Knowledge Recommendation System for Human-Robot Collaborative Disassembly Using Knowledge Graph

2021 ◽  
Author(s):  
Yang Hu ◽  
Yiwen Ding ◽  
Feng Xu ◽  
Jiayi Liu ◽  
Wenjun Xu ◽  
...  
Keyword(s):  
Recommendation System ◽  
Industrial Robots ◽  
Knowledge Graph ◽  
Disassembly Process ◽  
Knowledge Based ◽  
Manufacturing Efficiency ◽  
Human Operators ◽  
Traditional Manufacturing ◽  
Human Robot Collaboration

Abstract In recent years, more and more attention has been paid to Human-Robot Collaborative Disassembly (HRCD) in the field of industrial remanufacturing. Compared with the traditional manufacturing, HRCD helps to improve the manufacturing flexibility with considering the manufacturing efficiency. In HRCD, knowledge could be obtained from the disassembly process and then provides useful information for the operator and robots to execute their disassembly tasks. Afterwards, a crucial point is to establish a knowledge-based system to facilitate the interaction between human operators and industrial robots. In this context, a knowledge recommendation system based on knowledge graph is proposed to effectively support Human-Robot Collaboration (HRC) in disassembly. A disassembly knowledge graph is constructed to organize and manage the knowledge in the process of HRCD. After that, based on this, a knowledge recommendation procedure is proposed to recommend disassembly knowledge for the operator. Finally, the case study demonstrates that the developed system can effectively acquire, manage and visualize the related knowledge of HRCD, and then assist the human operator to complete the disassembly task by knowledge recommendation, thus improving the efficiency of collaborative disassembly. This system could be used in the human-robot collaboration disassembly process for the operators to provide convenient knowledge recommendation service.

scholarly journals Event driven Recommendation System for E-commerce using Knowledge based Collaborative Filtering Technique

2020 ◽  
Vol 21 (3) ◽  
pp. 369-378
Author(s):  
Mahesh Kumar Singh ◽  
Om Prakash Rishi
Keyword(s):  
Collaborative Filtering ◽  
Domain Knowledge ◽  
Recommendation System ◽  
Evaluation Studies ◽  
Knowledge Graph ◽  
Knowledge Based ◽  
Target User ◽  
Online Trading ◽  
User Data ◽  
Two Phases

The Internet is changing the method of selling and purchasing items. Nowadays online trading replaces offline trading. The items offered by the online system can influence the nature of buying customers. The recommendation system is one of the basic tools to provide such an environment. Several techniques are used to design and implement the recommendation system. Every recommendation system passes from two phases similarity computation among the users or items and correlation between target user and items. Collaborative filtering is a common technique used for designing such a system. The proposed system uses a knowledge base generated from knowledge graph to identify the domain knowledge of users, items, and relationships among these, knowledge graph is a labelled multidimensional directed graph that represents the relationship  among the users and the items. Almost every existing recommendation system is based on one of feature, review, rating, and popularity of the items in which users’ involvement is very less or none. The proposed approach uses about 100 percent of users’ participation in the form of activities during navigation of the web site. Thus, the system expects under the users’ interest that is beneficial for both seller and buyer. The proposed system relates the category of items, not just specific items that may be interested in the users. We see the effectiveness of this approach in comparison with baseline methods in the area of recommendation system using three parameters precision, recall, and NDCG through online and offline evaluation studies with user data, and its performance is better than all other baseline systems in all aspects.

scholarly journals Collaborative Workplace Design: A Knowledge-Based Approach to Promote Human–Robot Collaboration and Multi-Objective Layout Optimization

2021 ◽  
Vol 11 (24) ◽  
pp. 12147
Author(s):  
Andrea Rega ◽  
Castrese Di Marino ◽  
Agnese Pasquariello ◽  
Ferdinando Vitolo ◽  
Stanislao Patalano ◽  
...  
Keyword(s):  
Complex Problem ◽  
Optimization Criterion ◽  
Layout Design ◽  
Industrial Case Study ◽  
Manufacturing Plants ◽  
Knowledge Based ◽  
Control Factors ◽  
Modeling Paradigm ◽  
Human Robot Collaboration

The innovation-driven Industry 5.0 leads us to consider humanity in a prominent position as the center of the manufacturing field even more than Industry 4.0. This pushes us towards the hybridization of manufacturing plants promoting a full collaboration between humans and robots. However, there are currently very few workplaces where effective Human–Robot Collaboration takes place. Layout designing plays a key role in assuring safe and efficient Human–Robot Collaboration. The layout design, especially in the context of collaborative robotics, is a complex problem to face, since it is related to safety, ergonomics, and productivity aspects. In the current work, a Knowledge-Based Approach (KBA) is adopted to face the complexity of the layout design problem. The framework resulting from the KBA allows for developing a modeling paradigm that enables us to define a streamlined approach for the layout design. The proposed approach allows for placing resource within the workplace according to a defined optimization criterion, and also ensures compliance with various standards. This approach is applied to an industrial case study in order to prove its feasibility. A what-if analysis is performed by applying the proposed approach. Changing three control factors (i.e., minimum distance, robot speed, logistic space configuration) on three levels, in a Design of Experiments, 27 layout configurations of the same workplace are generated. Consequently, the inputs that most affect the layout design are identified by means of an Analysis of Variance (ANOVA). The results show that only one layout is eligible to be the best configuration, and only two out of three control factors are very significant for the designing of the HRC workplace layout. Hence, the proposed approach enables the designing of standard compliant and optimized HRC workplace layouts. Therefore, several alternatives of the layout for the same workplace can be easily generated and investigated in a systematic manner.

