Quality Function Deployment

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Quality Function Deployment (QFD) is also known as House of Quality, due to characteristic appearance of analytic matrix. It was first used in 1972 in Japan, in the yard belonging to Mitsubishi. After a few years, it gained popularity in the United States, where it was used successfully in plants of Ford and General Motors, and later at Digital Equipment, Hewlett-Packard, AT&T and ITT.

Purpose of QFD

The purpose of QFD is to translate the needs and expectations of the audience into the specifications of product or service. Production on an industrial scale prevents direct contact with the target audience. There is a number of methods of indirect contact, including interviews, surveys, tests. A significant problem for product designers is a lack of customers' expertise. They are usually not able to determine the technical parameters of products. For example, only few customers of drills know how many revolutions per minute should it perform. Most of them think probably: the more the better. Increasing pressure on reducing design costs and shorten its duration meant that there was a need for a method that would make it possible to translate the conscious and unconscious customer requirements into technical specifications, taking into account technological capability, the degree of importance of individual characteristics to the customer and relationships between them. The answer to this need has become the Quality Function Deployment method.

How to build QFD matrix

Quality Function Deployment matrix

The main element analytical matrix is ​​known as the house of quality (Fig. 1). It consists of nine sections:

  1. Customer requirements
  2. The degree of importance of each of the requirements together with comparative assessment of competing companies.
  3. The technical characteristics(design, technology) product.
  4. The link between the needs of the recipient and technical characteristics.
  5. Rating the technical characteristics.
  6. Degree of correlation between technical characteristics.
  7. Values ​​desirable for each technical characteristics.
  8. Technical comparative assessment.
  9. Special requirements relating to safety, government regulations, service, etc.

Customer requirements (What?)

In Part I the needs and expectations of the client should be placed (the answer to the question: what?). They are obtained from market research, and use non-technical language, using terms that are used by the customer. This field of practical applications of the method includes dozens, and often more than 100 requirements.

Degree of importance (Why?)

The second part, on the right side of the diagram, allows to determine the significance of needs (question: why?). This part consists of several columns:

  1. The rank of individual requirement; how important it is for customers. Ranking scope can be defined individually, ex. from 0 to 5, from 0 to 20, etc.
  2. The second column shows how customers evaluate the fulfilment of the requirement in the tested product (if we already have a product, e.g. older make).
  3. The next one or more columns presents the grades obtained by the products of competitors.
  4. Planned level of quality. The assessment of customers that the organization wants to achieve in future for its product
  5. Indicator of improvement (planned level of quality divided by current customer evaluation in column two).
  6. Possibility of presenting feature to the customer (is it easily visible or can be unnoticed by customer). Scale from 1.0 to 2.0 usually.
  7. To finally answer how it will be important modification of the characteristic ratio shall be calculated by multiplying the values ​​of the first column, sixth (indicator of improvement) and seventh (possibility of presentation).
  8. The last column shows the same indicator in a percentage scale for an easier comparison of the features.

Technical characteristics (How?)

The first two parts of the scheme comply with experts in marketing and sales. However, when filling the third sector engineers are required. To every customer requirement one or more technical characteristics of the product should be assigned. We ask the question: how?

Requirements vs. specification

The fourth part links customer requirements with technical characteristics. It is easy to notice that some requirements may have a stronger effect on the characteristics and other weaker. It may also happen the opposite effect, as in the case of the aforementioned drill - the requirement "a sure and comfortable grip" is inversely correlated with trait "vibes". The strength of the correlation recorded numbers from - 9 to +9.

Rating the technical characteristics (Which?)

The fifth part answers the question which? It seeks to obtain information on mutual validity of product characteristics. For this purpose, a simple formula is used:

where

- correlation of requirement i and feature j

- percentage ratio for the requirement i (it was calculated in the second part, column 9)

The result is entered in both the numeric value, as well as a percentage scale.

Correlation between technical characteristics

Part sixth of the matrix has form of a triangle. It serves the presentation of correlations between technical features. It may turn out that the improvement in one parameter will affect the other, for example. "Number of revolutions" may be negatively correlated with "noise". The values ​​are assigned to the same extent as in the fourth part (-9 to +9).

Desirable values

Seventh part contains the numerical values ​​that are assumed for the modified product. You can also refer to standards or other acts. If the requirements and characteristics are plentiful and additionally they exhibit a negative correlation, filling this part becomes extremely difficult and requires a lot of compromises and decision-making at the highest level.

This data is used in part eight, which aims to compare the expected level of quality with existing competition. Additional requirements (legal, environmental, etc.) are recorded in part nine.

