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  • 151. Mohammed, Abdullah
    et al.
    Schmidt, Bernard
    Wang, Lihui
    Remote Monitoring and Controlling for Robotic Path Following Operations2012Conference paper (Refereed)
    Abstract [en]

    Controlling a robot's movement requires a prior knowledge about the needed path and configurations to accomplish the movement. The lack of this knowledge causes limitations in the robot's adaptability in dynamic environments. The objectives of this paper are: (1) to improve the ability of the robot to follow any arbitrary path defined by an operator, and (2) to provide the ability for an authorized distant operator to access the system for monitoring and controlling both the robot and the stages of the process. The system developed in this research consists of a calibrated network camera, an industrial robot and an application server. The process starts by having a sketch drown by an operator representing the paths that the robot needs to follow, then the operator can remotely take a snapshot of the paths and retrieve the contours that represent the paths; after that the system sends them to the robot controller to perform the task of path following. The results have shown that the system can perform the required task within a relatively short time and with a reasonable level of quality. This research proves that it is possible to build an adaptive robotic system that can follow efficiently any arbitrary path without the need for defining it in advance.

  • 152.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liang, Gao
    Minimising Energy Consumption for Robot Arm Movement2014Conference paper (Refereed)
    Abstract [en]

    Robots are widely used in industry due to their efficiency and high performance. Many of them are operating in the manufacturing stage of the production line where the highest percentage of energy is consumed. Therefore, their energy consumption became a major focus for many robots manufacturers and academic research groups. Nevertheless, the optimisation of that consumption is still a challenging task which requires a deep understanding of the robot’s kinematic and dynamic behaviours. This paper proposes an approach to develop an optimisation module using Matlab® to minimise the energy consumptions of the robot’s movement. With the help of Denavit-Hartenberg notation, the approach starts first by solving the inverse kinematics of the robot to find a set of feasible joint configurations required to perform the task, solving the inverse kinematics is usually a challenging step which requires in-depth analyses of the robot. The module then solves the inverse dynamics of the robot to analyse the forces and torques applied on each joint and link in the robot. Furthermore, a calculation for the energy consumption is performed for each configuration. The final step of the process represents the optimisation of the calculated configurations by choosing the one with the lowest power consumption and sends the results to the robot controller. Three case studies are used to evaluate the performance of the module. The experimental results demonstrate the developed module as a successful tool for energy efficient robot path planning. Further analyses for the results have been done by comparing them with the ones from commercial simulation software. The case studies show that the optimisation of the location for the target path could reduce the energy consumption effectively.

  • 153.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. KTH Royal Inst Technol, Dept Prod Engn, Stockholm, Sweden..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Brainwaves driven human-robot collaborative assembly2018In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 67, no 1, p. 13-16Article in journal (Refereed)
    Abstract [en]

    This paper introduces an approach to controlling an industrial robot using human brainwaves as a means of communication. The developed approach starts by establishing a set of training sessions where an operator is enquired to think about a set of defined commands for the robot and record the brain activities accordingly. The results of the training sessions are then used on the shop floor to translate the brain activities to a set of robot control commands. An industrial case study is carried out to assist the operator in coordinating a collaborative assembly task of a car engine manifold.

  • 154.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Vision-Based Robotic Path Following2013In: International Journal of Mechanisms and Robotic Systems, ISSN 2047-7252, Vol. 1, no 1, p. 95-111Article in journal (Refereed)
    Abstract [en]

    Most robotic manufacturing applications nowadays require tedious and expensive pre–programming of the chosen robot, each time when a new task is introduced. In order to eliminate the tedious robot programming for better productivity, this research proposes an adaptive approach that allows a robot to follow any arbitrary robot path defined by an operator. A so–developed system was designed to monitor and control the path following operation locally or remotely through an established web–based architecture, without the need of extra programming. The objective of the research is achieved by integrating an image processing module with a robotic system. The real benefits of such a system are the ability to control and monitor the stepwise processing stages, as well as to automate the whole operation to a certain level of control defined in advance. In particular, this paper introduces a prototype that can be extended to various industrial applications, such as arc welding, laser cutting and water jet cutting, which require controlling the 2D or 3D path of a robot.

