Study on the Organization Model for the Design Process Modular of Complex Mechanical Product

2012 ◽  
Vol 538-541 ◽  
pp. 2990-2994
Author(s):  
Jun Zheng
Keyword(s):  
Product Design ◽  
Design Process ◽  
Directed Acyclic Graph ◽  
Semantic Relations ◽  
Design Knowledge ◽  
Modular Approach ◽  
Organization Model ◽  
Acyclic Graph ◽  
Knowledge Based ◽  
Special Collections

In order to provide knowledge service more efficiently for complex mechanical product design, a knowledge organization model for complex mechanical product design knowledge based on the process modular approach was proposed. First, a general form, the knowledge instance, would be used to represent all forms of the knowledge for complex mechanical product design; then, based on the contents and features of the knowledge instances and the semantic relations in the domain ontology, the special collections of the knowledge instances which have related features would be composed to knowledge modules, and knowledge modules would be organized as a DAG(directed acyclic graph). The complex mechanical product design knowledge could be efficiently and completely queried based-on semantic according to the logical relationships expressed in the DAG.

Retrieval and Clustering for Multiple Disciplines Design Knowledge Based on Ontology and Semantic

2013 ◽  
Vol 300-301 ◽  
pp. 155-159 ◽  
Author(s):  
Guo Hai Zhang ◽  
Yu Sheng Li
Keyword(s):  
Semantic Web ◽  
Product Development ◽  
Product Design ◽  
Design Knowledge ◽  
Knowledge Retrieval ◽  
Calculation Methods ◽  
Specific Calculation ◽  
Complex Product ◽  
The Third ◽  
Knowledge Based

This paper presents a new kind of retrieval and clustering solution for multiple disciplines design knowledge during complex product development. The main contributions of this study can be focused on four points: The first is to distinguish the concepts and contents of ontology theories and semantic web. The second is to map the distinction and relationship between concepts to similarity and correlation of product design knowledge. The substances of conceptual hierarchy are introduced and their formal descriptions are given in the article. The third is to explore the specific calculation methods for semantic similarity and relevancy using the above theories and approaches. Finally, a model for design knowledge retrieval if proposed, and the tactics for knowledge retrieval and clustering are given.

Study on Knowledge-Based Product Design Framework for Facilitating the Interaction of Model Based Development and Prototyping

2014 ◽  
Vol 8 (3) ◽  
pp. 344-355 ◽  
Author(s):  
Yutaka Nomaguchi ◽  
◽  
Masashi Mizuta ◽  
Masaya Hirooka ◽  
Kikuo Fujita
Keyword(s):  
Product Design ◽  
Design Process ◽  
Modeling Language ◽  
Design Tools ◽  
Design Framework ◽  
Mechatronic System ◽  
Mechatronic Systems ◽  
Design Concepts ◽  
Model Based ◽  
Knowledge Based

Model-based development is a potential approach to designing complicated mechatronic systems. This paper proposes a product design framework for mechatronic systems, which integrates model-based development with prototyping and focuses on its process of deployment with hypothesis and verification. SysML is adopted as the modeling language for representing the mechatronic system without depending on specific domains, and FMEA is adopted as the method for describing the results of validation by prototyping. The DRIFT framework is used to capture designer’s operations on the design tools of SysML and FMEA and to manage its process. This study defines design concepts and design operations that are extracted from the patterns embedded in design process with SysML and FMEA. A design example of a ball-sorting robot is created using LEGO Mindstorms to demonstrate the proposed framework.

scholarly journals Product Advanced Design: A Cultural Intermediation Between Knowledge and Information

2021 ◽  
Vol 74 (74) ◽  
Author(s):  
Elisabetta Cianfanelli ◽  
Margherita Tufarelli ◽  
Maria Claudia Coppola
Keyword(s):  
Product Development ◽  
Product Design ◽  
High Intensity ◽  
Applied Research ◽  
Digital Transformation ◽  
Design Knowledge ◽  
Advanced Stage ◽  
Research Experience ◽  
Design And Development ◽  
Knowledge Based

"Digital transformation (DX) drives transversal change, breaking disciplinary silos to transition to more sustainable paradigms through new ontological and epistemological frameworks. This has consequences on product design and development too: since DX concerns cultural and meaning shifts, it enhances product development as a high-intensity knowledge-based process. Thus, product design shifts into its “Advanced” stage, enacting transcendence and translation of different kinds of knowledge into future-oriented artefacts. This highlights new needs in the generation and transmission of Advanced Design knowledge stemming from future artefact production instances. By focusing on recent challenges rising in product design and development, this paper aims to discuss the cultural intermediation enacted by Advanced Design knowledge through the results of an applied research experience."

