Case Studies with Analytic Design Methods

2007 ◽  
pp. 443-495
Keyword(s):  
Case Studies ◽  
Design Methods ◽  
Analytic Design

Engineering AI Systems

2021 ◽  
pp. 1-19 ◽  
Author(s):  
Jan Bosch ◽  
Helena Holmström Olsson ◽  
Ivica Crnkovic
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Data Quality ◽  
Case Studies ◽  
Research Agenda ◽  
Production Quality ◽  
Research Community ◽  
Design Methods ◽  
Engineering Approach ◽  
Quality Design

Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in industry. However, based on well over a dozen case studies, we have learned that deploying industry-strength, production quality ML models in systems proves to be challenging. Companies experience challenges related to data quality, design methods and processes, performance of models as well as deployment and compliance. We learned that a new, structured engineering approach is required to construct and evolve systems that contain ML/DL components. In this chapter, the authors provide a conceptualization of the typical evolution patterns that companies experience when employing ML as well as an overview of the key problems experienced by the companies that they have studied. The main contribution of the chapter is a research agenda for AI engineering that provides an overview of the key engineering challenges surrounding ML solutions and an overview of open items that need to be addressed by the research community at large.

scholarly journals Analytic design methods for wave rotor cycles

1994 ◽  
Vol 10 (5) ◽  
pp. 683-689 ◽  
Author(s):  
Edwin L. Resler ◽  
Jeffrey C. Mocsari ◽  
M. Razi Nalim
Keyword(s):  
Design Methods ◽  
Wave Rotor ◽  
Analytic Design

scholarly journals PEVALUATING ENGINEERING DESIGN METHODS: TAKING INSPIRATION FROM SOFTWARE ENGINEERING AND THE HEALTH SCIENCES

2020 ◽  
Vol 1 ◽  
pp. 1901-1910
Author(s):  
A. M. Hein ◽  
G. Lamé
Keyword(s):  
Software Engineering ◽  
Engineering Design ◽  
Case Studies ◽  
Health Sciences ◽  
Design Methods ◽  
Evaluation Approaches

AbstractEngineering design methods are typically evaluated via case studies, surveys, and experiments. Meanwhile, domains such as the health sciences as well as software engineering have developed further powerful evaluation approaches. The objective of this paper is to show how evaluation approaches from the health sciences and software engineering might further the evaluation of engineering design methods. We survey these approaches and show which approaches could be transferred to the evaluation of engineering design methods.

Environmentally-Conscious Design Methods for Manufacturing Firms with Servicification

2009 ◽  
Vol 3 (1) ◽  
pp. 26-32 ◽  
Author(s):  
Tomohiko Sakao ◽  
◽  
Mattias Lindahl ◽  
Anna Öhrwall-Rönnbäck
Keyword(s):  
Case Studies ◽  
Manufacturing Industry ◽  
Manufacturing Firms ◽  
Design Methods ◽  
Environmentally Conscious ◽  
Economic Implications ◽  
Manufacturing Company ◽  
Environmentally Conscious Design ◽  
Empirical Case Studies

Servicification is a key toward environmental conscious business in the manufacturing industry. After looking at the business and economic implications of Integrated Product and Service Offerings, the paper suggests specifications for methods beneficial for such a manufacturing company. The paper is based on the empirical case studies of 120 Swedish manufacturing firms of different sizes. It is expected to encourage discussion on this crucial theme in mature economies such as those of Europe and Japan.

scholarly journals Masonry Italian Code-Conforming Buildings. Part 1: Case Studies and Design Methods

2018 ◽  
Vol 22 (sup2) ◽  
pp. 54-73 ◽  
Author(s):  
Carlo F. Manzini ◽  
Guido Magenes ◽  
Andrea Penna ◽  
Francesca da Porto ◽  
Daniela Camilletti ◽  
...  
Keyword(s):  
Case Studies ◽  
Design Methods

Machine Learning Algorithms for Recommending Design Methods

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Mark Fuge ◽  
Bud Peters ◽  
Alice Agogino
Keyword(s):  
Case Studies ◽  
Spectral Clustering ◽  
Design Methods ◽  
Machine Learning Algorithms ◽  
New Methods ◽  
Recommendation Algorithms ◽  
Problem Description ◽  
Novice Designers ◽  
Effective Product

Every year design practitioners and researchers develop new methods for understanding users and solving problems. This increasingly large collection of methods causes a problem for novice designers: How does one choose which design methods to use for a given problem? Experienced designers can provide case studies that document which methods they used, but studying these cases to infer appropriate methods for a novel problem is inefficient. This research addresses that issue by applying techniques from content-based and collaborative filtering to automatically recommend design methods, given a particular problem. Specifically, we demonstrate the quality with which different algorithms recommend 39 design methods out of an 800+ case study dataset. We find that knowing which methods occur frequently together allows one to recommend design methods more effectively than just using the text of the problem description itself. Furthermore, we demonstrate that automatically grouping frequently co-occurring methods using spectral clustering replicates human-provided groupings to 92% accuracy. By leveraging existing case studies, recommendation algorithms can help novice designers efficiently navigate the increasing array of design methods, leading to more effective product design.

scholarly journals Thinking the Transformative

Dimensions ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 85-94
Author(s):  
Steffen Bösenberg
Keyword(s):  
Decision Making ◽  
Case Studies ◽  
Adaptive Reuse ◽  
Design Methods ◽  
Circular Motion ◽  
Working Process ◽  
Doctoral Thesis ◽  
Dynamic Dimension

Editorial Summary Steffen Bösenberg’s contribution »Thinking the Transformative« reflects the dynamic momentum of reflexive design and research. In reference to the working process of his doctoral thesis, he highlights the procedural circularity of reflexive, concept-driven research approaches, tracing the »circular motion of constant reflection and rethinking«. Hereby a transdisciplinary concept of »plasticity« is explored as a productive tool in the analysis of design methods in adaptive reuse. Decision-making, reconsideration, comparison or evaluation thereby become considerable as reciprocally interlinked processes, which equally depend upon and shape each other. Most interestingly, the transformation and plasticity of the process mirrors the dynamic dimension of the investigated case studies. [Katharina Voigt]

scholarly journals Enhancing the benefits of group involvement in research

Groupwork ◽  
2021 ◽  
Vol 30 (1) ◽  
Author(s):  
Alice Home
Keyword(s):  
Case Studies ◽  
Design Methods ◽  
Mutual Trust ◽  
Research Subjects ◽  
Community Groups ◽  
Mutual Learning ◽  
Practical Usefulness ◽  
Working Together ◽  
Community Issues ◽  
Group Involvement

Research can facilitate mutual learning, allow participants’ voices to be heard, increase practical usefulness of studies and foster empowerment. This paper discusses ways that groups can take part in research, outlines advantages and limits of each and explores strategies for enhancing benefits. This content is illustrated with brief examples from recent research publications and from two longer case studies. Groups and members can be involved as participants or co-producers of research. As participants, they either act as research subjects by contributing data, or as collaborators who are consulted at various times to help keep a study relevant to community issues. Being a subject offers an opportunity to reflect and share views, while collaborators and researchers can learn from working together. Though collaborators can exert influence, they have little control over decisions around focus, design, methods or dissemination of a study.  Co-producing knowledge offers community groups more power, learning and empowerment but requires high levels of mutual trust, commitment and persistence. Potential gains and risks increase as involvement intensifies. However, researchers can enhance benefits at any level, by keeping this goal in mind when planning studies.

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