Quality Control 7 Basic Tools. Basic Lean improvement tools

Name: Quality Control 7 Basic Tools. Basic Lean improvement tools
Rating: 4.4 (88 reviews)

Understand how the 7 Basic Tools can be used for Quality Control and lean improvements in a process. Producing Gains

Created byMartin Conneely

Last updated 4/2022

English

What you'll learn

Quality Control 7 Basic Tools
Cause & Effect Diagrams. Understand and apply tool to really issues in the operations and the service industry.
Flowcharts. Understand and apply tool to really issues in the operations and the service industry.
Check sheets. Understand and apply tool to really issues in the operations and the service industry.
Pareto Diagrams. Understand and apply tool to really issues in the operations and the service industry.
Histograms. Understand and apply tool to really issues in the operations and the service industry.
Control Charts. Understand and apply tool to really issues in the operations and the service industry.
Scatter Diagrams. Understand and apply tool to really issues in the operations and the service industry.
The student will understand the types of data used in statistics in simple terms.

Course content

1 section • 17 lectures • 2h 53m total length

Lecture 1 Introduction to Quality Control 7 Basic Tools Course5:10
This is an introduction lecture to Quality Control 7 Basic tools. Students will understand the learning outcomes of the course. Students will understand how to get the most benefit from the course content.
Lecture 2 Types of Data6:08
In this lecture students will get an overview on the different types of data that are used in statistics.
Data Type quiz
Lecture 3 Cause-and-effect Diagrams & Brainstorming16:58
Lecture 4 Flow charts15:13
Lecture 5 Check Sheets and Measles Charts15:37
Lecture 6 Pareto Analysis9:57
Lecture 7 Histograms & Tally charts13:16
Lecture 8 Control charts15:24
Lecture 9 Scatter Diagrams7:59
Lecture 10 Types of Attribute charts3:43
Explains four different attribute charts.
Lecture 11 NP Charts8:22
Explain how to create control charts for attribute data
Lecture 12 C Charts7:09
Understand what C chart is and how to create it via excel
Lecture 13 U Charts7:38
Understand what a U chart is. When to us them and how to create a U chart in excel.
Lecture 14 P Charts6:48
What will we learn?
When do we use an P chart.
How to create a P chart via excel.
Lecture 15 I-MR Charts7:36
What will we learn?
When do we use an I-MR chart. Which is an Individual control chart and a Moving range control chart.
How to create an I-MR chart.
Lecture 15 How to create an I-MR Chart in excel14:01
How to create an I-MR Chart in excel
Lecture 16 Bionomial Process Capability Analysis12:02
Binomial Capability Analysis of Discrete attribute data

Requirements

None.

Description

Who needs this course:

This course will be of huge benefit to students of quality control and lean improvements.

This course is necessary for Quality Engineers, Process Engineers, Process Technicians, Quality Technicians, Operational Managers, Operational Line Leads and Service Providers.

Any person who needs an answer to a defect or efficiency issue

Benefits:

Understand the 7 basic tools for quality control.

1.Cause & Effect Diagrams.

2.Flowcharts.

3.Check sheets.

4.Pareto Diagrams.

5.Histograms.

6.Control Charts.

7.Scatter Diagrams

Relate tools to simple examples.

Apply the techniques of the tools. This means students will be able to collect data, analyse data and put actions in place to resolve issues.

Students will be able to harness excel as a tool to apply the 7 basic tools.

Students will be able to use material to prepare for quality control academic exams.

Use and understand the lecturers 20 year experience in high volume manufacturing industry to help resolve problems.

This course will explain the types of data used in statistics in simple terms.

Who this course is for:

Quality Engineers
Process Engineers
Process Technicians
Quality Technicians
Operational Managers
Operational Line Leads
Service Providers
Lean Engineers
Manufacturing Engineering
Production Managers
Industrial Engineers