Quality Function Deployment (QFD): An Effective Technique for REquirements
This paper puts forward Quality Function Deployment as an effective tool for.
Tran, Tuyet-Lan↗
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An Overview of the Quality Function Deployment (QFD) Technique
QFD is a product planning tool and a process methodology that enables all organizations, departments, and individuals in a business or a project to systematically focus on the critical performance, functions, and/or characteristics of a product that are the most important to the customer. It is part of the Total Quality Management (TQM) concept.. This presentation describes the objectives of QFD, the process for implementing the technique, the benefits derived from proper implementation, the kinds of systems where QFD is best utilized, what the success factors are, how QFD works, some guidelines for selection of a QFD team, and the functional roles of key team members.
Quality Function Deployment QFD customer focus cus↗
Quality Function Deployment (QFD): An Effective Technique for Requirements
This paper discusses problems in requirements acquisition and reuse, describes.
Tran, Tuyet-Lan↗
QFD Application to a Software - Intensive System Development Project
This paper describes the use of Quality Function Deployment (QFD), adapted to requirements engineering for a software-intensive system development project, and sysnthesizes the lessons learned from the application of QFD to the Network Control System (NCS) pre-project of the Deep Space Network.
QFD Quality Function Deployment NCS Network Contro↗
NTP comparison process
The systems engineering process for the concept definition phase of the program involves requirements definition, system definition, and consistent concept definition. The requirements definition process involves obtaining a complete understanding of the system requirements based on customer needs, mission scenarios, and nuclear thermal propulsion (NTP) operating characteristics. A system functional analysis is performed to provide a comprehensive traceability and verification of top-level requirements down to detailed system specifications and provides significant insight into the measures of system effectiveness to be utilized in system evaluation. The second key element in the process is the definition of system concepts to meet the requirements. This part of the process involves engine system and reactor contractor teams to develop alternative NTP system concepts that can be evaluated against specific attributes, as well as a reference configuration against which to compare system benefits and merits. Quality function deployment (QFD), as an excellent tool within Total Quality Management (TQM) techniques, can provide the required structure and provide a link to the voice of the customer in establishing critical system qualities and their relationships. The third element of the process is the consistent performance comparison. The comparison process involves validating developed concept data and quantifying system merits through analysis, computer modeling, simulation, and rapid prototyping of the proposed high risk NTP subsystems. The maximum amount possible of quantitative data will be developed and/or validated to be utilized in the QFD evaluation matrix. If upon evaluation of a new concept or its associated subsystems determine to have substantial merit, those features will be incorporated into the reference configuration for subsequent system definition and comparison efforts.
Corban, Robert↗
Comparative evaluation and selection of heat exchangers using multicriteria decision-making
Here, this study presents a well-structured method for comparing and selecting Heat Exchanger (HE) technologies for Integrated Energy Systems (IES). The decision to select a HE for a particular IES configuration can vary greatly depending not only on engineering requirements but also on customer’s specific demand. In other words, the HE selection for IES requires a multicriteria decision-making approach, taking into account diverse technical, economic, and safety aspects, as well as the relative priorities considered by energy users. This study employs a HE evaluation approach combining multicriteria decision-making techniques widely used in various industries: quality function deployment (QFD) and analytic hierarchy process (AHP) techniques. Of particular interest is the use of the proposed method to select a high-temperature HEs that couples advanced nuclear reactors and industrial processes. To build a practical basis for comparing HEs within the proposed framework, efforts were made to identify the various HEs requirements for IES purposes. In addition, leveraging the insights obtained from the literature review and the market survey of commercial HE suppliers, a knowledge base was built to facilitate the comparison of each requirement across various HE designs. Also, evaluation metrics were identified for HE requirements with robust rational to enhance the quality of decisions made throughout the proposed evaluation process. The evaluation procedure and knowledge base described in this study can provide a useful basis for those interested in screening the appropriate HE designs for various IES scenarios.
Analytic Hierarchy Process (AHP)↗
QFD analysis of RSRM aqueous cleaners
This paper presents a Quality Function Deployment (QFD) analysis of the final down-selected aqueous cleaners to be used on the Redesigned Solid Rocket Motor (RSRM) program. The new cleaner will replace solvent vapor degreasing. The RSRM Ozone Depleting Compound Elimination program is discontinuing the methyl chloroform vapor degreasing process and replacing it with a spray-in-air aqueous cleaning process. Previously, 15 cleaners were down-selected to two candidates by passing screening tests involving toxicity, flammability, cleaning efficiency, contaminant solubility, corrosion potential, cost, and bond strength. The two down-selected cleaners were further evaluated with more intensive testing and evaluated using QFD techniques to assess suitability for cleaning RSRM case and nozzle surfaces in preparation for adhesive bonding.
