scholarly journals Design space exploration for flexibility assessment and decision making support in integrated industrial building design

2021 ◽  
Author(s):  
Julia Reisinger ◽  
Maximilian Knoll ◽  
Iva Kovacic
Keyword(s):  
Decision Making ◽  
Design Process ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
Building Design ◽  
Assessment Tools ◽  
Industrial Building ◽  
Industrial Buildings

AbstractIndustrial buildings play a major role in sustainable development, producing and expending a significant amount of resources, energy and waste. Due to product individualization and accelerating technological advances in manufacturing, industrial buildings strive for highly flexible building structures to accommodate constantly evolving production processes. However, common sustainability assessment tools do not respect flexibility metrics and manufacturing and building design processes run sequentially, neglecting discipline-specific interaction, leading to inflexible solutions. In integrated industrial building design (IIBD), incorporating manufacturing and building disciplines simultaneously, design teams are faced with the choice of multiple conflicting criteria and complex design decisions, opening up a huge design space. To address these issues, this paper presents a parametric design process for efficient design space exploration in IIBD. A state-of-the-art survey and multiple case study are conducted to define four novel flexibility metrics and to develop a unified design space, respecting both building and manufacturing requirements. Based on these results, a parametric design process for automated structural optimization and quantitative flexibility assessment is developed, guiding the decision-making process towards increased sustainability. The proposed framework is tested on a pilot-project of a food and hygiene production, evaluating the design space representation and validating the flexibility metrics. Results confirmed the efficiency of the process that an evolutionary multi-objective optimization algorithm can be implemented in future research to enable multidisciplinary design optimization for flexible industrial building solutions.

Enabling parametric design space exploration by non-designers

2020 ◽  
Vol 34 (2) ◽  
pp. 160-175 ◽  
Author(s):  
Eduardo Castro e Costa ◽  
Joaquim Jorge ◽  
Aaron D. Knochel ◽  
José Pinto Duarte
Keyword(s):  
User Interface ◽  
Mass Customization ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
End Users ◽  
Parametric Models ◽  
Direct Manipulation ◽  
Barycentric Interpolation

AbstractIn mass customization, software configurators enable novice end-users to design customized products and services according to their needs and preferences. However, traditional configurators hardly provide an engaging experience while avoiding the burden of choice. We propose a Design Participation Model to facilitate navigating the design space, based on two modules. Modeler enables designers to create customizable designs as parametric models, and Navigator subsequently permits novice end-users to explore these designs. While most parametric designs support direct manipulation of low-level features, we propose interpolation features to give customers more flexibility. In this paper, we focus on the implementation of such interpolation features into Navigator and its user interface. To assess our approach, we designed and performed user experiments to test and compare Modeler and Navigator, thus providing insights for further developments of our approach. Our results suggest that barycentric interpolation between qualitative parameters provides a more easily understandable interface that empowers novice customers to explore the design space expeditiously.

Many-Attribute Decision Making Using Iterative Attribute Subsets

2016 ◽  
Author(s):  
Laura Ziegler ◽  
Kemper Lewis
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Decision Problems ◽  
Trade Off ◽  
Current Design ◽  
Multi Attribute Decision Making

A unique set of cognitive and computational challenges arise in large-scale decision making, in relation to trade-off processing and design space exploration. While several multi-attribute decision making methods exist in the current design literature, many are insufficient or not fully explored for many-attribute decision problems of six or more attributes. To address this scaling in complexity, the methodology presented in this paper strategically elicits preferences over iterative attribute subsets while leveraging principles of the Hypothetical Equivalents and Inequivalents Method (HEIM). A case study demonstrates the effectiveness of the approach in the construction of a systematic representation of preferences and the convergence to a single ‘best’ alternative.

