A Framework for Decision-Based Engineering Design

1998 ◽  
Vol 120 (4) ◽  
pp. 653-658 ◽  
Author(s):  
G. A. Hazelrigg
Keyword(s):  
Engineering Design ◽  
Operations Research ◽  
Quality Function Deployment ◽  
Value Theory ◽  
Decision Making Process ◽  
Design Decisions ◽  
Decision Sciences ◽  
Research Decision ◽  
Decision Based Design ◽  
Total Life

Engineering design is increasingly recognized as a decision-making process. This recognition brings with it the richness of many well-developed theories and methods from economics, operations research, decision sciences, and other disciplines. Done correctly, it forces the process of engineering design into a total systems context, and demands that design decisions account for a product’s total life cycle. It also provides a theory of design that is based on a rigorous set of axioms that underlie value theory. But the rigor of decision-based design also places stringent conditions on the process of engineering design that eliminate popular approaches such as Quality Function Deployment. This paper presents the underlying notions of decision-based design, points to some of the axioms that underlie the theory of decision-based design, and discusses the consequences of the theory on engineering education.

scholarly journals Marketing Based Decision Making Process in Engineering Design

2018 ◽  
Vol 7 (4.36) ◽  
pp. 854
Author(s):  
K. Palani Raj ◽  
G. Veeramani
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Design Process ◽  
Consumer Behaviour ◽  
Decision Making Process ◽  
Risk And Uncertainty ◽  
Design Decisions ◽  
Different Types ◽  
Important Study ◽  
Process Manufacturing

Marketing based decision making process in engineering design is an important study required for industries. How to take efficient decision in design that influence marketing? Most of the engineering design decisions are based on consumer behaviour. Decision making in risk and uncertainty in engineering design is an important phenomenon. Cost and time are the two important factors that results loss because of inefficient decision and it affects marketing. Problems involved in marketing based engineering design and decision making process in solving problems is elaborately studied in this journal. How to choose a design in various alternatives, design process, manufacturing feasibility, material and methodology are the important factors that influences decision making in engineering design for marketing. Different types of theories in decision making process that helps in taking proper decision were studied in this journal. This study is based on data taken from various Research & Development centre in Industries. 

scholarly journals Ethics and Strategy in Decision-Based Design Frameworks: Problems and Solutions

2019 ◽  
Vol 1 (1) ◽  
pp. 3301-3310
Author(s):  
Daniel Hulse ◽  
Christopher Hoyle ◽  
Irem Tumer
Keyword(s):  
Engineering Design ◽  
Expected Utility ◽  
Design Framework ◽  
Multiple Stakeholders ◽  
Design Decisions ◽  
Problems And Solutions ◽  
Per Se ◽  
Definition Of ◽  
Decision Based Design

AbstractEngineering Design decisions impact customers, the environment and society at large in ways that have profound ethical and strategic implications for designers. Previous research in decision-based design has proposed the decisions should be made on the basis of maximizing the expected utility of the design to the designer. This paper discusses ethical and strategic challenges for these frameworks across five levels: the axioms that underlie utility, the definition of utility, the consideration of multiple stakeholders, the modeling scope, and resulting design framework implementation. Based on these problems, solutions are suggested to account for each in the development of improved, ethically- informed frameworks. Challenges presented here do not prohibit the prudent use of decision-based design frameworks per se, but instead point to cases that must addressed in practice while providing grounds for further research towards the development of decision-based design frameworks that are ethical by design.

Introducing multivariate Markov modeling within QFD to anticipate future customer preferences in product design

2018 ◽  
Vol 35 (3) ◽  
pp. 762-778 ◽  
Author(s):  
Katerina Gotzamani ◽  
Andreas Georgiou ◽  
Andreas Andronikidis ◽  
Konstantina Kamvysi
Keyword(s):  
Quality Function Deployment ◽  
Fuzzy Ahp ◽  
Markov Modeling ◽  
Design Decisions ◽  
Content Type ◽  
Customer Preferences ◽  
First Time ◽  
The Voice ◽  
Product Specifications

