Mereotopological assembly joint information representation for collaborative product design

Ontology-based assembly design and information sharing for collaborative product development

The New Product Development (NPD) is a series of processes that go through several stages beginning with an initial product concept or idea that is evaluated, developed, tested and launched on the market. NPD is a very important process for the company so that the products can be well received by consumers with a cost effective and faster time to market. Many concepts in NPD have been studied previously starting from the concept of User Centered System Design, Design for Manufacture and Assembly (DFMA), Make or Buy Analysis, and Supplier Integration as well as new concepts in the form of collaborative product design. However, To the authors' knowledge, there is limited published literature which has comprehensively integrated these several concepts. The purpose of this paper is to conduct a critical review of the existing body of knowledge from Collaborative Product Design by linking to the concepts of DFMA, User Centered System Design, Make or Buy Analysis, and Supplier Integration. Literature review of manually selected papers based on topic relevance is used to see existing research on each of these topic. Each topic is then carried out a critical review related to the strengths and weaknesses of the each. The findings of this study can facilitate the understanding of status quo and future research direction or a roadmap to achieve New Product Design cost effective and time to market by integrating collaborative product design with User Centered Design, DFMA, Make or Buy Analysis, and Supplier Integration.

This paper proposes a framework for building product information model (PIM) and product rule model (PRM), and integrated reasoning based on Description Frame Logic (DFL) [1] for collaborative product engineering environments. Most of the previous research has focused either on building ontology for PIM or on building a rule base for PRM respectively, not on both of them. Some research on product engineering has tried to build both ontology language and rule-language. But, the research is/has been limited to using both languages in a homogeneous approach under open world assumption (OWA) such as Web Ontology Language (OWL)/Semantic Web Rule Language (SWRL), which has some drawbacks to accommodate the requirements of enhanced expressivity for collaborative product engineering. We adopt Description Frame Logic (DFL) framework to integrate product semantics in PIM and engineering-specific knowledge in PRM based on description logic (DL) and logic programming (LP) under both open world assumption (OWA) and closed world assumption (CWA). This enables to secure seamless and interactive reasoning between PIM and PRM. We also include rule-expressions and constraint checking with DL for PIM while we include DL-expression in rules and LP’s non-logical features for PRM. This provides enhancement of expressiveness required for product engineering. Additionally, we show the benefits of the proposed framework with a case study.

Collaborative product design is a typical complex problem-solving process where designers' knowledge and expertise are always tactic and implicit. This paper depicts the concept of design scenario and the scenario-based design knowledge acquiring in a cognitive approach. Through a cognitive experiment based on protocol analysis and sketch analysis in terms of scenario-based collaborative product design, a model of scenario-based knowledge acquiring in product design is proposed. The model includes two types of spontaneous design knowledge acquiring method - concept-driven knowledge acquiring and data-driven knowledge acquiring, which indicates that design knowledge acquiring is a process of scenario moving. On the basis of the model, a scenario-based computer aided product design system CBID is developed to improve the ability and quality of collaborative product design of seven Chinese corporations.

Product design tends to be more complex and needs the effective cooperation among multidisciplinary designers and engineers. An ideal product design environment, which is both collaborative and intelligent, will be much appreciated. Agent technology is an innovative and promising approach to implementing distributed systems and is becoming popular in various areas of computing in recent years. In this paper, the dynamic nature of collaborative design process and the representation of collaborative design knowledge are presented. In order to model constantly evolving design process and the rationales resulted from collaboration, a Collaborative Product Data Model (CPDM), which extends traditional Product Data Model (PDM), and a constraint-based Collaborative Design Process Model (CDPM) are proposed. These are intended to facilitate the management and coordination of collaborative product design process and knowledge management. A design example is used to illustrate CDPM. While the system is being implemented, the architecture of our agent-based collaborative product design environment based on CPDM and CDPM is described.

Advent of internet made abundant of medical data available in various formats. Emerging technologies like AI, big data, machine learning and sematic web are increasingly applied in various sectors. Healthcare is the essential field which requires technological support in order to administer healthcare workforce, to improve the quality of healthcare services in resource constrained region, to manage the chronic diseases and pandemics like Covid-19 and so on. The supply of precise data to the technical system plays a significant role in providing better healthcare support than the available unorganized data. With the help of ontologies, semantic web represents the conceptual relationship between data more precisely. The accurate semantic rule and query engine provides effective definition of rules and knowledge retrieval from ontologies. In the medical field ontologies are used to represent medical terms, interoperability between systems with lexically different but semantically similar terms. It enhances the reuse and sharing of medical information and patient data. Also increases the percentage of support to integration of data and knowledge. The proposed case study considered Covid-19 ontology with 158 classes and maximum depth of 12 levels. Information retrieval from the knowledgebase is done using Simple Protocol and RDF Query Language (SPARQL), and Semantic Web Rule Language (SWRL). Simple queries can be formulated using Natural language based template. Additional knowledge can also be generated from the available information. This chapter ensures the effective utilization of information thereby enrich interoperability, integration and information retrieval.

