1.3.1 - DFSS

Objective:

This training has as focus the formation of professionals in the Six Sigma methodology that are more related to implementing new process and products. The objective is to pass the basis, concepts and tools of DFSS – Design for Six Sigma (DMADV) allowing the Belts to develop and lead projects in their organization using the DMADV flux (Define, Measure, Analyze, Design and Verify)

In short:

• To differentiate the DMAIC X DFSS methodologies.
• When and why to use the DFSS model.
• To use the Six Sigma methodology – DFSS to obtain significant results in the introduction of new processes, products and services.
• To comprehend the tools that support the DFSS methodology
• DFSS X Financial Impact in the organization
• To develop competencies to lead the introduction and the management of the changes in the organization
• To build in the company a culture of business efficient management

Target Audience:

• Professionals from diverse working areas related with new process, product and/or service release like, for instance, engineering, IT and Product and Process Engineering.

Pre-Requirements:

• None

Course Duration:

• 80 hours. In general, the training happens in two separated weeks (one per month) in a manner that the participant develops his project together with his training.

Programmatic Content:

Week 1

Introduction

• Introduction to the DFSS
• Historic
• DFSS structure
• Differentiation between DMAIC X DFSS
• Definition     
• Introduction to Define Phase
• How to identify a DFSS project
• Scope definition
• Change acceleration tools
• Multigenerational plan
• Risk Matrix
• Project charter
• Measure
• Introduction to Measure Phase
• Indentifying Voice of the Customer – VOC and Voice of the Business (VOB)
• Identifying the critical characteristics for a new product, process and/or service (CTQ`s)
• Research Methods (interviews, focus group, internal and external research)
• VOC table
• Affinity table
• Kano Model
• QFD (Quality Function Deployment) – House of quality number 1
• Basic Statistic
• Data type (continuous and discrete)
• Basic statistic –position and variation measurement, normal curve
• Data Collection – Planning (Operational Definition)
• Measurement System Analysis (MSA) – Continuous and Discrete Data
• Basic Graphs – Pareto / Box Plot / Dispersion Diagram / Trend

Week 2

Analyze

• Creating Design Models
• QFD (Quality Function Deployment) – House of quality number 2
• SIPOC
• Benchmarking
• Pugh matrix
• Capability analysis – Continuous Data (Normal data)
• Capability analysis – Discrete Data

Design

• Elaboration of Macro and detailed design
• QFD (Quality Function Deployment) – House of quality number 3 and 4
• Design of Experiments (DOE) – Full Factorial
• Monte Carlo Simulation
• FMEA
• Mistake Proofing Devices (Pokayoke)
• Process Control System
• Control Plan

Verify

• Pilot test
• Processes Control System
• Control Plan
• Statistical Process Control (SPC) for Continuous Data
• Statistical Process Control (SPC) for Discrete Data
• Project Examples

Training Modalities:

• In company – carried out in closed classes, by customer request.

Requirements for Certification:

• This Training is only provided in-company. Thus, the certification depends of the customer requirements. In general, the standard to be followed is.
  1 – Development of one project with impact in the organization
  2 – At least 80% of frequency in the training.

OBS: All participants earn the conclusion certificate if comply with 80% of frequency in the training.

Specific Needs for Training Attendance:

• Computers – should be one for each three attendants
• Use of Minitab statistical software