  • 155.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, R. X.
    Integrated Image Processing and Path Planning for Robotic Sketching2012In: Proceedings of the 8th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 2012Conference paper (Refereed)
  • 156. Moriwaki, T.
    et al.
    Sugimura, N.
    A Modelling System for Finite Element Analysis of Machine Products1993In: Transactions of the North American Manufacturing Research Institution of SME, ISSN 1047-3025, Vol. 21, p. 383-390Article in journal (Refereed)
  • 157. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    A Study on Thermal Analysis for Machine Tools with Relative Motions1993Conference paper (Refereed)
  • 158. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Development of an Integrated CAD/CAE System for Machine Tool Design1993In: Integrated Manufacturing Systems of JSPE, p. 81-94Article in journal (Refereed)
  • 159. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Development of Modelling System for CAD/CAE of Machine Tools (Part-1: Automatic Mesh Adjustment of FEM Model for Moving Parts)1993In: International journal of the Japan Society for Precision Engineering, ISSN 0916-782X, Vol. 59, no 2, p. 233-238Article in journal (Refereed)
  • 160. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Development of Modelling System for CAD/CAE of Machine Tools (Part-2: Application of Thermal Analysis for Moving Parts)1994In: International journal of the Japan Society for Precision Engineering, ISSN 0916-782X, Vol. 60, no 7, p. 959-963Article in journal (Refereed)
  • 161. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Modelling System for CAD/CAE of Machine Tools (1st Report, Concept and Approach to the System)1992Conference paper (Refereed)
  • 162. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Modelling System for CAD/CAE of Machine Tools (2nd Report, Automatic Generation of FEM Models)1992Conference paper (Refereed)
  • 163. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Modelling System for CAD/CAE of Machine Tools (3rd Report, Integrated Management of Finite Element Nodal Information)1992Conference paper (Refereed)
  • 164. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Study on Modelling Methods for Kinematic Analysis of Machine Tools1991In: Integrated Manufacturing Systems of JSPE, p. 69-78Article in journal (Refereed)
  • 165. Moriwaki, T.
    et al.
    Sugimura, N.
    Wang, Lihui
    Araki, Y.
    Modelling System for CAD/CAE of Machine Tools (4th Report, Application to Thermal Analysis with Relative Motions)1993In: Proceedings of 1993 Spring Annual Meeting of Japan Society for Precision Engineering, 1993, p. 39-40Conference paper (Refereed)
  • 166. Moriwaki, T.
    et al.
    Wang, Lihui
    Study on Thermal Behaviour of Machine Tool Elements across Movable Joints Under Operating States1995Conference paper (Refereed)
  • 167. Moriwaki, T.
    et al.
    Wang, Lihui
    Kuroda, N.
    Study on Thermal Deformation of Machine Tools1994Conference paper (Refereed)
  • 168. Moriwaki, T.
    et al.
    Wang, Lihui
    Kuroda, N.
    Thermal Analysis of Machine Elements with Relative Motions1994Conference paper (Refereed)
  • 169. Mourtzis, D.
    et al.
    Vlachou, E.
    Xanthopoulos, N.
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud-based adaptive process planning considering availability and capabilities of machine tools2016In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 39, p. 1-8Article in journal (Refereed)
    Abstract [en]

    Disturbances on manufacturing shop-floors and the increasing number of product variants necessitate adaptive and flexible process planning methods. This paper proposes a service-oriented Cloud-based software framework comprising two services. The first service generates non-linear process plans using event-driven function blocks and a genetic algorithm. The second service, gathers data from shop-floor machine tools through sensors, input from operators, and machine schedules. An information fusion technique processes the monitoring data in order to feed the process planning service with the status, specifications, and availability time windows of machine tools. The methodology is validated in a case study of a machining SME.

  • 170. Newman, S. T.
    et al.
    Ali, L.
    Brail, A.
    Brecher, C.
    Klemm, P.
    Liu, R.
    Nassehi, A.
    Nguyen, V. K.
    Proctor, F.
    Rosso, R. S. U.
    Stroud, I.
    Suh, S. H.
    Vitr, M.
    Wang, Lihui
    Xu, X. W.
    The Evolution of CNC Technology from Automated Manufacture to Global Interoperable Manufacturing2007Conference paper (Refereed)
  • 171. Newman, S.T.
    et al.
    Nassehi, A.
    Xu, Xun
    Rosso Jr., R.S.U.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, NRC, London, Ontario, Canada.
    Yusof, Y.
    Ali, L.
    Liu, R.
    Zheng, L.
    Kumar, S.
    Vichare, P.
    Dhokia, V.
    Strategic Advantages of Interoperability for Global Manufacturing Using CNC Technology2008In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 24, no 6, p. 699-708Article in journal (Refereed)
    Abstract [en]

    In the domain of manufacturing, computer numerically controllers (CNC) technology is a major contributor to the production capacity of the enterprises. The advances in CNC technology coupled with enhancements ill computing systems have provided the basis to re-examine the way in which computer-aided systems (CAx) call be used to enable global manufacturing. Interoperability of the various components of the CAx chain is therefore a major prerequisite for manufacturing enterprises for becoming strategically agile and consequently globally competitive. Being interoperable, resources call be utilized interchangeably in a plug-and-produce manner. Over the last 8 years the eminence of a STEP standard for machining entitled STEP-NC (numerical control) has become a well-known vehicle for research to improve the level of information availability at the CNC machine too]. Ill this paper, the authors introduce the background to the evolution of CNC manufacturing over the last 50 years and the Current standards available for programming. A review of the literature in interoperable CNC Manufacturing is then provided relating to Milling, turn-mill and other NC processes. The major part of the paper provides a strategic view of]low interoperability call be implemented across the CAx chain with a range of standards used to regulate the flow of information. Finally, the paper Outlines the advantages and major issues for future developments in interoperability, identifying future key requirements and limiting factors.

