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This tool is used to identify relationships between 2, 3, or 4 datasets.

## Introduction

This tool is used to identify relationships between 2, 3, or 4 datasets. Following the tree diagram, it serves to identify relationships and the strength of relationships between various alternatives and helps us in the search for the ideal solution. It is this type of matrix that is used for the construction of the QFD.

## 1 – Choose the matrix

 Name Number of groups Type of relationship studied L 2 A ↔ B T 3 b ↔ A ↔ C but not B ↔ C Y 3 A ↔ B ↔ C ↔ A C 3 The three simultaneously X 4 A ↔ B ↔ C ↔ D ↔ A but not A ↔ C or B ↔ D Roof 1 A ↔ A

## 2-Building The Matrix

### The L-matrix

This 2D matrix makes it possible to describe a relationship between two entities. This matrix is widely used in the QFD Which for the first makes the relationship between customer expectations and attributes of an object.

Example of an L-matrix for the quality of a pizza

 Fresh topping Filling quantity Low calorie Food Color Good taste 3 3 Low price -1 -1 -1 Good texture 9 9 1 Few calories -1 9 11 10 8 1

It is concluded that the fresh topping is the attribute of our pizzas most important for the quality of it.

### T-Matrix

In 2D, the T-matrix can correlate a element a with 2 other groups of elements. In the example below, the correlation between the model type, the method of purchase and the type of customer is evaluated.

 Internet 9 9 Large Area 3 3 3 Specialized Shop 1 1 9 Television broadcast 9 Model A Model B Model C Model D < 18ans 9 3 18 to 25 years 3 3 25 to 55 years 1 3 1 > 55 years 1 9

In this example, if one concentrates on product A, it is observed that it is mainly bought by under 18 years and that its main mode of purchase is the Internet.

### The Y-matrix

The matrix allows to correlate 3 factors between them. In the example below, we see for example that the stock level is the most important from the customer point of view, and the most impacted services are the planning, the production and the purchases.

### The Matrix C

The Matrix C is a cubic matrix. It allows to simultaneously connect 3 factors between them according to the following model.

### X Matrix

The X matrix is an extension of the T matrix and thus allows to correlate an additional factor. It is mainly used in the context of the Hoshin Kanri To deploy a policy.

### Roof matrix

The roof matrix allows to identify correlations between elements of the same group. It typically serves as part of the QFD To identify functions are not contradictory.

In the example below, we study whether there are correlations in different criteria for the validation of a cream. We observe that the color of the cream is very impacted by the presence of particles.