As living standards improve, modern products need to meet increasingly diversified and personalized user requirements. Traditional product design methods fall short due to their strong subjectivity, limited survey scope, lack of real-time data, and poor visual display. However, recent progress in big data and artificial intelligence (AI) are bringing a transformative big data and AI-driven product design methodology with a significant impact on many industries. Big data in the product lifecycle contains valuable information, such as customer preferences, market demands, product evaluation, and visual display: online product reviews reflect customer evaluations and requirements, while product images contain shape, color, and texture information that can inspire designers to quickly generate initial design schemes or even new product images. This survey provides a comprehensive review of big data and AI-driven product design, focusing on how big data of various modalities can be processed, analyzed, and exploited to aid product design using AI algorithms. It identifies the limitations of traditional product design methods and shows how textual, image, audio, and video data in product design cycles can be utilized to achieve much more intelligent product design. We finally discuss the major deficiencies of existing data-driven product design studies and outline promising future research directions and opportunities, aiming to draw increasing attention to modern AI-driven product design.

This paper analyzed the main features of product design and manufacturing in the knowledge management environment and service oriented management model based on collaborative. Based on the analysis of these two aspects, this paper puts forward the four key problems which the collaborative design activities in manufacturing supply chain will face in knowledge representation and knowledge converting and knowledge reuse and knowledge management. At last, a framework for collaborative product design(CPD) knowledge management model in manufacturing supply chain based on ontology is established under the application background of integrated platform for collaborative product design in manufacturing enterprise.

Clustering rule bases using ontology-based similarity measures

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

1.2 What are the main phases of product design and development Before discuss the collaboration issues for product design and development, we need to briefly review the phases of product design and development. The major phases of product design and development are normally defined as conceptual design, preliminary design, and detail design and development (Blanchard, 2004). During the conceptual design phase, the concepts, which are also called scheme, are built in order to completely and efficiently design the transceiver. The concepts may include such as product operational requirements and maintenance, current product problem (or deficiency), functional analysis for the product, applicable technical performance measures (TPMs), and specific performance measures and design-to criteria. Preliminary design phase begins with a “functional baseline” product configuration described in the product specification prepared during conceptual design phase. The functional baseline is translated into detailed qualitative and quantitative design requirements for allocating applicable elements of the product. An “allocated baseline” configuration in the form of development, product, and process specifications is established during this phase. At the beginning of detail design and

In today's global world, manufacturers are facing many challenges such as product design with distributed and collaborative workflows. Complexity in collaborative product design arises from the need to synthesize different perspectives of a problem. Specifically, dependency identification of the product design process, as well as integration and sharing of computing application among the design teams that are critical for efficiency of manufacturability. Web services are considered to be the key to collaborative product design through the Internet. Web services alone are passive whereas agents can provide alerts and updates when new information becomes available. In this paper, an agent-based Web services architecture is proposed and applied to augment manufacturability. Not only the agent-based Web services architecture makes system interoperation feasible, but also increases the efficiency of the distributed collaboration.

This paper aims to explore the design of intelligent products based on the needs of elderly users. Based on the existing literature results, the possibility of design intervention in the management of chronic diseases of the elderly was proposed, and the general characteristics and behavioral characteristics of the elderly users were studied by questionnaire method, the acceptability and subjective attitude of the elderly in using intelligent products and services were found, and the survey results were analyzed by mathematical statistics. The results showed that older people who considered it necessary to record physical data were higher than those who did not. With the increase of education, the proficiency of using mobile phone also increases; According to the elderly’s score of functional needs, the function with the highest score is automatic detection, followed by automatic analysis, remote consultation, diet therapy and community communication. Finally, based on the questionnaire survey results, this paper developed the design practice of intelligent medical products for hypertension, a common chronic disease of the elderly, and proposed the design strategy of intelligent products and services for chronic disease management of the elderly.

To achieve efficient development of high-quality product, manufacturing constraints must be fully taken into account at the early design stage. However, designers lack in-depth knowledge of manufacturing and production. Many time-consuming iterations of design changes are required between designers and manufacturing engineers. In order to minimize this knowledge gap, this paper presents an ontology-based product design framework for manufacturability verification and knowledge reuse to support the sharing and reuse of design and manufacturing knowledge. It aims at providing advices and feedback of restraints of manufacturing processes to the designers during the design process. The proposed framework consists of three major layers which include a foundation layer, a domain layer, and an instance layer. We use the Web Ontology Language (OWL), a standard of ontology representation language, to formalize the foundation layer. It contains the core product model and the standard ISO 10303 AP224 application protocol. The domain layer comprises extensional concepts and relationships for design and manufacturing integration and a rule base for manufacturability verification, which is represented in Semantic Web Rule Language (SWRL). In the instance layer, an inference engine is developed based on ontology and rule inference. It provides recommendations of manufacturability. Two case studies are provided as application examples to demonstrate the effectiveness of the framework.

The paper discusses the introduction of an innovative human-oriented Collaborative Manufacturing Environment (CME) into the next generation of digital manufacturing. Following an overview of the current state-of-the-art, the conceptual background of the overall CME has been given. The CME will provide support for data analysis, visualisation, advanced inter-action and presence, ergonomic analysis, and collaborative decision-making. The paper also focuses on the module supporting of the collaborative product and process design. The innovative aspect, being the seam-less integration of virtual reality and decision making principles is also analyzed. The module will help “define” the proper solutions to the design or re-conceptualization problems, based on collaborative interactions and testing, which can occur in virtual environments.