Purpose The purpose of this paper is to provide an enhanced version of quality function deployment (QFD) that captures customers’ present and future preferences, accurately prioritizes product specifications and eventually translates them into desirable quality products. Under rapidly changing environments, customer requirements and preferences are constantly changing and evolving, rendering essential the realization of the dynamic role of the “Voice of the Customer (VoC)” in the design and development of products. Design/methodology/approach The proposed methodological framework incorporates a Multivariate Markov Chain (MMC) model to describe the pattern of changes in customer preferences over time, the Fuzzy AHP method to accommodate the uncertainty and subjectivity of the “VoC” and the LP-GW-AHP to discover the most important product specifications in order to structure a robust QFD method. This enhanced QFD framework (MMC-QFD-LP-GW-Fuzzy AHP) takes into consideration the dynamic nature of the “VoC” captures the actual customers’ preferences (WHATs) and interprets them into design decisions (HOWs). Findings The integration of MMC models into the QFD helps to handle the sequences of customers’ preferences as categorical data sequences and to consider the multiple interdependencies among them. Originality/value In this study, a MMC model is introduced for the first time within QFD, in an effort to extend the concept of listening to further anticipating to customer wants. Gaining a deeper understanding of current and future customers’ preferences could help organizations to design products and plan strategies that more effectively and efficiently satisfy them.

Consideration-Constrained Engineering Design for Strategic Insights

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Minhua Long ◽  
Michael Erickson ◽  
Erin F. MacDonald
Keyword(s):  
Decision Making ◽  
Consumer Behavior ◽  
Engineering Design ◽  
Decision Making Process ◽  
Design Framework ◽  
Design Strategies ◽  
Clean Diesel ◽  
Product Planning ◽  
Conjunctive Rule

Consumer behavior can be modeled using a decision-making process termed “consideration” in which consumers form requirements, “consideration rules,” in order to narrow their options for further evaluation. One type of consideration rule is the conjunctive rule, where a consumer makes a list of requirements and a product must meet all of the requirements in order to be considered for purchase, such as “the vehicle must get 25 miles per gallon or more”; “it must be priced at $22,000 or less”; and “it must be a standard-sized sedan.” This paper offers a design framework for linking these consideration rules with design. We demonstrate the use of our framework with a case study, namely the Volkswagen (VW) “clean diesel” scandal, which investigates the design strategies used in response to the scandal by capturing considerations within the marketing product planning subproblem and assuring engineering feasibility within the engineering design subproblem.

Teaching Decision Science in Educational Administration

1976 ◽  
Vol 4 (3) ◽  
pp. 231-235
Author(s):  
Walter M. Mathews
Keyword(s):  
United States ◽  
Decision Making ◽  
Educational Administration ◽  
Response Rate ◽  
The United States ◽  
Decision Making Process ◽  
Decision Science ◽  
Mail Questionnaire ◽  
Major Topic ◽  
Decision Sciences

The universities in the United States that offer a Doctorate in Educational Administration were surveyed to collect information on courses that they offer which include decision sciences—techniques which aid the decision-making process of administrators and which are usually mathematically or technologically based. With a 71 per cent response rate to a mail questionnaire, it was found that forty-five of the responding seventy-six universities (59 per cent) offered such a course to their administration majors. Data were collected from the instructors concerning frequency offered, average enrollment, year originated, and percentage of administration doctoral majors enrolled. A tally of the major topic areas was also recorded.

Using the Compromise Decision Support Problem in Microsystem Design: A Formulation for a Miniature Parylene Gas Chromatographic Column

2004 ◽  
Author(s):  
Andrew R. Schnell ◽  
Farrokh Mistree ◽  
Hongseok Moses Noh ◽  
Peter J. Hesketh
Keyword(s):  
Gas Chromatography ◽  
Decision Support ◽  
Engineering Design ◽  
Performance Goals ◽  
Design Decisions ◽  
Design And Manufacturing ◽  
Per Se ◽  
Microsystem Design ◽  
Domain Independent ◽  
Insight Into

The concurrent consideration of design and manufacturing requirements at the early stages of design is one of the cited challenges in microsystem design. In this paper, we take the first steps, through an example, towards addressing these issues through the use of the compromise Decision Support Problem (cDSP). The cDSP is a domain-independent hybrid multiobjective decision support formulation utilized in engineering design. The design of a parylene microchannel for a microscale gas chromatography system is refined using the cDSP. The objective is to adjust the geometry of the microchannel to create a satisficing design for one fabrication goal and two performance goals. The cDSP is utilized for five scenarios, one in which all three goals are given equal priority, one for each of three goals when they are given first priority, and one in which the performance goals are given equal priority. We are more interested in demonstrating the method than the results per se. Our goal is to show how microsystem designers can use the cDSP to gain some insight into how these goals interact and how design decisions can be made with this insight.