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.

scholarly journals Semantic knowledge based reasoning framework for human robot collaboration

Procedia CIRP ◽  
2021 ◽  
Vol 97 ◽  
pp. 373-378
Author(s):  
Sharath Chandra Akkaladevi ◽  
Matthias Plasch ◽  
Michael Hofmann ◽  
Andreas Pichler
Keyword(s):  
Semantic Knowledge ◽  
Knowledge Based ◽  
Human Robot Collaboration

scholarly journals Semantic and knowledge based support to business model evaluation to stimulate green behaviour of electric vehicles’ drivers and energy prosumers

2021 ◽  
Author(s):  
Beniamino Di Martino ◽  
Dario Branco ◽  
Luigi Colucci Cante ◽  
Salvatore Venticinque ◽  
Reinhard Scholten ◽  
...  
Keyword(s):  
Business Model ◽  
Model Evaluation ◽  
Business Models ◽  
Real Case ◽  
Sustainable Mobility ◽  
Semantic Framework ◽  
Knowledge Based ◽  
Survey Results ◽  
Energy Prosumers

AbstractThis paper proposes a semantic framework for Business Model evaluation and its application to a real case study in the context of smart energy and sustainable mobility. It presents an ontology based representation of an original business model and examples of inferential rules for knowledge extraction and automatic population of the ontology. The real case study belongs to the GreenCharge European Project, that in these last years is proposing some original business models to promote sustainable e-mobility plans. An original OWL Ontology contains all relevant Business Model concepts referring to GreenCharge’s domain, including a semantic description of TestCards, survey results and inferential rules.

scholarly journals “Splendid Isolation”: The reproduction of music industry inequalities in Spotify’s recommendation system

2021 ◽  
pp. 146144482110221
Author(s):  
Tamas Tofalvy ◽  
Júlia Koltai
Keyword(s):  
Network Analysis ◽  
Recommendation System ◽  
Music Industry ◽  
Country Of Origin ◽  
Small Scale ◽  
Primary Determinant ◽  
Scale Network ◽  
Splendid Isolation

In this article, we argue that offline inequalities, such as core–periphery relations of the music industry, are reproduced by streaming platforms. First, we offer an overview of the reproduction of inequalities and core–periphery dynamics in the music industry. Then we illustrate this through a small-scale network analysis case study of Hungarian metal bands’ connections on Spotify. We show that the primary determinant of a given band’s international connectedness in Spotify’s algorithmic ecosystem is their international label connections. Bands on international labels have more reciprocal international connections and are more likely to be recommended based on actual genre similarity. However, bands signed with local labels or self-published tend to have domestic connections and to be paired with other artists by Spotify’s recommendation system according to their country of origin.

Knowledge transfer roles of subsidiaries in MNCs’ networks

2019 ◽  
Vol 29 (4) ◽  
pp. 329-346 ◽  
Author(s):  
Cigdem Baskici
Keyword(s):  
Knowledge Transfer ◽  
Single Case ◽  
Research Question ◽  
Hierarchical Structures ◽  
Knowledge Flows ◽  
Consumer Electronics ◽  
Knowledge Network ◽  
Content Type ◽  
Knowledge Based

Purpose Although there have been a considerable number of studies regarding subsidiary role typology in multinationals’ management literature, there appear to be few studies that consider knowledge-based role typology from the network-based perspective. The purpose of this study is to fill this gap and extend the study of Gupta and Govindarajan (1991). Thus, the study focuses on answering the following research question: Do subsidiaries have different roles in terms of knowledge flows within a multinational company (MNC)? Design/methodology/approach This empirical study has been carried out as an explorative single case study. An MNC with 15 foreign subsidiaries headquartered in Turkey, which operated in the manufacturing of household appliances and consumer electronics, has been selected as the case. Knowledge transfer is analyzed in this MNC from the network perspective. Findings Four role typologies are detected for subsidiaries of the MNC: collector transmitter, collector diffuser, converter transmitter and converter diffuser. Research limitations/implications Findings of this study are specific to this case. Testing the findings in a sample consisting of subsidiaries of MNCs producing transnational products may contribute to the generalizability of these roles. Practical implications This study offers potentially important findings for MNC managers to use. First, in this study, knowledge flows' route could be defined within MNCs’ dual network. Second, role typologies could inform MNC managers to design their MNCs’ knowledge network. Originality/value The suggested typologies are expected to more accurately define the roles of subsidiaries within contemporary MNCs which are accepted to be transformed from hierarchical structures to network-based organizations.

DEVELOPMENT OF A KNOWLEDGE-BASED INTELLIGENT CAD SYSTEM FOR AUTOMOTIVE PANEL DIE

2008 ◽  
Vol 07 (01) ◽  
pp. 51-54 ◽  
Author(s):  
HUI-XIA LIU ◽  
WEI WEI ◽  
XIAO WANG ◽  
LAN CAI
Keyword(s):  
Die Design ◽  
Design System ◽  
Working Process ◽  
Cad System ◽  
Knowledge Based ◽  
Working Principle ◽  
Panel Die ◽  
Automotive Panels ◽  
Automotive Panel

A knowledge-based intelligent die design system for automotive panels is developed by UG software platform. This system can accomplish design intelligently and automatically through engineering rules in the knowledge base. The framework and implementation of the system are discussed. Finally, a case study of the panel die design of car trunk in the system is implemented, which illustrates working process, working principle, implement method and practicability of the system, and validates the advanced design conception proposed in this paper.

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