A Model for Acquisition of Implicit Design Knowledge Based on KDD

2006 ◽  
Vol 505-507 ◽  
pp. 505-510
Author(s):  
Jing Min Li ◽  
Jin Yao ◽  
Yong Mou Liu
Keyword(s):  
Knowledge Acquisition ◽  
Knowledge Discovery ◽  
Product Design ◽  
Domain Knowledge ◽  
Design System ◽  
Design Knowledge ◽  
Knowledge Based ◽  
Knowledge Discovery In Database ◽  
Knowledge Intensive ◽  
Set Up

Knowledge discovery in database (KDD) represents a new direction of data processing and knowledge innovation. Design is a knowledge-intensive process driven by various design objectives. Implicit knowledge acquisition is key and difficult for the intelligent design system applied to mechanical product design. In this study, the characteristic of implicit design knowledge and KDD are analyzed, a model for product design knowledge acquisition is set up, and the key techniques including the expression and application of domain knowledge and the methods of knowledge discovery are discussed. It is illustrated by an example that the method proposed can be used to obtain the engineering knowledge in design case effectively, and can promote the quality and intelligent standard of product design.

Cyberphysical Design Automation Framework for Knowledge-based Engineering

2013 ◽  
Vol 1 (1) ◽  
pp. 158-178
Author(s):  
Urcun John Tanik
Keyword(s):  
System Design ◽  
Design Process ◽  
Design Automation ◽  
Design Theory ◽  
Knowledge Bases ◽  
Knowledge Based ◽  
Knowledge Based Engineering ◽  
Cyberphysical System ◽  
Automation Framework

Cyberphysical system design automation utilizing knowledge based engineering techniques with globally networked knowledge bases can tremendously improve the design process for emerging systems. Our goal is to develop a comprehensive architectural framework to improve the design process for cyberphysical systems (CPS) and implement a case study with Axiomatic Design Solutions Inc. to develop next generation toolsets utilizing knowledge-based engineering (KBE) systems adapted to multiple domains in the field of CPS design automation. The Cyberphysical System Design Automation Framework (CPSDAF) will be based on advances in CPS design theory based on current research and knowledge collected from global sources automatically via Semantic Web Services. A case study utilizing STEM students is discussed.

The design of modular oil tank: A new design process model

2020 ◽  
Vol 15 ◽  
Author(s):  
Jin Li ◽  
Xingsheng Jiang ◽  
Jingye Li ◽  
Yadong Zhao ◽  
Xuexing Li
Keyword(s):  
Product Design ◽  
Design Process ◽  
Process Model ◽  
Mechanical Design ◽  
Computer Software ◽  
Reference Value ◽  
Fuel Tank ◽  
Design Quality ◽  
Design Time ◽  
Design Process Model

Background: In the whole design process of modular fuel tank, there are some unreasonable phenomena. As a result, there are some defects in the design of modular fuel tank, and the function does not meet the requirements in advance. This paper studies this problem. Objective: Through on-the-spot investigation of the factory, a mechanical design process model is designed. The model can provide reference for product design participants on product design time and design quality, and can effectively solve the problem of low product design quality caused by unreasonable product design time arrangement. Methods: After sorting out the data from the factory investigation, computer software is used to program, simulate the information input of mechanical design process, and the final reference value is got. Results: This mechanical design process model is used to guide the design and production of a new project, nearly 3 months ahead of the original project completion time. Conclusion: This mechanical design process model can effectively guide the product design process, which is of great significance to the whole mechanical design field.

scholarly journals Triple-Helix Structured Model Based on Problem-Knowledge-Solution Co-evolution for Innovative Product Design Process

2020 ◽  
Vol 33 (1) ◽  
Author(s):  
Qian Hui ◽  
Yan Li ◽  
Ye Tao ◽  
Hongwei Liu
Keyword(s):  
Product Design ◽  
Design Process ◽  
Design Problem ◽  
Triple Helix ◽  
Problem Solution ◽  
Innovative Product ◽  
Innovative Design ◽  
Structured Model ◽  
Knowledge Spaces ◽  
Product Design Process