Operational and Strategic Decisions in Engineering Design Games

2018 ◽  
Author(s):  
Paul T. Grogan ◽  
Alparslan Emrah Bayrak
Keyword(s):  
Cognitive Load ◽  
Engineering Design ◽  
Situation Awareness ◽  
Strategic Decisions ◽  
Design Decisions ◽  
Operational Decisions ◽  
Operational Design ◽  
Load Limit ◽  
Dynamic Decisions ◽  
Human Participants

Engineering design games model decision-making activities by incorporating human participants in an entertaining platform. This article distinguishes between design decisions at operational and strategic timescales as important features of engineering design games. Operational decisions consider static and short-term dynamic decisions to establish a player’s situation awareness and initial entertainment. Strategic decisions consider longer-term dynamic decisions subject to large uncertainties to retain player engagement. However, constraints on cognitive load limit the ability to simultaneously address both lower-level operational design decisions and higher-level strategic decisions such as collaboration or sustainability. Partial automation can be introduced to reduce cognitive load for operational decisions and focus additional effort on strategic decisions. To illustrate tradeoffs between operational and strategic decisions, this paper discusses example cases for two existing games: Orbital Federates and EcoRacer. Discussion highlights the role of automation and entertainment in engaging human participants in engineering design games and makes recommendations for design of future engineering design games.

Addressing Adoption and Research Design Decisions Simultaneously

2011 ◽  
Vol 31 (6) ◽  
pp. 853-865 ◽  
Author(s):  
Claire McKenna ◽  
Karl Claxton
Keyword(s):  
Research Design ◽  
Resource Constraints ◽  
Design Decisions ◽  
Research Designs ◽  
Adoption Decisions ◽  
Conducting Research ◽  
Research Decision ◽  
The Cost ◽  
The Impact

Methods to estimate the cost-effectiveness of technologies are well developed with increasing experience of their application to inform adoption decisions in a timely way. However, the experience of using similarly explicit methods to inform the associated research decisions is less well developed despite appropriate methods being available with an increasing number of applications in health. The authors demonstrate that evaluation of both adoption and research decisions is feasible within typical time and resource constraints relevant to policy decisions, even in situations in which data are sparse and formal elicitation is required. In addition to demonstrating the application of expected value of sample information (EVSI) in these circumstances, the authors examine and carefully distinguish the impact that the research decision is expected to have on patients while enrolled in the trial, those not enrolled, and once the trial reports. In doing so, the authors are able to account for the range of opportunity cost associated with research and evaluate a number of research designs including length of follow-up and sample size. The authors also explore the implications for research design of conducting research while the technology is approved for widespread use and whether approval should be withheld until research reports. In doing so, the authors highlight the impact of irrecoverable opportunity costs when the initial costs of a technology are compensated only by later gains in health outcome.

scholarly journals ALTERNATIVE ANALYSIS OF FINITE-TIME PROBABILITY DISTRIBUTIONS OF RENEWAL THEORY

2014 ◽  
Vol 28 (2) ◽  
pp. 183-201 ◽  
Author(s):  
Percy H. Brill
Keyword(s):  
Operations Research ◽  
Stochastic Models ◽  
Probability Distributions ◽  
Renewal Theory ◽  
Regenerative Process ◽  
Renewal Processes ◽  
Level Crossing ◽  
Alternative Analysis ◽  
Level Crossing Analysis ◽  
Total Life

We introduce a level-crossing analysis of the finite time-t probability distributions of the excess life, age, total life, and related quantities of renewal processes. The technique embeds the renewal process as one cycle of a regenerative process with a barrier at level t, whose limiting probability density function leads directly to the time-t quantities. The new method connects the analysis of renewal processes with the analysis of a large class of stochastic models of Operations Research. Examples are given.

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