Quality function deployment

Quality function deployment (QFD) is a method developed in Japan beginning in 1966 to help transform the voice of the customer into engineering characteristics for a product.[1][2] Yoji Akao, the original developer, described QFD as a "method to transform qualitative user demands into quantitative parameters, to deploy the functions forming quality, and to deploy methods for achieving the design quality into subsystems and component parts, and ultimately to specific elements of the manufacturing process."[1] The author combined his work in quality assurance and quality control points with function deployment used in value engineering.

House of quality

A1 House of Quality
A house of quality for enterprise product development processes

The house of quality, a part of QFD,[3] is the basic design tool of quality function deployment.[4] It identifies and classifies customer desires (What's), identifies the importance of those desires, identifies engineering characteristics which may be relevant to those desires (How's), correlates the two, allows for verification of those correlations, and then assigns objectives and priorities for the system requirements.[2] This process can be applied at any system composition level (e.g. system, subsystem, or component) in the design of a product, and can allow for assessment of different abstractions of a system.[2] It is intensely progressed through a number of hierarchical levels of What’s and How’s and analyse each stage of product growth (service enhancement), and production (service delivery).[5]

The house of quality appeared in 1972 in the design of an oil tanker by Mitsubishi Heavy Industries.[4]

The output of the house of quality is generally a matrix with customer desires on one dimension and correlated nonfunctional requirements on the other dimension.[2][6] The cells of matrix table are filled with the weights assigned to the stakeholder characteristics where those characteristics are affected by the system parameters across the top of the matrix.[6] At the bottom of the matrix, the column is summed, which allows for the system characteristics to be weighted according to the stakeholder characteristics.[6] System parameters not correlated to stakeholder characteristics may be unnecessary to the system design and are identified by empty matrix columns, while stakeholder characteristics (identified by empty rows) not correlated to system parameters indicate "characteristics not addressed by the design parameters".[6] System parameters and stakeholder characteristics with weak correlations potentially indicate missing information, while matrices with "too many correlations" indicate that the stakeholder needs may need to be refined.[6]

Areas of application

QFD is applied in a wide variety of applications viz Product Design [7]), manufacturing, production, engineering, research and development (R&D), information technology (IT), support, testing, regulatory, and other phases in hardware, software, service[8], and system organizations. organization functions necessary to assure customer satisfaction, including business planning, packaging and logistics, procurement, marketing, sales & service. QFD is also deployed in quality improvement, quality management, military needs and consumer products. Customer services Applications for Education improvement [5] and services in Hotels etc.

Fuzziness

The concepts of fuzzy logic have been applied to QFD ("Fuzzy QFD" or "FQFD").[9] A review of 70 papers in 2013 by Abdolshah and Moradi found a number of conclusions: most FQFD "studies were focused on quantitative methods" to construct a house of quality matrix based on customer requirements, where the most-employed techniques were based on multiple-criteria decision analysis methods.[9] They noted that there are factors other than the house of quality relevant to product development, and called metaheuristic methods "a promising approach for solving complicated problems of FQFD."[9]

Derived techniques and tools

The process of quality function deployment (QFD) is described in ISO 16355-1:2015 [10]. Pugh concept selection can be used in coordination with QFD to select a promising product or service configuration from among listed alternatives.

Modular function deployment uses QFD to establish customer requirements and to identify important design requirements with a special emphasis on modularity. There are three main differences to QFD as applied in modular function deployment compared to house of quality:[11] The benchmarking data is mostly gone; the checkboxes and crosses have been replaced with circles, and the triangular "roof" is missing.[11]

