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Training

Trust the Process

APQP Training Program

Advanced Product Quality Planning is the framework of procedures and techniques used to develop products. Test.

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DFMEA – FMECA Training Program

Design Failure Modes & Effects Analysis and Failure Modes, Effects & Criticality Analysis are a step-by-step approach to identify and…

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DRBFM Training Program

Design Review Based on Failure Modes is a focused approach of mitigating change risk within the product and process design….

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PFMEA Training Program

Process Failure Modes and Effects Analysis is a step-by-step approach to identify and manage the risks of failures within the…

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PPAP Training Program

Production Part Approval Process is a standardized process in the automotive and aerospace industries that helps manufacturers and suppliers communicate…

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DFM/A Training Program

Design for Manufacturing and Assembly is a combination of two methodologies; Design for Manufacture, which means the design for ease…

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DMAIC Training Program

Lean Six Sigma – A structured and disciplined approach to making fact-based decisions that cover the DMAIC phases: Define; Measure;…

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DOE Training Program

Design of experiments (DOE) – provides a systematic method to determine the relationship between factors affecting a process and the…

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Reliability Engineering Training Program

Reliability Engineering describes a focused approach to complete Reliability Engineering methods and how they will benefit your organization

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ISO 26262 Training Program

Functional Safety describes how to implement a vehicle level functional safety program, create a HARA, and understand the interactions within…

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MSA Training Program

Measurement System Analysis is an experimental and mathematical method of determining how much the variation within the measurement process contributes…

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SPC Training Program

Statistical Process Control is a scientific visual method used to monitor, control and improve processes by eliminating special cause variation…

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FTA Training Program

Fault Tree Analysis is a systematic, deductive (top-down), graphical methodology for defining a single specific undesirable event and determining all…

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MFMEA / DFM M&T Training Program

Machine Failure Modes and Effects Analysis is a methodical approach for identifying all possible equipment failures in a manufacturing or…

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RCA Training Program

Root Cause Analysis – 8D is a methodical problem-solving process that covers the three common stages of correction: ⦁ Act…

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QSB Training Program

QSB will provide a summary of how to assess shop floor manufacturing systems. Training will include control of nonconforming products,…

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Poka-Yoke Training Program

Poka-yoke is a technique for avoiding simple human error in the workplace. Also known as mistake-proofing, goof-proofing, and fail-safe work…

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Process Awareness

Ability and knowledge to participate in  completing the FMEA Process

LEVEL 1

Competency

Ability and knowledge to lead a team in the FMEA Process

LEVEL 2

Proficient

Ability to teach and mentor Participants and Team Leads in the FMEA Process

LEVEL 3

Expert

Ability to lead an organization implementing FMEA

LEVEL 4

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DFM/A Training Program

Design for Manufacturing and Assembly is a combination of two methodologies; Design for Manufacture, which means the design for ease…

Learn More »

PFMEA Training Program

Process Failure Modes and Effects Analysis is a step-by-step approach to identify and manage the risks of failures within the…

Learn More »

DRBFM Training Program

Design Review Based on Failure Modes is a focused approach of mitigating change risk within the product and process design….

Learn More »

DFMEA – FMECA Training Program

Design Failure Modes & Effects Analysis and Failure Modes, Effects & Criticality Analysis are a step-by-step approach to identify and…

Learn More »

Please visit ReliatrainGov.com for more information about Government Services

PFMEA Training Program

Process Failure Modes and Effects Analysis is a step-by-step approach to identify and manage the risks of failures within the…

Learn More »

DRBFM Training Program

Design Review Based on Failure Modes is a focused approach of mitigating change risk within the product and process design….

Learn More »

DFMEA – FMECA Training Program

Design Failure Modes & Effects Analysis and Failure Modes, Effects & Criticality Analysis are a step-by-step approach to identify and…

Learn More »

Please visit ReliatrainGov.com for more information about Government Services

DOE Training Program

Design of Experiments (DOE)

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COURSE DESCRIPTION

“Design of Experiments” is a 16-hour activity-based, interactive workshop to showcase the power and utility of this statistical tool while teaching how to plan and analyze an experiment. It is also to dispel the conception that DOE is reserved only to those with advanced math training. Participants can expect to be fully engaged while learning and applying principles, tools, and techniques for completing innovative DOE projects. Participants are expected to pass a quiz and complete a work-related project as part of this course.

What is DOE?
A structured method used to determine the relationship between independent factors (X’s) and the output/response (Y) (objective is to find the effect of factors (X) on the response (Y).

