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.

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.

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.

Taxonomy for classifying engineering decision problems and support systems

1995 ◽  
Vol 9 (5) ◽  
pp. 427-438 ◽  
Author(s):  
David G. Ullman ◽  
Bruce D'Ambrosio
Keyword(s):  
Decision Support ◽  
Engineering Design ◽  
Quantitative Data ◽  
Decision Problems ◽  
Design Decision ◽  
Decision Support Tools ◽  
Design Decisions ◽  
Wide Range ◽  
Support Tools ◽  
Need Support

AbstractThe design of even the simplest product requires thousands of decisions. Yet few of these decisions are supported with methods on paper or on computers. Is this because engineering design decisions do not need support or is it because techniques have yet to be developed that are usable on a wide basis? In considering this question a wide range of decision problem characteristics need to be addressed. In engineering design some decisions are made by individuals, others by teams – some are about the product and others about the processes that support the product – some are based on complete, consistent, quantitative data and others on sparse, conflicting, qualitative discussions. To address the reasons why so little support is used and the characteristics of potentially useful decision support tools, a taxonomy of decision characteristics is proposed. This taxonomy is used to classify current techniques and to define the requirements for an ideal engineering design decision support system.

scholarly journals THE CREATIVITY MATRIX: AN EXTENSION TO AXIOMATIC DESIGN

2011 ◽  
Author(s):  
Brad Crowell ◽  
Peter Gregson
Keyword(s):  
Cognitive Psychology ◽  
Engineering Design ◽  
Design Process ◽  
Axiomatic Design ◽  
Synthesis Methods ◽  
Creative Design ◽  
Design Decisions ◽  
Good Design ◽  
Design Creativity ◽  
Analysis And Synthesis

Axiomatic Design helps a designer to make good design decisions. However, this addresses only one part of design. Prior to selecting a proposed design, the designer must synthesize options for further consideration. Within engineering design, creativity and expertise have been left to the competency of the designer and called the “art of engineering design”. To achieve a truly creative design process that addresses both analysis and synthesis, methods based on theories from Cognitive Psychology must be included. The resulting Creative Axiomatic Design process addresses both synthesis and analysis, enhancing creativity and expertise to inspire innovation and alternative perspectives on the design problem.

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.

scholarly journals Situation awareness modeling for emergency management on offshore platforms

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Syed Nasir Danial ◽  
Jennifer Smith ◽  
Faisal Khan ◽  
Brian Veitch
Keyword(s):  
Emergency Management ◽  
Case Studies ◽  
Situation Awareness ◽  
Emergency Evacuation ◽  
Offshore Platforms ◽  
Markov Logic ◽  
Cognitive States ◽  
Active Research ◽  
Human Participants ◽  
Fire Accidents

Abstract Situation awareness is the first and most important step in emergency management. It is a dynamic step involving evolving conditions and environments. It is an area of active research. This study presents a Markov Logic Network to model SA focusing on fire accidents and emergency evacuation. The model has been trained using empirical data obtained from case studies. The case studies involved human participants who were trained for responding to emergencies involving fire and smoke using a virtual environment. The simulated (queried) and empirical findings are reasonably consistent. The proposed model enables implementing an agent that exploits environmental cues and cognitive states to determine the type of emergency currently being faced. Considering each emergency type as a situation, the model can be used to develop a repertoire of situations for agents so that the repertoire can act as an agent’s experience for later decision-making.

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