scholarly journals QUANTUM COMBINATORIAL DESIGN

2021 ◽  
Vol 1 ◽  
pp. 2511-2520
Author(s):  
James Gopsill ◽  
Guy Johns ◽  
Ben Hicks
Keyword(s):  
Quantum Computing ◽  
Design Research ◽  
Design Space ◽  
Design Tool ◽  
Combinatorial Design ◽  
Configuration Design ◽  
Design Task ◽  
Future Design ◽  
Component Selection ◽  
Classical Computing

AbstractCombinatorial Design such as configuration design, design optioneering, component selection, and generative design, is common across engineering. Generating solutions for a combinatorial design task often involves the application of classical computing solvers that can either map or navigate design spaces. However, it has been observed that classical computing resource power-law scales with many design space models. This observation suggests classical computing may not be capable of modelling our future design space needs.To meet future design space modelling needs, this paper examines quantum computing and the characteristics that enables its resources to scale polynomially with design space size. The paper then continues to present a combinatorial design problem that is subsequently represented, constrained and solved by quantum computing. The results of which are the derivation of an initial set of circuits that represent design space constraints. The study shows the game-changing possibilities of quantum computing as an engineering design tool and is the start of an exciting new journey for design research.

On combinatorial design spaces for the configuration design of product families

2001 ◽  
Vol 15 (2) ◽  
pp. 91-108 ◽  
Author(s):  
ZAHED SIDDIQUE ◽  
DAVID W. ROSEN
Keyword(s):  
Engineering Design ◽  
Design Space ◽  
Optimization Problems ◽  
Product Family ◽  
Product Variety ◽  
Combinatorial Design ◽  
Configuration Design ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Space Modeling

For typical optimization problems, the design space of interest is well defined: It is a subset of Rn, where n is the number of (continuous) variables. Constraints are often introduced to eliminate infeasible regions of this space from consideration. Many engineering design problems can be formulated as search in such a design space. For configuration design problems, however, the design space is much more difficult to define precisely, particularly when constraints are present. Configuration design spaces are discrete and combinatorial in nature, but not necessarily purely combinatorial, as certain combinations represent infeasible designs. One of our primary design objectives is to drastically reduce the effort to explore large combinatorial design spaces. We believe it is imperative to develop methods for mathematically defining design spaces for configuration design. The purpose of this paper is to outline our approach to defining configuration design spaces for engineering design, with an emphasis on the mathematics of the spaces and their combinations into larger spaces that more completely capture design requirements. Specifically, we introduce design spaces that model physical connectivity, functionality, and assemblability considerations for a representative product family, a class of coffeemakers. Then, we show how these spaces can be combined into a “common” product variety design space. We demonstrate how constraints can be defined and applied to these spaces so that feasible design regions can be directly modeled. Additionally, we explore the topological and combinatorial properties of these spaces. The application of this design space modeling methodology is illustrated using the coffeemaker product family.

A configuration design based method for platform commonization for product families

2004 ◽  
Vol 18 (1) ◽  
pp. 21-39 ◽  
Author(s):  
BRIAN CORBETT ◽  
DAVID W. ROSEN
Keyword(s):  
Design Space ◽  
Product Family ◽  
Combinatorial Design ◽  
Product Configuration ◽  
Configuration Design ◽  
Design Problems ◽  
Product Families ◽  
Assembly Design ◽  
Assembly Sequences ◽  
Design Requirements

Product families help companies reach customers in several different markets, lessen the time needed to develop new products, and reduce costs by sharing common components among many products. The product platform can be considered as a set of technologies, components, or functions, and their arrangements, that are utilized for more than one product. Configuration design focuses on the components in a product and their connections and relationships. Discrete, combinatorial design spaces are used to model design requirements regarding physical connections, module partitions, and assembly sequences for the product family. To ensure that products satisfy all design requirements, it is necessary to combine these design spaces into a common configuration space into which all requirements can be mapped. This paper presents computational methods for modeling and combining design spaces so those configurations can be identified that satisfy all constraints. A new representation of assembly sequences facilitates the development of an assembly design space, elements of which can be enumerated readily. Because the size of the combinatorial design spaces can become quite large, computational efficiency is an important consideration. A new designer guided method, called the partitioning method, is presented for decomposing configuration design problems in a hierarchical manner that enables significant reductions in design space sizes. An example of a family of automotive underbodies illustrates the application of the discrete design space approach to develop a common platform.

Hider: A Methodology for Early-Stage Exploration of Design Space

1996 ◽  
Author(s):  
Sudhakar Y. Reddy
Keyword(s):  
Design Space ◽  
Optimization Problems ◽  
Early Stage ◽  
Simulation Models ◽  
Design Tool ◽  
System Level ◽  
Complex Simulation ◽  
Machine Learning Approach ◽  
Detailed Simulation ◽  
And Performance

Abstract This paper describes HIDER, a methodology that enables detailed simulation models to be used during the early stages of system design. HIDER uses a machine learning approach to form abstract models from the detailed models. The abstract models are used for multiple-objective optimization to obtain sets of non-dominated designs. The tradeoffs between design and performance attributes in the non-dominated sets are used to interactively refine the design space. A prototype design tool has been developed to assist the designer in easily forming abstract models, flexibly defining optimization problems, and interactively exploring and refining the design space. To demonstrate the practical applicability of this approach, the paper presents results from the application of HIDER to the system-level design of a wheel loader. In this demonstration, complex simulation models for cycle time evaluation and stability analysis are used together for early-stage exploration of design space.

