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  • 1.
    Jiang, Yuning
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Atif, Yacine
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Ding, Jianguo
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    A Semantic Framework With Humans in the Loop for Vulnerability-Assessment in Cyber-Physical Production Systems2020Inngår i: Risks and Security of Internet and Systems: 14th International Conference, CRiSIS 2019, Hammamet, Tunisia, October 29–31, 2019, Proceedings / [ed] Slim Kallel, Frédéric Cuppens, Nora Cuppens-Boulahia, Ahmed Hadj Kacem, Springer, 2020, Vol. 12026, s. 128-143Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Criticalmanufacturingprocessesinsmartnetworkedsystems such as Cyber-Physical Production Systems (CPPSs) typically require guaranteed quality-of-service performances, which is supported by cyber- security management. Currently, most existing vulnerability-assessment techniques mostly rely on only the security department due to limited communication between di↵erent working groups. This poses a limitation to the security management of CPPSs, as malicious operations may use new exploits that occur between successive analysis milestones or across departmental managerial boundaries. Thus, it is important to study and analyse CPPS networks’ security, in terms of vulnerability analysis that accounts for humans in the production process loop, to prevent potential threats to infiltrate through cross-layer gaps and to reduce the magnitude of their impact. We propose a semantic framework that supports the col- laboration between di↵erent actors in the production process, to improve situation awareness for cyberthreats prevention. Stakeholders with dif- ferent expertise are contributing to vulnerability assessment, which can be further combined with attack-scenario analysis to provide more prac- tical analysis. In doing so, we show through a case study evaluation how our proposed framework leverages crucial relationships between vulner- abilities, threats and attacks, in order to narrow further the risk-window induced by discoverable vulnerabilities.

  • 2.
    Lindblom, Jessica
    et al.
    Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningscentrum för Informationsteknologi.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Towards an Evaluation Framework of Safety, Trust, and Operator Experience in Different Demonstrators of Human-Robot Collaboration2018Inngår i: Advances in Manufacturing Technology XXXII: Proceedings of the 16th International Conference on Manufacturing Research, incorporating the 33rd National Conference on Manufacturing Research, September 11–13, 2018, University of Skövde, Sweden / [ed] Peter Thorvald, Keith Case, Amsterdam: IOS Press, 2018, s. 145-150Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Advancements in human-robot collaboration (HRC) are regarded as major aspects of the future Industry 4.0. HRC entails humans that cooperatively work with robots in dynamic, changing, and unpredictable settings where they should assist and learn from each other and automatically respond to changes. This requires research and development to investigate and evaluate how these hybrid collaborative systems should function and distribute work. The common practice is to focus on performance-related issues, which are highly influenced by human factors (HF). Because of the prevailing orientation towards HF, HRC runs the risk of not considering the modern understandings of human cognition and technology-mediated activity, in which humans are considered as actors (not factors) in a socio-material context. Although HF is dominant and well justified, the problem is that it may hinder general development, because it is not aligned with the modern understanding of cultivating a safety culture that promotes continuous improvements and development as an inherent attitude of companies and work practices. Taking an opposite approach, where the human operators working together with robots are playing active and positive roles in constructing safety, trust, and good operator experience. Hence, the collaborative human-robot system perspective addresses the need to develop and assess new evaluation methods that consider aspects like safety, trust, and operator experience from modern understandings of human cognition and technology-mediated activity, where also different levels of in human-robot collaboration have to be considered. This paper presents 1) the initial conceptual framework of HRC that addresses these above issues. It also describes 2) the design of a comparative analysis and benchmarking tasks of operators when interacting closely with robots, in three different demonstrators of varying levels of collaboration. The final outcome from this work should, in the long run, function as a roadmap for successful implementation of HRC in industry.

