A Six Sigma (DFSS) Approach for Quality by Design
Six Sigma is the application of scientific methods to the design and operation of management systems and business processes. It was introduced by engineer Bill Smith while working at Motorola in 1986. Six Sigma focuses on reducing variation in systems, processes and products, defect prevention and cycle time reduction all of which directly impacts the bottom line of a business. Sigma (σ) is a statistical term that measures the variability in any product or process. Six Sigma aims for a process to be 99.99996% defect free. In other words, a process which results in less than 3.4 defects per million opportunities (DPMO).
DMAIC Vs DMADV
Six Sigma is generally implemented with two methodologies i.e., DMAIC and DMADV based on their area of application. While DMAIC (Define, Measure, Analyse, Improve and Control) method, we can improve existing products and processes; DMADV, also called as “Design for Six Sigma” and focuses on new product and process design. Design for Six Sigma covers a full range of product or process design as described below.
Core Concepts of Design for Six Sigma
Voice of the Customer (VOC): The stated (and implied) needs and expectations of the customer on the product or service
- Quality Function Deployment (QFD): An approach to capture the stated (and implied) needs and expectations of customer and translating them into product characteristics or engineering specifications to produce products to meet those needs.
- Critical to Quality (CTQ): Key measurable characteristics of a product or process whose performance standards or specification limits must be met in order to satisfy the customer.
- Design of experiments (DOE): A statistical method of designing experiments for determining the relationship between process inputs and process outputs. DOE enables product and process designers to find the optimal design parameters to obtain a robust design. There are two approaches to DOE: Factorial experiments and Taguchi design.
- Variation: The dissimilarity between two products for the same characteristic or attribute.
- Process Capability: Ability of a process to produce products within the design specification.
Opportune time for implementation of Design for Six Sigma (DFSS)
DFSS is a systematic methodology for designing products or services from the very beginning to ensure that they produce Six Sigma quality products and services, meeting customer requirements. It aims to optimize the product in the design stage itself when the costs are lowest to achieve Six Sigma performance.
Implementation of DMADV Methodology
The DMADV project methodology, known as DFSS (“Design For Six Sigma”) consists of five phases
Voice of customer (VOC) is captured using methods like Market Research, Customer surveys, Customer observation, Interviews, Benchmarking, Feedback reports, Focus groups and KANO analysis are some of the techniques that can be used to capture VOC.
A business case is prepared listing compelling reasons for selecting and working on a particular project and the potential benefits expected. It is crucial to ensure the full support of all stakeholders in the project from project initiation.
QFD is used to translate the voice of customer (VOC) into design or engineering parameters. Identify the Critical to Quality (CTQ) parameters from customer’s perspective. Collect data on CTQ parameters to evaluate the initial capability and establish the baseline performance level.
Analyze the data by using appropriate statistical and data analysis techniques to develop optimum parameters for the product design. Data analysis mainly depends on the type of data available. There are two types of data: Continuous data (Quantitative or Measurable) and discrete data (qualitative or attribute). The following table illustrates the applicable data analysis for different types of input and output data.
A statistical model is developed using Design of Experiments. The functional relationship between X and Y is given by
Y= f (X1, X2, X3,…,Xn) + ϵ
Where, Y is the Critical to Quality parameter (CTQ) that needs to be optimized; X1, X2, X3 are input parameters which could influence the CTQ and ϵ is the experimental error. DOE analysis gives optimum values of input parameters for optimizing the Critical to Quality parameter “Y”. Response Surface Methodology (RSM) can also be used to optimize the response parameter(Y).
The expertise of external professionals can be sought to analyze and mine the data if internal capacity is not available within the organization.
Design the product with the optimum parameters obtained through the statistical analysis. Optimize the design using simulations.
Check the design to ensure it meets the customer, statutory and regulatory requirements. Develop and test the prototype to verify that the intended objectives are met.
Customers today are highly informed and their demands are ever increasing. Organizations have to constantly innovate to be a leader in the market place. Systematic implementation of Design for Six sigma will pave the way for an organization to enhance customer value through improved design. DFSS intervenes at the early stage of product development and thus can bring down the product life cycle cost.