Computer-Aided Design Ideation Using InnoGPS

2019 ◽  
Author(s):  
Jianxi Luo ◽  
Serhad Sarica ◽  
Kristin L. Wood
Keyword(s):  
Computer Aided Design ◽  
Data Science ◽  
Design Science ◽  
Data Driven ◽  
Process Data ◽  
Science Data ◽  
Design Concepts ◽  
Patent Classification ◽  
Computer Aided ◽  
Design Ideation

Abstract Traditionally, the ideation of design opportunities and new concepts relies on human expertise or intuition and is faced with high uncertainty. Inexperienced or specialized designers often fail to explore ideas broadly and become fixed on specific ideas early in the design process. Recent data-driven design methods provide external design stimuli beyond one’s own knowledge, but their uses in rapid ideation are still limited. Intuitive and directed ideation techniques, such as brainstorming, mind mapping, Design-by-Analogy, SCAMPER, TRIZ and Design Heuristics may empower designers in rapid ideation but are limited in the designer’s own knowledge base. Herein, we harness data-driven design and rapid ideation techniques to introduce a data-driven computer-aided rapid ideation process using the cloud-based InnoGPS system. InnoGPS integrates an empirical network map of all technology domains based on the international patent classification which are connected according to knowledge distance based on patent data, with a few map-based functions to position technologies, explore neighborhoods, and retrieve knowledge, concepts and solutions in the near or far fields for design analogies and syntheses. The functions of InnoGPS fuse design science, network science, data science and interactive visualization and make the design ideation process data-driven, theoretically-grounded, visually-inspiring, and rapid. We demonstrate the procedures of using InnoGPS as a data-driven rapid ideation tool to generate new rolling toy design concepts.

Representing analogies to influence fixation and creativity: A study comparing computer-aided design, photographs, and sketches

2015 ◽  
Vol 29 (2) ◽  
pp. 161-171 ◽  
Author(s):  
Olufunmilola Atilola ◽  
Julie Linsey
Keyword(s):  
Computer Aided Design ◽  
Idea Generation ◽  
Generation Process ◽  
Critical Question ◽  
Design Fixation ◽  
Design Concepts ◽  
Computer Aided ◽  
Aided Design ◽  
Effective Design

AbstractMany tools are being developed to assist designers in retrieving analogies. One critical question these designers face is how these analogues should be represented in order to minimize design fixation and maximize idea generation. To address this question, an experiment is presented that compares various representations' influence on creativity and design fixation. This experiment presents an effective example (analogue) as computer-aided design (CAD), sketch, or photograph representations. We found that all representations induced fixation, and the degree of fixation did not vary significantly. We also found that CAD representations encourage engineering designers to identify and copy the key effective features of the example. CAD and photo representations also produced a higher quality of design concepts. Results from this experiment offer insights into how these various representations may be used in examples during idea generation; CAD representations appear to offer the greatest advantages during the idea generation process. The results from this experiment also indicate that analogical databases of effective design examples should include CAD and photolike images of the analogue rather than sketches.

scholarly journals Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining

2021 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Berend Denkena ◽  
Marcel Wichmann ◽  
Klaas Maximilian Heide ◽  
René Räker
Keyword(s):  
Computer Aided Design ◽  
Laser Scanning ◽  
Numerical Control ◽  
Software Systems ◽  
Process Data ◽  
Computer Aided ◽  
Cad Cam ◽  
Scan Paths ◽  
Interference Signals ◽  
Aided Design

The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection.

scholarly journals A Data-Driven Approach to Appraisal and Selection at a Domain Data Repository

2018 ◽  
Vol 12 (2) ◽  
Author(s):  
Amy M Pienta ◽  
Dharma Akmon ◽  
Justin Noble ◽  
Lynette Hoelter ◽  
Susan Jekielek
Keyword(s):  
Data Driven ◽  
Data Repository ◽  
Search Activity ◽  
Process Data ◽  
Science Data ◽  
Social Scientists ◽  
Data Repositories ◽  
The Social ◽  
Data Driven Approach ◽  
User Demand

Social scientists are producing an ever-expanding volume of data, leading to questions about appraisal and selection of content given finite resources to process data for reuse. We analyze users’ search activity in an established social science data repository to better understand demand for data and more effectively guide collection development. By applying a data-driven approach, we aim to ensure curation resources are applied to make the most valuable data findable, understandable, accessible, and usable. We analyze data from a domain repository for the social sciences that includes over 500,000 annual searches in 2014 and 2015 to better understand trends in user search behavior. Using a newly created search-to-study ratio technique, we identified gaps in the domain data repository’s holdings and leveraged this analysis to inform our collection and curation practices and policies. The evaluative technique we propose in this paper will serve as a baseline for future studies looking at trends in user demand over time at the domain data repository being studied with broader implications for other data repositories.