AbstractA design problem with deficient information is generally described as wicked or ill-defined. The information insufficiency leaves designers with loose settings, free environments, and a lack of strict boundaries, which provides them with more opportunities to facilitate innovation. Therefore, to capture the opportunity behind the uncertainty of a design problem, this study models an innovative design as a composite solving process, where the problem is clarified and resolved from fuzziness to satisfying solutions by interplay among design problems, knowledge, and solutions. Additionally, a triple-helix structured model for the innovative product design process is proposed based on the co-evolution of the problem, solution, and knowledge spaces, to provide designers with a distinct design strategy and method for innovative design. The three spaces interact and co-evolve through iterative mappings, including problem structuring, knowledge expansion, and solution generation. The mappings carry the information processing and decision-making activities of the design, and create the path to satisfying solutions. Finally, a case study of a reactor coolant flow distribution device is presented to demonstrate the practicability of this model and the method for innovative product design.

scholarly journals IoT-enabled directed acyclic graph in spark cluster

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Jahwan Koo ◽  
Nawab Muhammad Faseeh Qureshi ◽  
Isma Farah Siddiqui ◽  
Asad Abbas ◽  
Ali Kashif Bashir
Keyword(s):  
Distributed Computing ◽  
Real Time ◽  
Directed Acyclic Graph ◽  
Random Access ◽  
Heterogeneous Data ◽  
The Body ◽  
Computing Environment ◽  
Time Data ◽  
Acyclic Graph ◽  
Sensory Data

Abstract Real-time data streaming fetches live sensory segments of the dataset in the heterogeneous distributed computing environment. This process assembles data chunks at a rapid encapsulation rate through a streaming technique that bundles sensor segments into multiple micro-batches and extracts into a repository, respectively. Recently, the acquisition process is enhanced with an additional feature of exchanging IoT devices’ dataset comprised of two components: (i) sensory data and (ii) metadata. The body of sensory data includes record information, and the metadata part consists of logs, heterogeneous events, and routing path tables to transmit micro-batch streams into the repository. Real-time acquisition procedure uses the Directed Acyclic Graph (DAG) to extract live query outcomes from in-place micro-batches through MapReduce stages and returns a result set. However, few bottlenecks affect the performance during the execution process, such as (i) homogeneous micro-batches formation only, (ii) complexity of dataset diversification, (iii) heterogeneous data tuples processing, and (iv) linear DAG workflow only. As a result, it produces huge processing latency and the additional cost of extracting event-enabled IoT datasets. Thus, the Spark cluster that processes Resilient Distributed Dataset (RDD) in a fast-pace using Random access memory (RAM) defies expected robustness in processing IoT streams in the distributed computing environment. This paper presents an IoT-enabled Directed Acyclic Graph (I-DAG) technique that labels micro-batches at the stage of building a stream event and arranges stream elements with event labels. In the next step, heterogeneous stream events are processed through the I-DAG workflow, which has non-linear DAG operation for extracting queries’ results in a Spark cluster. The performance evaluation shows that I-DAG resolves homogeneous IoT-enabled stream event issues and provides an effective stream event heterogeneous solution for IoT-enabled datasets in spark clusters.

Risk identification and modeling for blockchain-enabled container shipping

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Son Nguyen ◽  
Peggy Shu-Ling Chen ◽  
Yuquan Du
Keyword(s):  
Design Methodology ◽  
Directed Acyclic Graph ◽  
Risk Identification ◽  
Container Shipping ◽  
Content Type ◽  
Acyclic Graph ◽  
Operational Risks ◽  
Systems Security ◽  
Event Risk ◽  
Potential Risks

PurposeAlthough being considered for adoption by stakeholders in container shipping, application of blockchain is hindered by different factors. This paper investigates the potential operational risks of blockchain-integrated container shipping systems as one of such barriers.Design/methodology/approachLiterature review is employed as the method of risk identification. Scientific articles, special institutional reports and publications of blockchain solution providers were included in an inclusive qualitative analysis. A directed acyclic graph (DAG) was constructed and analyzed based on network topological metrics.FindingsTwenty-eight potential risks and 47 connections were identified in three groups of initiative, transitional and sequel. The DAG analysis results reflect a relatively well-connected network of identified hazardous events (HEs), suggesting the pervasiveness of information risks and various multiple-event risk scenarios. The criticality of the connected systems' security and information accuracy are also indicated.Originality/valueThis paper indicates the changes of container shipping operational risk in the process of blockchain integration by using updated data. It creates awareness of the emerging risks, provides their insights and establishes the basis for further research.

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