Collaborative Product Design Research Articles

An integrated framework for collaborative product design and assembly based on STEP compatible ontology model in cloud manufacturing

AbstractNowadays, new product development processes are encountering fast design and development cycles. This issue has become one the main competition factors among industries. Accordingly, companies make drastic efforts to enhance the quality and speed in the realm of designing and manufacturing by taking novel approaches. Using the potential of new technologies, they design and develop products worldwide, and integrate stakeholders in the collaborative process to achieve this goal. This study has aimed at laying a foundation to fulfill the requirements for globalized collaborative product development processes. This creates an opportunity for both an integrated and collaborative environment. As first objective, the paper has proposed STEP Standard-based model in the form of a cloud service model to create an integrated data structure for product design data while giving flexibility for service-oriented access to integrated model. For second objective, using the Ontology interoperability model, the collaborative design among the stakeholders has been enabled through smart interference control. This control interprets the data semantic to an ontology structure and detects the potential conflicts. The model supports two levels of parts in singular and collective form and based on the assembly scheme for collaborative design and development. Different facets of the proposed model are addressed to fulfill the necessity of real-time distributed collaboration in designing and assembling via a case study.

A simple method and case study of task planning for collaborative design based on FDSM

A simple method and case study of task planning for collaborative design based on FDSM

XMKR: Explainable manufacturing knowledge recommendation for collaborative design with graph embedding learning

XMKR: Explainable manufacturing knowledge recommendation for collaborative design with graph embedding learning

A Data-Driven Human–Machine Collaborative Product Design System Toward Intelligent Manufacturing

A Data-Driven Human–Machine Collaborative Product Design System Toward Intelligent Manufacturing

Retracted: Text Knowledge Acquisition Method of Collaborative Product Design Based on Genetic Algorithm

Retracted: Text Knowledge Acquisition Method of Collaborative Product Design Based on Genetic Algorithm

ОПЫТНО-ЭКСПЕРИМЕНТАЛЬНАЯ РАБОТА ПО ФОРМИРОВАНИЮ ПРЕДПРИНИМАТЕЛЬСКОЙ КОМПЕТЕНТНОСТИ СТУДЕНТОВ МЕДИЦИНСКИХ ВУЗОВ

The article reveals the fact that the formation of entrepreneurial competence of medical students at this stage of society development is one of the priority areas. Many universities have included disciplines aimed at developing the entrepreneurial potential of young people in their educational programs for training specialists. Our study is unique in that there are few medical schools that work with this topic in the process of preparing students. Many medical students are not well prepared for this new challenge. In order to form a certain level of entrepreneurial competence among students of medical universities, the author conducted a scientific and independent experimental work, the results are obtained. The results of experimental work on the formation of entrepreneurial competence of students of medical universities show that the author’s model, which combines the knowledge and experience of students, really increases the effectiveness of student training in terms of entrepreneurial competence. This model focuses on three criterion dimensions. In the scientific work of students, criteria-based assessments were identified and substantiated for the development offurther practical research. The students were trained by a team of teachers of economics and a medical university. Interactive opportunities for students are provided through simulation content, role play, collaborative product design, and simulation.

Building a Design-Rationale-Centric Knowledge Network to Realize the Internalization of Explicit Knowledge

A large number of publicly available documents, including patent documents and journal articles, can provide designers with creative stimuli, which could facilitate product innovation and collaborative design. As an important tacit knowledge, the acquisition, sharing, and reuse of design rationale (DR) is of great value to designers, which could help designers to better understand design intentions and ideas, support design automation, and promote better collaborative design. However, due to the fragmentation of DR in documentation, this hinders designer acquisition and reuse. If the DR fragments could be automatically extracted from the technical documents to build an interconnected knowledge network system, the problem would be effectively solved, which would further promote the development and utilization of digital archives. To address this issue, this study proposes a three-dimensional design knowledge network metamodel, Design Knowledge Semantic Network (DKSN), and a DKSN-based knowledge fusion method for the construction of a Design Knowledge Network (DKN). We set up an empirical experiment to verify the feasibility and performance of the method. Patent documents and open access research articles are used as sample documents, and a product data dictionary imported from ISO/TS 23768-1 is used as the predefined artifact dictionary. The results further confirm the feasibility and good application prospects of the proposed method.

