in respective roles optimally without requirement of much mentoring
  • All team members of an active team within a process or organization
  • Anyone interested in improving process efficiency

5S

5S
What is 5s?
Origin of 5s Where it came from?
Benefits
Clearing the work area
The 5s methodology unpacked Sort (Seiri) Determine what you need
Set in Order (Seiso) Designated locations
Design your workplace for efficiency
Spic and span
Shine (Seiton) Creating cleaning routines
Making it routine
Standardize (Seiketsu) Design systems to ensure new norms
The benefits of 5S
Changing the future
Sustain (Shitsuke) Techniques to prevent old habits
The benefits of 5S
Zones & Zone members
Red tagging activity
Implemetation of 5S challenges faced during deployment
Tips for effective 5S