Friday, July 3, 2015

Quality Engineering and Management

Week 1:

Defining Quality
Understanding Customer Expectations
DMAIC

Intro - Define:

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Defining Quality:

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Understanding Customer Expectations:

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DMAIC - Define, Measure, Analyse, Improve, Control:

PROJECT: Define - Defining Customer Expectations, Basic Process Understanding:

This an overview of the DMAIC steps: DefineMeasureAnalyzeImproveControl. The learning objectives for each of the DMAIC step are listed below.


Define: During this step of our project, you, the project leader, are responsible for determining the (target) customer’s expectations for a hiking boot, for gaining a basic understanding of the hiking boot production process flow and identifying the outputs which are critical to quality. In an actual project, you would also be responsible for establishing a project team and project charter, including setting up a project timeline and estimating the costs.
In this hiking boot scenario, the learning objectives for Define are:
  1. Specify the customer expectations for quality parameters in a hiking boot.
  2. Identify the process output which is critical to quality for the hiking boot.
  3. Gain a basic understanding of the production process flow.
Measure: In the Measure phase of our project you will measure and analyze the critical to quality output identified in the Define phase. This will establish the baseline process performance with respect to the goal of the process improvement project. You and your project team then need to understand the hiking boot production process in as much detail as possible by creating a detailed process map. The process map is carefully reviewed in order to identify the parameters which are likely to influence the critical to quality output. In an actual project, a data collection plan would be developed and implemented for these parameters.
In this hiking boot scenario, the learning objectives for Measure are:
  1. Establish the baseline process performance with respect to the customer expectations.
  2. Using the given process flow, identify the key parameters to be measured which are likely to influence the critical to quality output.
Analyze: During this step of our project, the project team will analyze the data for the key process parameters identified in Measure which are likely to influence the critical to quality output. In Analyze, the object is to establish the root cause of the process deviation or process problem by confirming (or not) the effect of these parameters on the output. In an actual project, this phase could include additional work to identify potential causes, development of Cause and Effect diagrams to help prioritize the work.
In this hiking boot scenario, the learning objective for Analyze is:
  1. Using the key parameters which are likely to influence the critical to quality output, perform correlation analysis to determine root cause.
Improve: During this step of the project, your project team will propose a hypothesis for a process change in order to effect the process improvement. Identify a solution and demonstrate that the solution does effect the desired process improvement.
In this hiking boot scenario, the learning objectives for Improve are:
  1. Establish a hypothesis to be tested.
  2. Analyse the data for the new process to show that the implemented changes result in an improved process and quantify this improvement.
Control: In the final step of the project of the DMAIC process improvement cycle, the goal is to ensure that the improvement gains are maintained over the long term. Here it is important to implement standardized documentation, employee training and on-going process monitoring.

Practice - Defining Quality:

Manufacturing Process

Cold Delight is one of the biggest brands of frozen desserts and dairy products within the United States. Cold Delight sells its products to end customers and also to wholesale retailers such as Wal-Mart. Cold Delight was founded in 1956 and it has a range of different products such as: shave ice, sorbet, snow cones (based on flavored water), sorbet (based on fruit purées, ice creams and frozen yogurt (based on milk and cream), frozen custard (based on custard) and others. Within the dairy products they produce butter, buttermilk, cheese, cream etc. Recently, Cold Delight has been experiencing revenue losses and even though they are not that big, your boss is concerned that if the trend goes on, it might affect this year’s profits. In order to find out why revenues are dropping, the company performed a questionnaire to its customers, asking them to give feedback on your products. Some of the responses of the customers are quoted below:
“The texture of the ice cream is poor. It is too watery.”
“This chocolate ice cream does not taste as chocolate! It tastes like dirty feet!”
“I just bought a 500ml ice cream the other day and for my surprise, when I opened the box, it was clear there was less than 500ml inside!”
“This ice cream is not worth the price.”
A retailer said: “we were supposed to get your product every Friday and it’s been two weeks in a row that we cannot supply our customers"

Answer:

Problem 1: Ice cream quality --> consistency is poor (Ice cream is too watery)

Problem 2: Ice cream quality --> taste is poor (This chocolate ice cream does not taste like chocolate!)

Problem 3: Ice cream availability (quantity) --> too little ice cream in serving size of 500ml (There was less than 500ml inside!)

Problem 4: Ice cream consumption of resources --> too many or too expensive resources used, so price is high (Too expensive product!)

Problem 5: Ice cream availability (time) --> Late delivery of the products!









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Week 2:

Introduction:

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Probability Vs Statistics:

Link

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Random Variables & Probability Distribution:

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Random Variable: Intensity of Rainfall


1. Probability Distributions, Mean & Variance:

Link

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2. Probability Distributions, Mean & Variance:

Link

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Important Probability Distributions:

Link

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Week 3:

Introduction

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The normal Distribution:

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Example of normally distributed variable:


The Normal Distribution:

Link

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The Normal Distribution:

Link

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Central Limit Theorem:

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Central Limit Theorem:

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PROJECT: Measure - Establish Baseline Process Performance










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Week 4:

Introduction

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Measurement Theory and Sampling Plans

Link

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Measurement Theory and Sampling Plans

Link

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Descriptive vs Inferential Statistics

Link

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Case example - Descriptive Statistics

Link

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Descriptive vs Inferential Statistics

Link

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Project: Measure - Process Mapping





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Week 5:

Introduction:

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Confidence Intervals:


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Example - Confidence Intervals - Table Factory:




Confidence Intervals:


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Hypothesis Testing:


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Hypothesis Testing:


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Hypothesis Testing:


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Week 6:

Introduction

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Process Capability:


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Qualitative Look at CP/CPK:


Process Capability:


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Regression & Correlation:


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Project: Root cause analysis







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Week 7:

Introduction

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Design of Experiments

Link

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Design of Experiments

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Design of Experiments

Link

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Significance of Effects (Analysis of Variance)

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Significance of Effects (Analysis of Variance)

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Project: Improving the process















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Week 8:

Introduction:

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Process Control and Control Charts:


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X - Bar & R - Charts:


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Example X-Bar and R-Charts (Part 1):


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X-Bar and R-Charts:


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Example X-Bar and R-Charts (Part 2):


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Rational Sub-grouping:

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Case Study: SPC at Melon Helmets












Project: Control







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Week 9: Six Sigma

Introduction:

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Application: Six Sigma DEFINE and MEASURE



Sigma Guide: Excel-based tool for DEFINE

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Week 10:

Introduction

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Application: Six-sigma Analyze


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Optional: Minitab files for Six-sigma application


Application: Six-sigma improve and control


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Course Close

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