Notes

  1. ^ a b Akao, Yoji (1994). "Development History of Quality Function Deployment". The Customer Driven Approach to Quality Planning and Deployment. Minato, Tokyo: Asian Productivity Organization. ISBN 92-833-1121-3.
  2. ^ a b c d Larson et al. (2009). p. 117.
  3. ^ "Frequently Asked Questions about QFD". QFDI.org. QFD Institute. Archived from the original on December 13, 2013.
  4. ^ a b Hauser, John R.; Clausing, Don. "The House of Quality". Harvard Business Review. No. May 1988. Archived from the original on April 16, 2016.
  5. ^ a b Chahal, Amrinder Singh; et al. (2011). "Managing Class Room Quality Better: A Journey Thru QFD". Quality World (January): 4–11. SSRN 1829993.
  6. ^ a b c d e Larson et al. (2009). p. 119.
  7. ^ {{cite web |url=http://qfdeurope.com/en/history-of-qfd/%7Ctitle=History of QFD |
  8. ^ "Quality Function Deployment (Draft)" (PDF). di.ufpe.br. Archived (PDF) from the original on March 3, 2016.
  9. ^ a b c Abdolshah, Mohammad; Moradi, Mohsen (2013). "Fuzzy Quality Function Deployment: An Analytical Literature Review". Journal of Industrial Engineering. doi:10.1155/2013/682532.
  10. ^ |url=https://www.iso.org/standard/62626.html%7C
  11. ^ a b Börjesson, Fredrik; Jiran, Scott. "The Generation of Modular Product Architecture Deploys a Pragmatic Version of Quality Function Deployment". Archived from the original on December 31, 2012.

References

  • Larson, Wiley J.; Kirkpatrick, Doug; Sellers, Jerry Jon; Thomas, L. Dale; Verma, Dinesh, eds. (2009). Applied Space Systems Engineering. Space Technology. United States of America: McGraw-Hill. ISBN 978-0-07-340886-6.

Further reading

Contextual inquiry

Contextual inquiry (CI) is a user-centered design (UCD) research method, part of the contextual design methodology. A contextual inquiry interview is usually structured as an approximately two-hour, one-on-one interaction in which the researcher watches the user in the course of the user's normal activities and discusses those activities with the user.

Design for Six Sigma

Design for Six Sigma (DFSS) is a business-process management method related to traditional Six Sigma. It is used in many industries, like finance, marketing, basic engineering, process industries, waste management, and electronics. It is based on the use of statistical tools like linear regression and enables empirical research similar to that performed in other fields, such as social science. While the tools and order used in Six Sigma require a process to be in place and functioning, DFSS has the objective of determining the needs of customers and the business, and driving those needs into the product solution so created. DFSS is relevant for relatively simple items / systems. It is used for product or process design in contrast with process improvement. Measurement is the most important part of most Six Sigma or DFSS tools, but whereas in Six Sigma measurements are made from an existing process, DFSS focuses on gaining a deep insight into customer needs and using these to inform every design decision and trade-off.

There are different options for the implementation of DFSS. Unlike Six Sigma, which is commonly driven via DMAIC (Define - Measure - Analyze - Improve - Control) projects, DFSS has spawned a number of stepwise processes, all in the style of the DMAIC procedure.DMADV, define – measure – analyze – design – verify, is sometimes synonymously referred to as DFSS, although alternatives such as IDOV (Identify, Design, Optimize, Verify) are also used. The traditional DMAIC Six Sigma process, as it is usually practiced, which is focused on evolutionary and continuous improvement manufacturing or service process development, usually occurs after initial system or product design and development have been largely completed. DMAIC Six Sigma as practiced is usually consumed with solving existing manufacturing or service process problems and removal of the defects and variation associated with defects. It is clear that manufacturing variations may impact product reliability. So, a clear link should exist between reliability engineering and Six Sigma (quality). In contrast, DFSS (or DMADV and IDOV) strives to generate a new process where none existed, or where an existing process is deemed to be inadequate and in need of replacement. DFSS aims to create a process with the end in mind of optimally building the efficiencies of Six Sigma methodology into the process before implementation; traditional Six Sigma seeks for continuous improvement after a process already exists.

Gemba

Genba (現場, also romanized as gemba) is a Japanese term meaning "the actual place". Japanese detectives call the crime scene genba, and Japanese TV reporters may refer to themselves as reporting from genba. In business, genba refers to the place where value is created; in manufacturing the genba is the factory floor. It can be any "site" such as a construction site, sales floor or where the service provider interacts directly with the customer.In lean manufacturing, the idea of genba is that the problems are visible, and the best improvement ideas will come from going to the genba. The gemba walk, much like Management By Walking Around (MBWA), is an activity that takes management to the front lines to look for waste and opportunities to practice genba kaizen, or practical shop floor improvement.