Marrs, Roy D.↗
Improving Customer Satisfaction in an R and D Environment
Satisfying customer needs is critical to the sustained competitive advantage of service suppliers. It is therefore important to understand the types of customer needs which, if fulfilled or exceeded, add value and contribute to overall customer satisfaction. This study identifies the needs of various research and development (R&D) customers who contract for engineering and design support services. The Quality Function Deployment (QFD) process was used to organize and translate each customer need into performance measures that, if implemented, can improve customer satisfaction. This study also provides specific performance measures that will more accurately guide the efforts of the engineering supplier. These organizations can either implement the QFD methodology presented herein or extract a few performance measures that are specific to the quality dimensions in need of improvement. Listening to 'what' customers talk about is a good first start.
Alexander, Anita↗
Quality Function Deployment for Large Systems
Quality Function Deployment (QFD) is typically applied to small subsystems. This paper describes efforts to extend QFD to large scale systems. It links QFD to the system engineering process, the concurrent engineering process, the robust design process, and the costing process. The effect is to generate a tightly linked project management process of high dimensionality which flushes out issues early to provide a high quality, low cost, and, hence, competitive product. A pre-QFD matrix linking customers to customer desires is described.
Dean, Edwin B.↗
SATWG networked quality function deployment
The initiative of this work is to develop a cooperative process for continual evolution of an integrated, time phased avionics technology plan that involves customers, technologists, developers, and managers. This will be accomplished by demonstrating a computer network technology to augment the Quality Function Deployment (QFD). All results are presented in viewgraph format.
Brown, Don↗
Fuzzy set approach to quality function deployment: An investigation
The final report of the 1992 NASA/ASEE Summer Faculty Fellowship at the Space Exploration Initiative Office (SEIO) in Langley Research Center is presented. Quality Function Deployment (QFD) is a process, focused on facilitating the integration of the customer's voice in the design and development of a product or service. Various input, in the form of judgements and evaluations, are required during the QFD analyses. All the input variables in these analyses are treated as numeric variables. The purpose of the research was to investigate how QFD analyses can be performed when some or all of the input variables are treated as linguistic variables with values expressed as fuzzy numbers. The reason for this consideration is that human judgement, perception, and cognition are often ambiguous and are better represented as fuzzy numbers. Two approaches for using fuzzy sets in QFD have been proposed. In both cases, all the input variables are considered as linguistic variables with values indicated as linguistic expressions. These expressions are then converted to fuzzy numbers. The difference between the two approaches is due to how the QFD computations are performed with these fuzzy numbers. In Approach 1, the fuzzy numbers are first converted to their equivalent crisp scores and then the QFD computations are performed using these crisp scores. As a result, the output of this approach are crisp numbers, similar to those in traditional QFD. In Approach 2, all the QFD computations are performed with the fuzzy numbers and the output are fuzzy numbers also. Both the approaches have been explained with the help of illustrative examples of QFD application. Approach 2 has also been applied in a QFD application exercise in SEIO, involving a 'mini moon rover' design. The mini moon rover is a proposed tele-operated vehicle that will traverse and perform various tasks, including autonomous operations, on the moon surface. The output of the moon rover application exercise is a ranking of the rover functions so that a subset of these functions can be targeted for design improvement. The illustrative examples and the mini rover application exercise confirm that the proposed approaches for using fuzzy sets in QFD are viable. However, further research is needed to study the various issues involved and to verify/validate the methods proposed.
Masud, Abu S. M.↗
Manned maneuvering unit applications for automated rendezvous and capture
Automated Rendezvous and Capture (AR&C) is an important technology to multiple National Aeronautics and Space Administration (NASA) programs and centers. The recent Johnson Spacecraft Center (JSC) AR&C Quality Function Deployment (QFD) has listed on-orbit demonstration of related technologies as a near term priority. Martin Marietta has been evaluating use of the Manned Maneuvering Unit (MMU) for a low cost near term on-orbit demonstration of AR&C technologies such as control algorithms, sensors, and processors as well as system level performance. The MMU Program began in 1979 as the method of repairing the Space Shuttle (STS) Thermal Protection System (the tiles). The units were not needed for this task, but were successfully employed during three Shuttle flights in 1984: a test flight was flown in in February as proof of concept, in April the MMU participated in the Solar Max Repair Mission, and in November the MMU's returned to space to successfully rescue the two errant satellites, Westar and Palapa. In the intervening years, the MMU simulator and MMU Qualification Test Unit (QTU) have been used for Astronaut training and experimental evaluations. The Extra-Vehicular Activities (EVA) Retriever has used the QTU, in an unmanned form, as a free-flyer on the Johnson Space Center (JSC) Precision Air Bearing Floor (PABF). Currently, the MMU is undergoing recertification for flight. The two flight units were removed from storage in September, 1991 and evaluation tests were performed. The tests demonstrated that the units are in good shape with no discrepancies that would preclude further use. The Return to Flight effort is currently clearing up recertification issues and evaluating the design against the present Shuttle environments.