  • 3.
    Mao, Junjie
    et al.
    School of Software, Shanghai Jiao Tong University, Shanghai, China.
    Cai, Hongming
    School of Software, Shanghai Jiao Tong University, Shanghai, China.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Huang, Chengxi
    School of Software, Shanghai Jiao Tong University, Shanghai, China.
    Chen, Fengming
    Department of Information, Shanghai Waigaoqiao Shipbuilding Co, Ltd Shanghai, China.
    Xu, Boyi
    School of Economics & Management, Shanghai Jiao Tong University Shanghai, China.
    A Web of Things Based Device-adaptive Service Composition Framework2016Inngår i: 2016 IEEE 13th International Conference on e-Business Engineering (ICEBE), IEEE, 2016, s. 40-47Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In WoT environment, smart things provide RESTful services to expose their resources and operations. There are a large number of smart things that offer the same functionalities but have different service interfaces. Because of the high coupling between device service instances and process specifications like BPEL, the cost of reusing a BPEL specification between different device environments could be extremely high. We propose a device-adaptive service composition framework for WoT environment, in order to help users to apply the business process and service composition technologies more conveniently. In the framework, we design an activity description model, which is a semantic description for business activities, to overcome the shortcoming of directly binding the process and the service. Then, a matching mechanism between the model and the WADL of device services is proposed to select candidate services for the composition. Furthermore, we represent the matching result in a logical composition model, with which the source code of a general service can be automatically generated. The general service is a unified encapsulation for device services that match the functionalities of business activity. So user can interact with the general service instead of the origin services on the device, which decouples the process specification and the actual device services. A case study is offered to illustrate how to apply our framework in an intelligent charging pile sharing platform.

  • 4.
    Wang, Lihui
    et al.
    Department of Production Engineering, KTH Royal Institute of Technology, Sweden.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system. Department of Production Engineering, KTH Royal Institute of Technology, Sweden.
    Liu, Dawei
    AVIC Chengdu Aircraft Industrial (Group) Ltd. Co., China.
    Dynamic feature based adaptive process planning for energy-efficient NC machining2017Inngår i: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 66, nr 1, s. 441-444Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents a dynamic feature based adaptive process planning approach that can optimise machining cost, machining time and energy consumption simultaneously. The material removal volume of a dynamic feature is refined into non-overlapping volumes removed respectively by a single machining operation in which unified cutting mode is performed. Benefitting from this refinement, energy consumption is estimated analytically based on instantaneous cutting force as a function of real cutting parameters. Moreover, the cutting parameters assigned to each machining operation are optimised effectively in the unified cutting mode. This novel approach enhances the energy efficiency of NC machining through process planning.

  • 5.
    Wang, Wei
    et al.
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Bandaru, Sunith
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Sánchez de Ocãna Torroba, Adrian
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Improved Human-Robot Collaboration Through Simulation-Based Optimization2019Inngår i: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, 10–12 September 2019, Queen’s University, Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, s. 153-158, artikkel-id 10.3233/ATDE190027Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In order to pursue the dream combination of human flexibility and robot automation, human robot collaboration (HRC) is increasingly being investigated through academic research and industrial scenarios. HRC involves several challenges ranging from safety and comfort of the human to process efficiency and cost of robot operation. Achieving the right balance between these aspects is critical to implementing a safe, profitable and sustainable HRC environment. In this paper,we propose the use of simulation-based optimization (SBO) for assembly task allocation and scheduling for a HRC working cell in which an industrial robot assists a human worker. The list of product assembly operations are classified according to the capability of human worker and robot, and the sequencing constraints on them are the initial inputs of the method. The operators’ ergonomic load scores and cycletime of the assembly process are achieved by simulation. The optimized solutions are sorted to find the trade-offs between ergonomics and cycle time. We demonstratethe feasibility of the proposed approach through an industrial case study.

  • 6.
    Zhang, Xiaoyang
    et al.
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Lu, Xin
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Wang, Sheng
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    Wang, Wei
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap. Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Li, Weidong
    Faculty of Engineering, Environment and Computing, Coventry University, Coventry, United Kingdom.
    A multi-sensor based online tool condition monitoring system for milling process2018Inngår i: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, s. 1136-1141Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Tool condition monitoring has been considered as one of the key enabling technologies for manufacturing optimization. Due to the high cost and limited system openness, the relevant developed systems have not been widely adopted by industries, especially Small and Medium-sized Enterprises. In this research, a cost-effective, wireless communication enabled, multi-sensor based tool condition monitoring system has been developed. Various sensor data, such as vibration, cutting force and power data, as well as actual machining parameters, have been collected to support efficient tool condition monitoring and life estimation. The effectiveness of the developed system has been validated via machining cases. The system can be extended to wide manufacturing applications.

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