In quality management, genba means the manufacturing floor and the idea is that if a problem occurs, the engineers must go there to understand the full impact of the problem, gathering data from all sources. Unlike focus groups and surveys, genba visits are not scripted or bound by what one wants to ask.

Glenn Mazur introduced this term into Quality Function Deployment (QFD, a quality system for new products where manufacturing has not begun) to mean the customer's place of business or lifestyle. The idea is that to be customer-driven, one must go to the customer's genba to understand his problems and opportunities, using all one's senses to gather and process data.

History of the concept of creativity

The ways in which societies have perceived the concept of creativity have changed throughout history, as has the term itself. The ancient Greek concept of art (in Greek, "techne" — the root of "technique" and "technology"), with the exception of poetry, involved not freedom of action but subjection to rules. In Rome, the Greek concept was partly shaken, and visual artists were viewed as sharing, with poets, imagination and inspiration.

Under medieval Christianity, the Latin "creatio" came to designate God's act of "creatio ex nihilo" ("creation from nothing"); thus "creatio" ceased to apply to human activities. The Middle Ages, however, went even further than antiquity, when they revoked poetry's exceptional status: it, too, was an art and therefore craft and not creativity.

Renaissance men sought to give voice to their sense of their freedom and creativity. The first to apply the word "creativity," however, was the 17th-century Polish poet Maciej Kazimierz Sarbiewski — but he applied it only to poetry. For over a century and a half, the idea of human creativity met with resistance, because the term "creation" was reserved for creation "from nothing."

In the 19th century, art took its revenge: now not only was art recognized as creativity, but it alone was. When later, at the turn of the 20th century, there began to be discussion as well of creativity in the sciences and in nature, this was taken as the transference, to the sciences and to nature, of concepts that were proper to art.

Innovation management

Innovation management is a combination of the management of innovation processes, and change management. It refers to product, business process, and organizational innovation. Innovation management is the subject of ISO 50500 series standards developed by ISO TC 279.

Innovation management includes a set of tools that allow managers and engineers to cooperate with a common understanding of processes and goals. Innovation management allows the organization to respond to external or internal opportunities, and use its creativity to introduce new ideas, processes or products. It is not relegated to R&D; it involves workers at every level in contributing creatively to a company's product development, manufacturing and marketing.

By utilizing innovation management tools, management can trigger and deploy the creative capabilities of the work force for the continuous development of a company. Common tools include brainstorming, prototyping, product lifecycle management, idea management, TRIZ, Phase–gate model, project management, product line planning and portfolio management. The process can be viewed as an evolutionary integration of organization, technology and market by iterating series of activities: search, select, implement and capture.Innovation processes can either be pushed or pulled through development. A pushed process is based on existing or newly invented technology, that the organization has access to, and tries to find profitable applications for.

A pulled process is based on finding areas where customers needs are not met, and then find solutions to those needs. To succeed with either method, an understanding of both the market and the technical problems are needed. By creating multi-functional development teams, containing both engineers and marketers, both dimensions can be solved.The product lifecycle of products is getting shorter because of increased competition. This forces companies to reduce the time to market. Innovation managers must therefore decrease development time, without sacrificing quality or meeting the needs of the market.

Kano model

The Kano model is a theory for product development and customer satisfaction developed in the 1980s by Professor Noriaki Kano, which classifies customer preferences into five categories.

Kansei engineering

Kansei engineering (Japanese: 感性工学 kansei kougaku, emotional or affective engineering) aims at the development or improvement of products and services by translating the customer's psychological feelings and needs into the domain of product design (i.e. parameters). It was founded by Mitsuo Nagamachi, Professor Emeritus of Hiroshima University (also former Dean of Hiroshima International University and CEO of International Kansei Design Institute). Kansei engineering parametrically links the customer's emotional responses (i.e. physical and psychological) to the properties and characteristics of a product or service. In consequence, products can be designed to bring forward the intended feeling.