Chain of QFD matrices

Presented a conduct is only the first step to create a new product, called product planning. The entrance to the next step (that is data for the first part of a quality house) - to develop the project - will use technical features and their parameters as an input and result with data regarding the components of the product. The third step is to plan the process and the result of it are technological operations. Fourth, production planning, allows to determine the production requirements. It is possible to build the following matrices, until the lowest level of design of all elements relevant to a new product.

J. Sikorski lists the following benefits of using this method:

  • Creation of a single organizational structure,
  • Facilitate checks on compliance with the work schedule.
  • Initiating collaborative forms of work,
  • Breaking down barriers between departments,
  • Flow of information about customer expectations through the entire structure of the company,
  • Accurate diagnosis of the hierarchy of customer expectations,
  • Ability to anticipate the level of their performance,
  • Increase the company's potential in terms of full implementation of the requirements.
  • Business decisions based on accumulated knowledge,
  • Avoiding many of the costs and loss of time.

Example of QFD

To illustrate the QFD, Figure 2 shows the application of the method on the rail passenger car. Table 1 shows the properties of the product and the two competitors. An example has been greatly simplified, since both the number of requested characteristics and technical performance in practice are much greater.

Table 1. Performance characteristics of the rail passenger car

Feature Current product Competitor A Competitor B

the number of compartments

9 10 9

number of seats in a row

4 4 3

type of chair

seat retractable one stage, profiled bench, not retractable

Profiling

seat retractable two stages, not profiled

space for luggage

4 shelves, tables 4 4 shelves, 2 tables 2 shelves, tables 4

ventilation

Heating controlled window opens central heating, window open air conditioning, tilt casement

front door

opened manually opened manually opened automatically.
Example of the method QFD for rail passenger wagon

Advantages of Quality Function Deployment

QFD is a powerful tool for product and service development that can be used to identify customer needs and translate them into product requirements. It is also known as House of Quality, due to its characteristic appearance of analytic matrix. The main advantages of using QFD are:

  • It helps to systematically capture customer needs and incorporate them into the design process. This results in higher customer satisfaction because the product or service meets the customer’s expectations.
  • It helps to create a cross-functional team that is focused on the customer and works together to develop the best product or service.
  • It enables the organization to prioritize customer requirements and make sure they are addressed during the design process.
  • It helps to identify potential problems early in the design process, allowing the organization to take corrective action before the product or service is launched.
  • It helps to identify potential opportunities for improvement, allowing the organization to stay ahead of its competition.
  • It helps to reduce the time and cost associated with product development by streamlining the design process.

Limitations of Quality Function Deployment

  • Quality Function Deployment is a powerful tool for gathering customer requirements and converting them into design specifications. However, it is not without its limitations.
  • QFD is complex and requires a high level of expertise to use correctly. It is also time-consuming and costly to implement, making it inappropriate for smaller businesses with limited budgets.
  • QFD is based on assumptions that might not always be accurate, and it is also highly dependent on the quality of data used. It is also susceptible to subjective judgement and can be prone to bias.
  • QFD also fails to address non-quantifiable customer requirements, such as aesthetic preferences and emotional needs.
  • Finally, QFD does not provide a comprehensive view of customer feedback and preferences, as it only focuses on a few key areas. This can lead to important customer requirements being overlooked.

Other approaches related to Quality Function Deployment

Introduction:

Alongside Quality Function Deployment (QFD), there are other approaches that can be used to improve product quality in the manufacturing industry. These approaches include:

  • Quality by Design (QbD): QbD involves the integration of scientific knowledge and product development for the purpose of achieving the desired quality standards. It is based on the idea that product quality can be achieved by understanding the relationship between design parameters, process parameters and product characteristics.
  • Design of Experiments (DOE): DOE is an experimental technique that is used to determine the relationship between input factors (independent variables) and output responses (dependent variables). This process allows for the optimization of product design and the development of robust manufacturing processes.
  • Six Sigma: Six Sigma is a process improvement methodology that is used to reduce defects and increase customer satisfaction. It involves the implementation of advanced statistical tools and techniques to analyze, measure and improve processes.
  • Total Quality Management (TQM): TQM is a management approach that is focused on the continual improvement of product quality. It involves the implementation of quality control systems and processes to ensure that products meet customer requirements.

Summary:

In addition to Quality Function Deployment (QFD), there are several other approaches that can be used to improve product quality in the manufacturing industry. These include Quality by Design (QbD), Design of Experiments (DOE), Six Sigma, and Total Quality Management (TQM). Each of these techniques has its own set of tools and techniques that can be used to optimize product design and develop robust manufacturing processes.


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References

Author: Slawomir Wawak