A Computer-Aided Design Based Research Platform for Design Thinking Studies

2019 ◽  
Vol 141 (12) ◽  
Author(s):  
Molla Hafizur Rahman ◽  
Corey Schimpf ◽  
Charles Xie ◽  
Zhenghui Sha
Keyword(s):  
Decision Making ◽  
Design Process ◽  
Computer Aided Design ◽  
Design Thinking ◽  
Data Driven ◽  
Clustering Methods ◽  
Fine Grained ◽  
Research Platform ◽  
Computer Aided ◽  
Aided Design

Abstract Design thinking is often hidden and implicit, so empirical approach based on experiments and data-driven methods has been the primary way of doing such research. In support of empirical studies, design behavioral data which reflects design thinking becomes crucial, especially with the recent advances in data mining and machine learning techniques. In this paper, a research platform that supports data-driven design thinking studies is introduced based on a computer-aided design (cad) software for solar energy systems, energy3d, developed by the team. We demonstrate several key features of energy3d including a fine-grained design process logger, embedded design experiment and tutorials, and interactive cad interfaces and dashboard. These features make energy3d a capable testbed for a variety of research related to engineering design thinking and design theory, such as search strategies, design decision-making, artificial intelligent (AI) in design, and design cognition. Using a case study on an energy-plus home design challenge, we demonstrate how such a platform enables a complete research cycle of studying designers” sequential decision-making behaviors based on fine-grained design action data and unsupervised clustering methods. The results validate the utility of energy3d as a research platform and testbed in supporting future design thinking studies and provide domain-specific insights into new ways of integrating clustering methods and design process models (e.g., the function–behavior–structure model) for automatically clustering sequential design behaviors.

Study on Three-Dimension Computer Aided Process Planning System

2011 ◽  
Vol 121-126 ◽  
pp. 1316-1320
Author(s):  
Lei Chen ◽  
Ming Ran Deng
Keyword(s):  
Process Planning ◽  
Computer Aided Design ◽  
Process Model ◽  
Planning System ◽  
Three Dimension ◽  
Process Data ◽  
Computer Aided Process Planning ◽  
Cad System ◽  
Computer Aided ◽  
Working Procedure

Aiming at the problem of process data update and working procedure model, the three-dimension CAPP (Computer Aided Process Planning) based on three-dimension CAD (Computer Aided Design) is proposed. The core of the system is the process model that is used to transfer data between CAPP and CAD system. This system can solve the problem of two-dimension CAPP based on parameter feature modeling of three-dimension CAD and has been applied to some aviation enterprises in china.

scholarly journals Data-driven smart sustainable cities of the future: urban computing and intelligence for strategic, short-term, and joined-up planning

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Simon Elias Bibri
Keyword(s):  
Big Data ◽  
Decision Support ◽  
Data Science ◽  
Smart Cities ◽  
Data Driven ◽  
Sustainable Cities ◽  
Short Term ◽  
Science Data ◽  
Urban Computing ◽  
The Future

AbstractSustainable cities are quintessential complex systems—dynamically changing environments and developed through a multitude of individual and collective decisions from the bottom up to the top down. As such, they are full of contestations, conflicts, and contingencies that are not easily captured, steered, and predicted respectively. In short, they are characterized by wicked problems. Therefore, they are increasingly embracing and leveraging what smart cities have to offer as to big data technologies and their novel applications in a bid to effectively tackle the complexities they inherently embody and to monitor, evaluate, and improve their performance with respect to sustainability—under what has been termed “data-driven smart sustainable cities.” This paper analyzes and discusses the enabling role and innovative potential of urban computing and intelligence in the strategic, short-term, and joined-up planning of data-driven smart sustainable cities of the future. Further, it devises an innovative framework for urban intelligence and planning functions as an advanced form of decision support. This study expands on prior work done to develop a novel model for data-driven smart sustainable cities of the future. I argue that the fast-flowing torrent of urban data, coupled with its analytical power, is of crucial importance to the effective planning and efficient design of this integrated model of urbanism. This is enabled by the kind of data-driven and model-driven decision support systems associated with urban computing and intelligence. The novelty of the proposed framework lies in its essential technological and scientific components and the way in which these are coordinated and integrated given their clear synergies to enable urban intelligence and planning functions. These utilize, integrate, and harness complexity science, urban complexity theories, sustainability science, urban sustainability theories, urban science, data science, and data-intensive science in order to fashion powerful new forms of simulation models and optimization methods. These in turn generate optimal designs and solutions that improve sustainability, efficiency, resilience, equity, and life quality. This study contributes to understanding and highlighting the value of big data in regard to the planning and design of sustainable cities of the future.

scholarly journals Interactive communication between the user and the computer-aided design system of shaft forging on presses

2018 ◽  
Vol 224 ◽  
pp. 04001 ◽  
Author(s):  
Sergey Kanyukov ◽  
Anatoly Konovalov ◽  
Olga Muizemnek
Keyword(s):  
Programming Languages ◽  
Computer Aided Design ◽  
Subject Area ◽  
Design System ◽  
Interactive Communication ◽  
Design Concepts ◽  
Computer Aided ◽  
Process Documentation ◽  
Open Die Forging ◽  
Aided Design

Despite the accelerated development of computer technology, programming languages and methods in recent years, computer-aided design of open-die forging on presses is still not widespread due to weak formalization of the subject area. Therefore, the developers of relevant computer-aided systems have to put “approximate” algorithms and programs into the systems for solving technological problems. As a result, they provide users with the ability to adjust design concepts by a graphic dialogue. The paper describes a mechanism of interactive communication between the user and the computer-aided design system of shaft forging on presses, which was developed at the Institute of Engineering Science of the Russian Academy of Sciences (Ural Branch). This system provides wide opportunities for making necessary adjustments in a forging drawing and a forging process map. This ensures obtaining necessary design and process documentation suitable for using in the production process, even when the algorithms and programs are imperfect. Moreover, it significantly facilitates the implementation of the system at various enterprises.

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