It has now been adopted as one of the topics for professional development by the Royal Statistical Society.

Probabilistic design

Probabilistic design is a discipline within engineering design. It deals primarily with the consideration of the effects of random variability upon the performance of an engineering system during the design phase. Typically, these effects are related to quality and reliability. Thus, probabilistic design is a tool that is mostly used in areas that are concerned with quality and reliability. For example, product design, quality control, systems engineering, machine design, civil engineering (particularly useful in limit state design) and manufacturing. It differs from the classical approach to design by assuming a small probability of failure instead of using the safety factor.

Product analysis

Product analysis involves examining product features, costs, availability, quality and other aspects. Product analysis is conducted by potential buyers, by product managers attempting to understand competitors and by third party reviewers.Product analysis can also be used as part of product design to convert a high-level product description into project deliverables and requirements. It involves all facets of the product, its purpose, its operation, and its characteristics.

Project

Contemporary business and science treat as a project (or program) any undertaking, carried out individually or collaboratively and possibly involving research or design, that is carefully planned (usually by a project team) to achieve a particular aim.An alternative view sees a project managerially as a sequence of events: a "set of interrelated tasks to be executed over a fixed period and within certain cost and other limitations".A project may be a temporary (rather than permanent) social system (work system), possibly constituted by teams (within or across organizations) to accomplish particular tasks under time constraints.A project may be a part of wider programme management or an ad hoc structure.

Note that open-source software "projects" (for example) may lack defined team-membership, precise planning and time-limited durations.

QFD

QFD may refer to:

Quality function deployment

Quantum flavordynamics

Question-focused dataset

Boufarik Airport, Algeria (IATA: QFD)

Quality (business)

In business, engineering, and manufacturing, quality has a pragmatic interpretation as the non-inferiority or superiority of something; it's also defined as being suitable for its intended purpose (fitness for purpose) while satisfying customer expectations. Quality is a perceptual, conditional, and somewhat subjective attribute and may be understood differently by different people. Consumers may focus on the specification quality of a product/service, or how it compares to competitors in the marketplace. Producers might measure the conformance quality, or degree to which the product/service was produced correctly. Support personnel may measure quality in the degree that a product is reliable, maintainable, or sustainable.

Quality assurance

Quality assurance (QA) is a way of preventing mistakes and defects in manufactured products and avoiding problems when delivering products or services to customers; which ISO 9000 defines as "part of quality management focused on providing confidence that quality requirements will be fulfilled". This defect prevention in quality assurance differs subtly from defect detection and rejection in quality control, and has been referred to as a shift left as it focuses on quality earlier in the process i.e. to the left of a linear process diagram reading left to right.The terms "quality assurance" and "quality control" are often used interchangeably to refer to ways of ensuring the quality of a service or product. For instance, the term "assurance" is often used as follows: Implementation of inspection and structured testing as a measure of quality assurance in a television set software project at Philips Semiconductors is described. The term "control", however, is used to describe the fifth phase of the Define, Measure, Analyze, Improve, Control (DMAIC) model. DMAIC is a data-driven quality strategy used to improve processes.Quality assurance comprises administrative and procedural activities implemented in a quality system so that requirements and goals for a product, service or activity will be fulfilled. It is the systematic measurement, comparison with a standard, monitoring of processes and an associated feedback loop that confers error prevention. This can be contrasted with quality control, which is focused on process output.

Quality assurance includes two principles: "Fit for purpose" (the product should be suitable for the intended purpose); and "right first time" (mistakes should be eliminated). QA includes management of the quality of raw materials, assemblies, products and components, services related to production, and management, production and inspection processes. The two principles also manifest before the background of developing (engineering) a novel technical product: The task of engineering is to make it work once, while the task of quality assurance is to make it work all the time.Historically, defining what suitable product or service quality means has been a more difficult process, determined in many ways, from the subjective user-based approach that contains "the different weights that individuals normally attach to quality characteristics," to the value-based approach which finds consumers linking quality to price and making overall conclusions of quality based on such a relationship.