A semantic similarity-based method to support the conversion from EXPRESS to OWL

Abstract Product data sharing is fundamental for collaborative product design and development. Although the STandard for Exchange of Product model data (STEP) enables this by providing a unified data definition and description, it lacks the ability to provide a more semantically enriched product data model. Many researchers suggest converting STEP models to ontology models and propose rules for mapping EXPRESS, the descriptive language of STEP, to Web Ontology Language (OWL). In most research, this mapping is a manual process which is time-consuming and prone to misunderstandings. To support this conversion, this research proposes an automatic method based on natural language processing techniques (NLP). The similarities of language elements in the reference manuals of EXPRESS and OWL have been analyzed in terms of three aspects: heading semantics, text semantics, and heading hierarchy. The paper focusses on translating between language elements, but the same approach has also been applied to the definition of the data models. Two forms of the semantic analysis with NLP are proposed: a Combination of Random Walks (RW) and Global Vectors for Word Representation (GloVe) for heading semantic similarity; and a Decoding-enhanced BERT with disentangled attention (DeBERTa) ensemble model for text semantic similarity. The evaluation shows the feasibility of the proposed method. The results not only cover most language elements mapped by current research, but also identify the mappings of the elements that have not been included. It also indicates the potential to identify the OWL segments for the EXPRESS declarations.

Member combination selection for product collaborative design under the open innovation model

Member combination selection for product collaborative design under the open innovation model

Knowledge transferring and conversion in the early stage of collaborative product design by entrepreneurial teams

PurposeThe purpose of the study is to discover a model of knowledge conversion and knowledge transferring/sharing barriers in an entrepreneurial team (ET) working with innovative users at the early and fuzzy front end (FFE) stage of collaborative product design (Co-PD) process.Design/methodology/approachThe exploratory research framework included sampling, data collection and data analysis, through sequential levels of categorizations, undertaken jointly with constant comparative analysis. The sample frame is the pool of ETs/startups from university business accelerators that carry out Co-PD at the FFE stage. The research survey is based on observations of the collaborative ETs activities, questionnaires and in-depth interviews with them. The research was conducted on individual and team levels when Co-PD process and ET activities were in progress.FindingsThis study identified specific set of concepts of knowledge conversion and transferring/sharing and their barriers that reflect specificity of Co-PD processes at the FFE stage in collaborative ETs. The discovered conversion process is represented by the socialization, externalization and internalization, three-mode knowledge conversion model. The significance of barriers and frequency of their occurrence were measured in knowledge transferring/sharing in collaborative ETs on individual and team levels.Originality/valueThis study shows novel insights into how knowledge transfers/shares and converts in the context of ET working with innovative users in Co-PD process at the FFE stage.

A multitask context-aware approach for design lesson-learned knowledge recommendation in collaborative product design

A multitask context-aware approach for design lesson-learned knowledge recommendation in collaborative product design

Retracted] Text Knowledge Acquisition Method of Collaborative Product Design Based on Genetic Algorithm

In order to overcome the problems of poor clustering effect and large error of text knowledge acquisition in traditional text knowledge acquisition methods, a new text knowledge acquisition method of collaborative product design based on genetic algorithm is proposed in this paper. The definition of collaborative product design text knowledge clustering is given. According to the operation process of the genetic algorithm, the chromosomes of clustered text are constructed and encoded and the initial population is obtained. The fitness function of clustering is constructed by the DB index evaluation method; the selection, crossover, and mutation operators in the genetic algorithm are determined; and the objective function of collaborative product design text knowledge clustering is constructed. After the text knowledge clustering is completed, the text knowledge data of collaborative product design are obtained in an all‐around way by using the method of rough set and neural network. The experimental results show that compared with the traditional text knowledge acquisition methods, the clustering effect of the proposed method is better and the text knowledge error is reduced up to 0.02.