Sensing Home: Designing an Open Tool That Lets People Collect and Interpret Simple Sensor Data from Their Homes

i-com ◽  
2018 ◽  
Vol 17 (2) ◽  
pp. 153-167
Author(s):  
Arne Berger ◽  
Albrecht Kurze ◽  
Sören Totzauer ◽  
Michael Storz ◽  
Kevin Lefeuvre ◽  
...  
Keyword(s):  
Design Space ◽  
Group Discussion ◽  
Design Tool ◽  
Sensor Data ◽  
Sensor Technology ◽  
The Internet ◽  
Smart Sensor ◽  
Design Rationale ◽  
Domestic Products ◽  
The Internet Of Things

AbstractThe Internet of Things in the home is a design space with huge potential. With sensors getting smaller and cheaper, smart sensor equipped objects will become an integral, preinstalled part of the future home. With this article we will reflect on Sensing Home, a design tool to explore sensors in the home together with people. Sensing Home allows people to integrate sensors and connectivity into mundane domestic products in order to make them smart. As such, it can be used by people to experience and explore sensors in the home and daily life. They may explore possible use cases, appropriate sensor technology, and learn about this technology through use. At the same time people may also be empowered to understand the issues and implications of sensors in the home. We present the design rationale of Sensing Home, five usage examples of how Sensing Home allowed people to explore sensor technology, and the deployment of Sensing Home together with a self-developed group discussion method to empower people to understand the benefits and pitfalls of sensors in their home. The article ends with a brief reflection whether Sensing Home is a probe or a toolkit.

Prototyping of microbial chassis for the biomanufacturing of high-value chemical targets

2021 ◽  
Author(s):  
Christopher J. Robinson ◽  
Jonathan Tellechea-Luzardo ◽  
Pablo Carbonell ◽  
Adrian J. Jervis ◽  
Cunyu Yan ◽  
...  
Keyword(s):  
Metabolic Engineering ◽  
Potential Role ◽  
Design Space ◽  
Scale Up ◽  
Combinatorial Design ◽  
Design Build ◽  
Biological Circuits ◽  
Genetic Constructs ◽  
Host Strains

Metabolic engineering technologies have been employed with increasing success over the last three decades for the engineering and optimization of industrial host strains to competitively produce high-value chemical targets. To this end, continued reductions in the time taken from concept, to development, to scale-up are essential. Design–Build–Test–Learn pipelines that are able to rapidly deliver diverse chemical targets through iterative optimization of microbial production strains have been established. Biofoundries are employing in silico tools for the design of genetic parts, alongside combinatorial design of experiments approaches to optimize selection from within the potential design space of biological circuits based on multi-criteria objectives. These genetic constructs can then be built and tested through automated laboratory workflows, with performance data analysed in the learn phase to inform further design. Successful examples of rapid prototyping processes for microbially produced compounds reveal the potential role of biofoundries in leading the sustainable production of next-generation bio-based chemicals.

Configuration Design: An Integrated Approach Using Grammars

1996 ◽  
Author(s):  
Linda C. Schmidt ◽  
Jonathan Cagan
Keyword(s):  
Optimal Solution ◽  
Integrated Approach ◽  
Configuration Design ◽  
Levels Of Abstraction ◽  
Component Selection ◽  
Successful Design ◽  
Design Generation ◽  
Selection Tasks ◽  
Optimal Configurations ◽  
Different Levels

Abstract A computational approach to design that integrates conceptual design, configuration design, and catalog component selection tasks overcomes some of the barriers to successful design automation. FFREADA is a design generation and optimization algorithm featuring hierarchical ordering of grammar based-design generation processes at different levels of abstraction. FFREADA is used to design hand-held, power drills and to develop an appropriate objective function for design optimization. The drill grammar expresses a vast space of design states that are not limited to any particular functional architecture or component configuration. (The algorithm’s optimization runs operate in a space which exceeds 20249 designs.) Good drill designs, those with values within 1% of the optimal solution, are found in minutes by sampling less than 0.15% of the design states. Optimal configurations are found for drills with three different torque requirements.

Towards Computer Aided Design and Analysis of Spatial Flexure Mechanisms

2016 ◽  
Author(s):  
Omer Anil Turkkan ◽  
Hai-Jun Su
Keyword(s):  
Computer Aided Design ◽  
Screw Theory ◽  
Design Tool ◽  
Future Design ◽  
Linear Elastic ◽  
Wide Range ◽  
Speed Up ◽  
System Equations ◽  
Compliance Matrices ◽  
Aided Design

Flexure mechanisms are the central part of numerous precision instruments and devices that are used in a wide range of science and engineering applications and currently, design of flexure mechanisms often heavily relies on designers’ previous hands-on experience. Therefore, a design tool that will speed up the design process is needed and this paper will introduce a systematic approach for building the necessary equations that are based on screw theory and linear elastic theory to analyze flexure mechanisms. A digital library of commonly used flexure elements must be available for a design tool and therefore, we first present the compliance matrices of commonly used flexure components. Motion twists and force wrenches of the screw theory can be related with these compliance matrices. Then, we introduce an algorithm that constructs the required linear system equations from individual compliance equations. This algorithm is applicable to flexure mechanisms with serial, parallel or hybrid chains. Finally, the algorithm is tested with a flexure mechanisms and it is shown that this approach can be the core of a future design tool.

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