Requirement prioritization

Requirement prioritization is used in Software product management for determining which candidate requirements of a software product should be included in a certain release. Requirements are also prioritized to minimize risk during development so that the most important or high risk requirements are implemented first. Several methods for assessing a prioritization of software requirements exist.

SDI Tools

SDI Tools is a set of commercial software add-in tools for Microsoft Excel developed and distributed by Statistical Design Institute, LLC., a privately owned company located in Texas, United States.

SDI Tools were first developed in 2000 by Dr. George Chollar, Dr. Jesse Peplinski, and Garron Morris as several Add-Ins for Microsoft Excel to support a methodology for product development that combined elements of Design for Six Sigma and Systems Engineering Today, SDI Tools are split into two main Microsoft Excel Add-Ins called Triptych and Apogee.

Test method

A test method is a method for a test in science or engineering, such as a physical test, chemical test, or statistical test. It is a definitive procedure that produces a test result. In order to ensure accurate and relevant test results, a test method should be "explicit, unambiguous, and experimentally feasible.", as well as effective and reproducible.A test can be considered an observation or experiment that determines one or more characteristics of a given sample, product, process, or service. The purpose of testing involves a prior determination of expected observation and a comparison of that expectation to what one actually observes. The results of testing can be qualitative (yes/no), quantitative (a measured value), or categorical and can be derived from personal observation or the output of a precision measuring instrument.

Usually the test result is the dependent variable, the measured response based on the particular conditions of the test or the level of the independent variable. Some tests, however, may involve changing the independent variable to determine the level at which a certain response occurs: in this case, the test result is the independent variable.

Toyota Auto Body

Toyota Auto Body is a manufacturing subsidiary of the Toyota group based in Japan. It is headquartered in Kariya, Aichi and was established in 1945. The company has plants in the Mie and Aichi prefectures and other facilities around Japan and abroad. It developes and produces a range of minivans, SUVs and light commercial vehicles.

Voice of the customer

Voice of the customer (VOC) is a term used in business and Information Technology (through ITIL, for example) to describe the in-depth process of capturing customer's expectations, preferences and aversions. Specifically, the Voice of the Customer is a market research technique that produces a detailed set of customer wants and needs, organized into a hierarchical structure, and then prioritized in terms of relative importance and satisfaction with current alternatives. Voice of the Customer studies typically consist of both qualitative and quantitative research steps. They are generally conducted at the start of any new product, process, or service design initiative in order to better understand the customer's wants and needs, and as the key input for new product definition, Quality Function Deployment (QFD), and the setting of detailed design specifications.Much has been written about this process, and there are many possible ways to gather the information – focus groups, individual interviews, contextual inquiry, ethnographic techniques, etc. But all involve a series of structured in-depth interviews, which focus on the customers' experiences with current products or alternatives within the category under consideration. Needs statements are then extracted, organized into a more usable hierarchy, and then prioritized by the customers.

It is critical that the product development core team are involved in this process. They must be the ones who take the lead in defining the topic, designing the sample (i.e. the types of customers to include), generating the questions for the discussion guide, either conducting or observing and analyzing the interviews, and extracting and processing the needs statements.

According to APICS the definition of VOC is: Actual customer descriptions in words for the functions and features customers desire for goods and services. In the strict definition, as relates to quality function deployment (QFD), the term customer indicates the external customer of the supplying entity.

Yoji Akao

Yoji Akao (赤尾 洋二, Akao Yōji, 1928 – October 24, 2016) is a Japanese planning specialist recognized as the developer of Hoshin Kanri (a strategic planning methodology). With the late Shigeru Mizuno, he developed Quality Function Deployment (a group decision making technique). Akao and Mizuno also co-founded the Quality Function Deployment Institute: a non-profit organization dedicated to dissemination and advancement of QFD.Akao received a Ph.D. in 1964 from the Tokyo Institute of Technology.

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