A Study on Consumer Preference and Purchase Intention for the Feature of Chinese Fashion Brands for Collaborative Product Design For female college students in Huabei, China

본 연구는 중국 여대생에 대한 중국 패션브랜드의 컬래버레이션 제품디자인에 따른 소비자의 호감도 및 구매의도를 분석하고, 중국 패션산업에서 소비자가 선호하는 패션제품을 개발하는 방향과 마케팅 전략을 제시하는 것이 목적이다. 연구목적을 달성하기 위해 중국 화베이(华北)지역에 거주하는 여자 대학생들을 대항으로 2021년 4월 28일부터 2021년 5월 28일 기간 동안 온라인으로 설문조사를 실시하였다. 총 227부의 설문지를 최종 분석대상으로 사용하였다. 분석결과는 다음과 같다. 첫째, 본 연구에서의 컬래버레이션 제품의 특성은 독특성, 상징성, 희소성, 심미성으로 분류되었다. 둘째, 중국 패션 브랜드의 컬래버레이션 제품디자인의 독특성, 심미성은 소비자 호감도에 영향을 미치는 것으로 나타났으며 상징성, 희소성은 소비자의 호감도에 영향을 미치지 않는 것으로 나타났다. 셋째, 중국 패션브린드의 컬래버레이션 제품디자인의 독특성, 상징성, 희소성, 심미성은 소비자 구매의도에 직접적 영향은 미치지 않는 것으로 나타났다. 넷째, 중국 패션브랜드의 컬래버레이션 제품디자인에 대한 소비자의 호감도는 구매의도에 영향을 미치는 것으로 나타났다.This study analyzes consumers preference and purchase intentions for Chinese female college students according to the collaboration product design of Chinese fashion brands. The goal of the research is to present the direction of developing fashion products favored by consumers and marketing strategies in the Chinese fashion industry. To achieve their research goals, a survey of female university students living in China Huabei region was conducted online from Apri 28, 2021 and to May 28, 2021. A total of 227 questionnaires were used for final analysis. The analysis results are as follows: First, the characteristics of collaboration products in this work were classified as uniqueness, symbolism, scarcity, aesthetics. Second, the uniqueness and aesthetics of the collaboration product design of Chinese fashion brands have been shown to affect consumer favorability, while symbolism and scarcity have no effect on consumer favorability. Third, the uniqueness, symbolism, scarcity, and aesthetics of the collaboration product design of Chinese fashion brands do not affect consumer purchase intentions. Fourth, consumers preference for the collaboration product design of Chinese fashion brands has been shown to affect their purchasing intentions.

An approach to user knowledge acquisition in product design

An approach to user knowledge acquisition in product design

A collective intelligence oriented three-layer framework for socialized and collaborative product design

A collective intelligence oriented three-layer framework for socialized and collaborative product design

A New Method of Identifying Core Designers and Teams Based on the Importance and Similarity of Networks.

In the process of product collaborative design, the association between designers can be described by a complex network. Exploring the importance of the nodes and the rules of information dissemination in such networks is of great significance for distinguishing its core designers and potential designer teams, as well as for accurate recommendations of collaborative design tasks. Based on the neighborhood similarity model, combined with the idea of network information propagation, and with the help of the ReLU function, this paper proposes a new method for judging the importance of nodes—LLSR. This method not only reflects the local connection characteristics of nodes but also considers the trust degree of network propagation, and the neighbor nodes' information is used to modify the node value. Next, in order to explore potential teams, an LA-LPA algorithm based on node importance and node similarity was proposed. Before the iterative update, all nodes were randomly sorted to get an update sequence which was replaced by the node importance sequence. When there are multiple largest neighbor labels in the propagation process, the label with the highest similarity is selected for update. The experimental results in the related networks show that the LLSR algorithm can better identify the core nodes in the network, and the LA-LPA algorithm has greatly improved the stability of the original LPA algorithm and has stably mined potential teams in the network.

