scholarly journals Reflective Decision-Making in Elementary Students' Engineering Design

2017 ◽  
Vol 106 (3) ◽  
pp. 356-397 ◽  
Author(s):  
Kristen Bethke Wendell ◽  
Christopher G. Wright ◽  
Patricia Paugh
Keyword(s):  
Decision Making ◽  
Elementary Students ◽  
Engineering Design

scholarly journals Challenges for Experience Feedback in Engineering Design

2009 ◽  
Author(s):  
Henrik Nerga˚rd ◽  
Tobias Larsson
Keyword(s):  
Decision Making ◽  
Knowledge Sharing ◽  
Engineering Design ◽  
Empirical Finding ◽  
Qualitative Approach ◽  
Lessons Learned ◽  
Current Feedback ◽  
Active Dissemination ◽  
Different Levels

In this paper empirical finding from a study conducted at an aerospace company is compared to theory regarding Experience Feedback (EF), Lessons Learned (LL) and Decision Making (DM). The purpose with the study was to examine how EF within the organization was conducted and what problems and possibilities that was seen. A qualitative approach was taken and interviews and a workshop was conducted. The empirical findings show that EF exist on different levels within the organization but current feedback processes are currently leaning more towards archiving and storing than knowledge sharing and learning. Also passive dissemination approaches are mostly used whereas active dissemination within the correct context is needed The aim with this paper is to discuss issues and empirical findings that should be considered when creating work methods and systems that support learning by EF and LL dissemination.

Arrow's Theorem and Engineering Design Decision Making

1999 ◽  
Vol 11 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Michael J. Scott ◽  
Erik K. Antonsson
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Design Decision ◽  
Arrow’S Theorem ◽  
Arrow's Theorem

A Formal Approach to Handling Conflicts in Multiattribute Group Decision Making

2005 ◽  
Vol 128 (4) ◽  
pp. 678-688 ◽  
Author(s):  
Tung-King See ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Group Decision Making ◽  
Group Decision ◽  
Decision Problems ◽  
Team Leaders ◽  
Formal Approach ◽  
Aggregation Functions ◽  
Group Members ◽  
Problem Data

Supporting the decision of a group in engineering design is a challenging and complicated problem when issues like consensus and compromise must be taken into account. In this paper, we present the foundations of the group hypothetical equivalents and inequivalents method and two fundamental extensions making it applicable to new classes of group decision problems. The first extension focuses on updating the formulation to place unequal importance on the preferences of the group members. The formulation presented in this paper allows team leaders to emphasize the input from certain group members based on experience or other factors. The second extension focuses on the theoretical implications of using a general class of aggregation functions. Illustration and validation of the developments are presented using a vehicle selection problem. Data from ten engineering design groups are used to demonstrate the application of the method.

scholarly journals Computational intelligence in product design engineering: review and trends

2021 ◽  
Author(s):  
Filippo A. Salustri
Keyword(s):  
Decision Making ◽  
Product Design ◽  
Engineering Design ◽  
Computational Intelligence ◽  
Design Automation ◽  
State Of The Art ◽  
Design Engineering ◽  
Broad Perspective ◽  
Research Issues ◽  
Product Engineering

Product design engineering is undergoing a transformation from informal and largely experience-based discipline to a science-based domain. Computational intelligence offers models and algorithms that can contribute greatly to design formalization and automation. This paper surveys computational intelligence concepts and approaches applicable to product design engineering. Taxonomy of the surveyed literature is presented according to the generally recognized areas in both product design engineering and computational intelligence. Some research issues that arise from the broad perspective presented in the paper have been signaled but not fully pursued. No survey of such a broad field can be complete, however, the material presented in the paper is a summary of state-of-the-art computational intelligence concepts and approaches in product design engineering. Keywords: Computational intelligence, engineering design, product engineering, decision making, design automation

scholarly journals Elementary Students Navigating the Demands of Giving Engineering Design Peer Feedback (Fundamental)