Why use DOE?
⦁ To allow for the simultaneous study of the effects that several factors may have on a process
⦁ To maximize information obtained from a given number of simulation runs
⦁ To determine if there is interaction between factors

When to use DOE?
⦁ When investigating or characterizing a process or product variables that influence product performance

Desired Results of Design of Experiments include:
⦁ Problem Solving
-Eliminate defective products or services
-Reduce cycle time of handling transactional processes
⦁ Optimizing
-Mathematical model is desired to move the process response
-Opportunity to meet differing customer requirements (specifications or VOC)
⦁ Robust Design
-Provide consistent process or product performance
-Desensitize the output response(s) to input variable changes including NOISE variables
-Design processes knowing which input variables are difficult to maintain.
⦁ Screening
-Past process data is limited, or statistical conclusions prevented good narrowing of critical factors in analyze phase.

COURSE OBJECTIVES

To provide participants the skills and abilities to increase customer satisfaction, reduce cost, increase quality, improve reliability, improve speed, and make intended processes more robust, effective, and efficient. At the end of this course you should be able to:

⦁ Define how to evaluate which process inputs have a significant impact
⦁ Define the “target level” of defined inputs
⦁ Define what “Histogram” means
⦁ Define “Statistical Process Control (SPC)” and when it is used in the DOE process
⦁ Define “Regression and Correlation Analysis”
⦁ Define what a “Factor” is within the DOE process
⦁ Define what a “Level” is within the DOE process
⦁ Define what a “Response” is within the DOE process
⦁ Define what a “Significant Input” is within the DOE process
⦁ Define what “Reducing Variability” is within the DOE process
⦁ Define the difference between factors, levels and structure within a DOE
⦁ Define “Unexplained Variation”
⦁ Define “Noise Factors”
⦁ Define what “Correlation” means within the DOE process
⦁ List the Experimental Design Process Steps
⦁ Define “One-factor Experiment”
⦁ Define the use of the F-test
⦁ Define “Multi-factor Test”
⦁ Define a 22 full factorial experiment using the 8-steps for analysis of effects
⦁ Develop and implement a DOE plan for a work-related process

COURSE OUTLINE

This training will include an introduction to Minitab statistical software. The training will follow the 9 phases defined in the process flow: Introduction; Preparation; DOE Components; DOE Purpose; Design Guidelines; Design Process; One-factor Experiments; Multi-factor Experiments; and Taguchi Methods.

Step One: Introduction

⦁ Definition of DOE
⦁ Process Overview

Step Two: Preparation

⦁ Toolbox Review
⦁ Software Review

Step Three: DOE Components

⦁ Factors
⦁ Levels
⦁ Response

Step Four: DOE Purpose

⦁ Compare Alternatives
⦁ Identify Inputs
⦁ Optimal Process Output
⦁ Reduce Variability
⦁ Target Response
⦁ Improve Robustness
⦁ Balance Tradeoffs

Step Five: Design Guidelines

⦁ Error Sources
⦁ Noise Factors
⦁ Correlation
⦁ Interactions

Step Six: Design Process

⦁ Define Problem
⦁ Determine Objectives
⦁ Brainstorming
⦁ Design Experiment
⦁ Conduct Experiment
⦁ Collect Data
⦁ Analyze Data
⦁ Interpret Results
⦁ Verify Predicted Results

Step Seven: One-factor Experiments

⦁ SPC Chart Method
⦁ F-test - ANOVA
⦁ Model F-ratio

Step Eight: Multi-factor Experiments

⦁ Full Factorial Experiment
⦁ Fractional Factorial Designs

Step Nine: Taguchi Methods

⦁ Robust Design
⦁ Loss Function

COURSE PREREQUISITES

The prerequisites for this workshop are familiarity with the concepts of process stability, basic statistical process control (SPC), and measurement systems analysis (MSA). It is recommended that the participants have access to Minitab statistical software throughout training.

COURSE RECOMMENDED PARTICIPANTS

A recommended DOE course candidate is someone with at least two years of work experience who wants to build or demonstrate his or her knowledge of contemporary quality tools and processes.

This DOE training program is intended for all industries including but not limited to:

Commercial
Medical (Including Hospitals)
Utilities
Aerospace
Civil Engineering
Tooling and Equipment
Oil and Gas
Trains & Railroad
Equipment
Military [DOD]
Government
Phones & Personal Devices

ReliaTrain offers mentoring, facilitation, and training support for Product and Process Development based on Quality and Reliability industry standards. ReliaTrain provides step-by-step methodologies that can be tailored to your organizational requirements. Let ReliaTrain experts support implementation of DOE methodology at your company.

Contact us to learn more about DOE