The art of packaging: An investigation on Modern Packaging Design and Artistic Thinking under the Background of Big Data

ABSTRACT Big data technology with the in-depth development of big data technology has allowed various 8 fields to boost industrial development. The designers have analyzed the skills required for 9 creating modern packaging design and artistic thinking through big data. After analysis, the 10 designers optimize their product design and try to enrich product packaging design connotation. 11 This paper first conducts an in-depth analysis of the theoretical concepts. In the context of big 12 data analysis, this study discusses big data characteristics and investigated the relationship 13 between modern packaging design techniques and artistic thinking. It further analyzes modern 14 packaging design techniques under big data background, including cultural connotations, 15 composition techniques, and color scheme. Under the background of big data analysis, these 16 papers discuss applying artistic thinking in modern packaging design and provides theoretical 17 references for modern product packaging design. REFERENCES [1] C. Jiang and C.H. Gao. Product Design Thinking in the Context of Big Data. Journal of Ningbo Institute of Technology, 28(4):37–42, 2016. [2] Y.L. Ren and Q. Fan. Research on the Applicability of Big Data in Product Design Research. Packaging Engineering, 36(20):139–142, 2015. [3] Z. Wen. Product Packaging Design Based on Big Data Analysis. Green Packaging, 3(5):72–76, 2018. [4] B.B. Liu, R. Zhang, and X. Chen. Product Color Design Based on Big Data. Packaging Engineering, 41(14):17–21, 2019. [5] H.Y. Huang. Research on Product Design Based on Interaction. Packaging World, 31(1):65–65, 2019. [6] W.L. Ma. Management and Application of Art Design Resources in the Construction of Big Data—Taking the School of Art and Design of Beijing University of Technology as an Example. Art Education, 24(1):231–232, 2017. [7] X.D. Shang. Application of Big Data Ideas in Product Design Market Research. Modern Decoration (Theory), 15(6):255–255, 2014. [8] Y.J. Ye and Y.X. Wu. A Preliminary Study of Internet Product Design Decisions in the Big Data Era. Popular Literature, 13(5):91–92, 2019. [9] L.L. Fan. Research on Fashion Design Methods of Industrial Products in the Big Data Era. Furniture and Interior Decoration, 27(1):32–33, 2020. [10] G.N. Miao. Research on Key Points of Complex Product Collaborative Design based on Cloud Service. Art Technology, 29(8):270–270, 2016.

Design and Integration of JMF-Based Multimedia-Supported Environment in a Product Data Management System

In order to meet discipline experts' requirements of knowledge exchange, conflict resolution, and design decision in the collaborative product design process, a JMF-based multimedia-supported environment (MSE) is proposed. The requirement to develop the MSE for multi-disciplinary collaborative design process is analyzed. Related key technologies of multimedia applications required to build the integrated MSE are described. Construction of multimedia interaction mode, design of system architecture, and formulation of development plan are implemented. Discipline experts' roles are defined, and safety certification function of application programs is achieved. Based on the development platform of Java 2 enterprise edition (J2EE), the realization of the system is completed, and the system is integrated into a previously developed product data management system. Through system experiment and test, the JMF-based system environment can well meet the needs of multimedia real-time interaction, knowledge sharing, and collaborative decision making in the process of collaborative product design.

An Augmented Reality Collaborative Product Design Cloud-Based Platform in the Context of Learning Factory

An Augmented Reality Collaborative Product Design Cloud-Based Platform in the Context of Learning Factory

The Architecture of a Product Collaborative Design Platform Based on Cloud Manufacturing

The Architecture of a Product Collaborative Design Platform Based on Cloud Manufacturing