2020 ◽  
Author(s):  
Fatima Rahman ◽  
Chelsea Andrews ◽  
Kristen Wendell ◽  
Nicole Batrouny ◽  
Tejaswini Dalvi
Keyword(s):  
Elementary Students ◽  
Engineering Design ◽  
Peer Feedback

A Model for Make-or-Buy Decisions in Engineering Design Services Sector: A Case Study from Turkey

2018 ◽  
Vol 15 (04) ◽  
pp. 1850038
Author(s):  
Z. Aytan Ediz ◽  
M. Atilla Öner ◽  
Y. Can Erdem ◽  
Nesimi Kaplan
Keyword(s):  
Decision Making ◽  
Cluster Analysis ◽  
Engineering Design ◽  
Administrative Support ◽  
Social Dynamics ◽  
Successful Implementation ◽  
Cluster Membership ◽  
Services Sector ◽  
Engineering Company

Make-or-buy decision is an important factor affecting the profitability of the firms in all sectors. The goal of this study is to propose a model for firms in engineering design services sector for make-or-buy decisions. A survey was conducted to determine the importance percentages given in an engineering company in make-or-buy decisions and a model was developed. The results of the case study show intriguing clusters of company personnel. As the lack of consensus among company managers and personnel may inhibit the successful implementation of the developed strategy, we use K-Means Clustering to determine the different perspectives of different groups of employees (managers, senior engineers, junior engineers, technical and administrative support personnel) which may contribute to the understanding of social dynamics of decision making within the company. 4-cluster and 5-cluster analysis results indicate the need for further study on the dynamics of cluster membership.

Towards a Rational, Narrative-Based Design Framework for Navigating Radical Uncertainty in Engineering Design

2021 ◽  
Author(s):  
Kenneth M. Bryden ◽  
Scott Ferguson
Keyword(s):  
Decision Making ◽  
Engineering Design ◽  
Critical Role ◽  
Social Enterprises ◽  
Design Framework ◽  
Design Alternatives ◽  
Human Decision ◽  
Practical Engineering ◽  
Radical Uncertainty ◽  
High Level

Abstract This paper examines decision making under radical uncertainty in engineering design, that is, engineering decision making in those situations where it is not possible to know the outcomes and/or construct the utility functions and probabilities needed to support rational-human decision making. In these situations, despite being faced with radical uncertainty, engineers do (and must) proceed forward in a linear, clear, and predictable manner. Yet, they may not proceed in a manner that is well described by current engineering design frameworks. Examining the role of decision making in business and other social enterprises, Tuckett and Nikolic [1] have proposed conviction narrative theory (CNT) to describe how rational decision-makers confronted with situations in which insufficient information is available to support traditional decision-making tools use narrative and intuition to reach convincing and actionable decisions. This paper proposes that, in a manner similar to what is described in CNT, narrative and engineering judgment play a critical role in engineering design situations dominated by radical uncertainty. To that end, this paper integrates the traditional rational-human view of decision making as expressed by Hazelrigg in the well-known Decision-Based Design (DBD) framework and CNT as proposed by Tuckett and Nikolic. In the resulting rational, narrative-based design framework, narrative structures are used to describe and develop design alternatives and provide the ideas, beliefs, and preferences needed by the DBD framework. The resulting preferred design is expressed as a narrative and tested using engineering judgement. Specifically, the goal of the design process is expressed as a high-level guiding narrative that fosters the development of design narratives (design alternatives), and ultimately results in a convincing narrative that describes the preferred design. The high-level guiding narrative outlines the event(s), entity(s), preferences, and beliefs needed to support the design. The design narratives are narrative fragments that are nested within the high-level narrative and include the proposed action (idea), the specific challenges that the design faces, and the possible (but not yet verified) outcomes. The convincing narrative is the validated, preferred option that results from the DBD analysis and optimization process and is reviewed using engineering judgement. Following development of the rational, narrative-based design framework, the value of the framework is discussed within the context of practical engineering design.

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