Building design-space exploration through quasi-optimization of life cycle impacts and costs

2018 ◽  
Vol 144 ◽  
pp. 34-44 ◽  
Author(s):  
Joshua Hester ◽  
Jeremy Gregory ◽  
Franz-Josef Ulm ◽  
Randolph Kirchain
Keyword(s):  
Life Cycle ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Building Design

scholarly journals Design space exploration revisited

2006 ◽  
Vol 20 (2) ◽  
pp. 113-119 ◽  
Author(s):  
PIETER H.G. VAN LANGEN ◽  
FRANCES M.T. BRAZIER
Keyword(s):  
Design Process ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Explicit Representation ◽  
Design Exploration ◽  
Partial Design ◽  
Additional Information ◽  
Design Object ◽  
Design Requirements

Design involves reasoning about descriptions of design artifacts, reasoning about design requirements, and reasoning about design process objectives (such as keeping to deadlines and available budget). Reasoning about these three aspects occurs during exploration, generation, and evaluation of partial design descriptions. Design space exploration involves exploration in all three related spaces: the space of partial descriptions of design artifacts, the space of design requirements, and the space of design process objectives. These spaces are vast. Explicit representation of the relations between elements in these three spaces provides the additional information needed to understand and reuse descriptions of partial design process traces, and to guide design exploration. In their Keynote Article, Woodbury and Burrow describe one of these spaces, namely, the space of design object descriptions, as a network of partial and intentional descriptions of design artifacts. The links between partial descriptions represent paths in design processes. Making the information compiled in these paths of exploration explicit, as proposed in this paper, extends the approach described by Woodbury and Burrow, increasing options for accessibility.

Toward Implementing Quantifiable Social Justice Metrics in the Design Process

2016 ◽  
Author(s):  
Douglas L. Van Bossuyt ◽  
Jered Dean
Keyword(s):  
Social Justice ◽  
Design Process ◽  
Design Space Exploration ◽  
Engineering Students ◽  
Design Space ◽  
Space Exploration ◽  
Colorado School ◽  
Undergraduate Engineering ◽  
The Social ◽  
Promising Area

The recent increased popularity in teaching social justice in an engineering context has revealed issues related to implementing social justice criteria in a design process. Recent experiences with undergraduate engineering students from a variety of disciplines at the Colorado School of Mines indicate that quantifying the six social justice criteria may aid in the understanding and acceptance of social justice in the design process. This paper presents our efforts toward quantifying the social justice criteria and implementing that quantification into the design process as a set of metrics that can be tracked and potentially used as part of a design space exploration or optimization effort. While the implications of quantifying and using social justice criteria as part of the design process may at first seem ripe for misuse or misunderstanding, we have found our students more receptive of social justice as an integral part of engineering design when presented in the proposed quantified manner. Much work remains to be done to fully integrate social justice into the design process. The initial efforts to more strongly link social justice with the design process and findings of that effort are presented in this paper and indicate that this is a promising area of further research.

scholarly journals Design of mechatronic systems through aspect and object-oriented modeling

2016 ◽  
Vol 64 (3) ◽  
Author(s):  
Giacomo Barbieri ◽  
Patricia Derler ◽  
David M. Auslander ◽  
Roberto Borsari ◽  
Cesare Fantuzzi
Keyword(s):  
Computer Science ◽  
Design Process ◽  
Design Space Exploration ◽  
Design Space ◽  
Space Exploration ◽  
Object Oriented ◽  
Mechatronic Systems ◽  
Modeling Tools

AbstractDesign of mechatronic systems involves the use of multiple disciplines, from mechanics to electronics and computer science. Different granularities of hybrid co-simulations with increasing details can be used during the design process. However, there is the need of modeling tools for effectively managing the necessary abstraction layers. This work proposes a combination of Aspect-Oriented and Object-Oriented modeling for reaching the goal. Moreover, it shows how the utilization of these tools can facilitate design-space exploration, segregation of domains of expertise and enhances co-design.

scholarly journals Performance Driven Design Space Exploration for Multi-Objective Optimization Using Stability in Competition

2021 ◽  
Author(s):  
Summit Sehgal
Keyword(s):  
Real Estate ◽  
Analytical Approach ◽  
Design Space Exploration ◽  
Design Space ◽  
Parametric Design ◽  
Space Exploration ◽  
Systems Development ◽  
Performance Parameters ◽  
Multi Objective Optimization ◽  
Systems Architecture

Multi Parametric Design Space Exploration (DSE) for optimal micro-architecture synthesis is an extremely complex yet crucial stage in embedded systems development. Often it is very time complex to find the best suitable configuration to map the inherently contradictory performance parameters into systems silicon real estate. Owing to its exponentially exploding design space and multi way combinatorial mapping, DSE has proven to be notoriously hard and intractable for VLSI CAD tools. The presented work introduces a highly scalable and generalized analytical approach to identify the best configuration of systems architecture while maintaining prime accuracy resolution. This DSE approach coupled with

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