Brehm, Donald L.↗
Rendezvous, proximity operations and capture quality function deployment report
Rendezvous, Proximity Operations, and Capture (RPOC) is a missions operations area which is extremely important to present and future space initiatives and must be well planned and coordinated. To support this, a study team was formed to identify a specific plan of action using the Quality Function Deployment (QFD) process. This team was composed of members from a wide spectrum of engineering and operations organizations which are involved in the RPOC technology area. The key to this study's success is an understanding of the needs of potential programmatic customers and the technology base available for system implementation. To this end, the study team conducted interviews with a variety of near term and future programmatic customers and technology development sponsors. The QFD activity led to a thorough understanding of the needs of these customers in the RPOC area, as well as the relative importance of these needs.
Lamkin, Stephen L.↗
Prioritization methodology for chemical replacement
Since United States of America federal legislation has required ozone depleting chemicals (class 1 & 2) to be banned from production, The National Aeronautics and Space Administration (NASA) and industry have been required to find other chemicals and methods to replace these target chemicals. This project was initiated as a development of a prioritization methodology suitable for assessing and ranking existing processes for replacement 'urgency.' The methodology was produced in the form of a workbook (NASA Technical Paper 3421). The final workbook contains two tools, one for evaluation and one for prioritization. The two tools are interconnected in that they were developed from one central theme - chemical replacement due to imposed laws and regulations. This workbook provides matrices, detailed explanations of how to use them, and a detailed methodology for prioritization of replacement technology. The main objective is to provide a GUIDELINE to help direct the research for replacement technology. The approach for prioritization called for a system which would result in a numerical rating for the chemicals and processes being assessed. A Quality Function Deployment (QFD) technique was used in order to determine numerical values which would correspond to the concerns raised and their respective importance to the process. This workbook defines the approach and the application of the QFD matrix. This technique: (1) provides a standard database for technology that can be easily reviewed, and (2) provides a standard format for information when requesting resources for further research for chemical replacement technology. Originally, this workbook was to be used for Class 1 and Class 2 chemicals, but it was specifically designed to be flexible enough to be used for any chemical used in a process (if the chemical and/or process needs to be replaced). The methodology consists of comparison matrices (and the smaller comparison components) which allow replacement technology to be quantitatively compared in several categories, and a QFD matrix which allows process/chemical pairs to be rated against one another for importance (using consistent categories). Depending on the need for application, one can choose the part(s) needed or have the methodology completed in its entirety. For example, if a program needs to show the risk of changing a process/chemical one may choose to use part of Matrix A and Matrix C. If a chemical is being used, and the process must be changed; one might use the Process Concerns part of Matrix D for the existing process and all possible replacement processes. If an overall analysis of a program is needed, one may request the QFD to be completed.
Cruit, Wendy↗
A Product Development Decision Model for Cockpit Weather Information System
There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.
Sireli, Yesim↗
A Product Development Decision Model for Cockpit Weather Information Systems
There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.
Sireli, Yesim↗
A Study of Technical Engineering Peer Reviews at NASA
This report describes the state of practices of design reviews at NASA and research into what can be done to improve peer review practices. There are many types of reviews at NASA: required and not, formalized and informal, programmatic and technical. Standing project formal reviews such as the Preliminary Design Review and Critical Design Review are a required part of every project and mission development. However, the technical, engineering peer reviews that support teams' work on such projects are informal, some times ad hoc, and inconsistent across the organization. The goal of this work is to identify best practices and lessons learned from NASA's experience, supported by academic research and methodologies to ultimately improve the process. This research has determined that the organization, composition, scope, and approach of the reviews impact their success. Failure Modes and Effects Analysis (FMEA) can identify key areas of concern before or in the reviews. Product definition tools like the Project Priority Matrix, engineering-focused Customer Value Chain Analysis (CVCA), and project or system-based Quality Function Deployment (QFD) help prioritize resources in reviews. The use of information technology and structured design methodologies can strengthen the engineering peer review process to help NASA work towards error-proofing the design process.
Chao, Lawrence P.↗
System Architecture Modeling for Technology Portfolio Management using ATLAS
Strategic planners and technology portfolio managers have traditionally relied on consensus-based tools, such as Analytical Hierarchy Process (AHP) and Quality Function Deployment (QFD) in planning the funding of technology development. While useful to a certain extent, these tools are limited in the ability to fully quantify the impact of a technology choice on system mass, system reliability, project schedule, and lifecycle cost. The Advanced Technology Lifecycle Analysis System (ATLAS) aims to provide strategic planners a decision support tool for analyzing technology selections within a Space Exploration Architecture (SEA). Using ATLAS, strategic planners can select physics-based system models from a library, configure the systems with technologies and performance parameters, and plan the deployment of a SEA. Key parameters for current and future technologies have been collected from subject-matter experts and other documented sources in the Technology Tool Box (TTB). ATLAS can be used to compare the technical feasibility and economic viability of a set of technology choices for one SEA, and compare it against another set of technology choices or another SEA. System architecture modeling in ATLAS is a multi-step process. First, the modeler defines the system level requirements. Second, the modeler identifies technologies of interest whose impact on an SEA. Third, the system modeling team creates models of architecture elements (e.g. launch vehicles, in-space transfer vehicles, crew vehicles) if they are not already in the model library. Finally, the architecture modeler develops a script for the ATLAS tool to run, and the results for comparison are generated.
Thompson, Robert W.↗