  • 172. Newman, Stephen
    et al.
    Xu, X.W.
    Rosso Jr., R.S.U.
    Wang, Lihui
    Yusof, Y.
    Ali, L.
    Liu, R.
    Zheng, L.
    Kumar, S.
    Vichare, P.
    Dhokia, V.
    Interoperable CNC for Global Manufacturing2007Conference paper (Refereed)
  • 173. Orban, Peter
    et al.
    Bordatchev, E.V.
    Lang, S.
    Rehorn, A.G.
    Shen, W.
    Wang, Lihui
    National Research Council of Canada.
    Distributed Monitoring and Control of Machines and Machine Conditions2004In: Proceedings of the 2nd Conference on Emerging Machinery and Structural Condition Monitoring Technologies for Defence Applications, 2004Conference paper (Refereed)
  • 174. Peng, Tao
    et al.
    Xu, Xun
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A novel energy demand modelling approach for CNC machining based on function blocks2014In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 33, no 1, p. 196-208Article in journal (Refereed)
    Abstract [en]

    Energy efficiency remains one of the major issues in the machining domain. Today's machining systems are confronted with a number of new challenges, such as turbulent product demand and variations in production resources. Rapid and flexible energy modelling in a distributed and collaborative machining environment emerges as a new research area. Energy demand models in such an environment need to be practical, accurate, effective, scalable and reusable. Energy analysis and optimisation cannot be carried out once for all at the beginning. Instead, it is an on-going process. In this paper, the function block technique, i.e. IEC 61499, is used for the development of energy demand models as it brings advantages such as modularity, encapsulation, extensibility and reusability. A brief review on energy modelling and research on function blocks are given in the first part. A novel energy demand modelling approach based on function blocks is then proposed and elaborated. Three types of function blocks have been developed, i.e. machine tool dependent function blocks, state transition function blocks, and service interface function blocks. The first type, as the fundamental building blocks, is divided into two sub-types, machine component function block and machining state function block. Two case studies, based on a small 3-axis milling machine and an industrial production line respectively, are presented to demonstrate the possible applications using the function block-based model. Comprehensive discussions are given thereafter, including a pilot application of a distributed process planning system and a unique energy evaluation scheme. A confidence level associated energy rating system is proposed as the first step to turn energy consumption figures into useful indicators. The energy demand model based on function blocks developed here enhances the energy modelling and their practical implementations.

  • 175. Prasoon, R.
    et al.
    Das, D.
    Tiwari, M.K.
    Wang, Lihui
    University of Skovde.
    An Algorithm Portfolio Approach to Reconfigurable Setup Planning2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 8, p. 756-768Article in journal (Refereed)
    Abstract [en]

    This article discusses an algorithm portfolio approach to find optimal set-up plans in a dynamic shop floor environment where flexibility and promptness of the decision process is critical along with best possible utilisation of the available resources. An evolutionary algorithm based reconfigurable set-up planning approach is presented where the final set-up plan is determined in two steps: primitive set-up planning through feature grouping and reconfigurable set-up merging based on real time information from the scheduling system. The tendency of single algorithm approach to converge to sub-optimal solutions was countered by using portfolios of genetic algorithm and its three variants: Genetic Algorithm with Chromosome Differentiation, Sexual Genetic Algorithm and a modified version of Age Genetic Algorithm. Best performing portfolios selected after exhaustive experimentation showed dramatic computational improvements in achieving the optimal solution validating the appropriateness and effectiveness of algorithm portfolio approach.

  • 176. Putnik, G.D.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ubiquitous and Cloud Enterprise for Manufacturing2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 4-5, p. 344-346Article in journal (Refereed)
  • 177. Ren, Lei
    et al.
    Zhang, Lin
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Tao, Fei
    Chai, Xudong
    Cloud manufacturing: key characteristics and applications2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 6, p. 501-515Article in journal (Refereed)
    Abstract [en]

    Cloud manufacturing is emerging as a new manufacturing paradigm as well as an integrated technology, which is promising in transforming today's manufacturing industry towards service-oriented, highly collaborative and innovative manufacturing in the future. In order to better understand cloud manufacturing, this paper provides a critical review of relevant concepts and ideas in cloud computing as well as advanced manufacturing technologies that contribute to the evolution of cloud manufacturing. The key characteristics of cloud manufacturing are also presented in order to clarify the cloud manufacturing concept. Furthermore, a four-process structure is proposed to describe the typical scenario in cloud manufacturing, hoping to provide a theoretical reference for practical applications. Finally, an application case of a private cloud manufacturing system for a conglomerate is presented.

  • 178. Sandberg, Ulf
    et al.
    Schmidt, Bernard
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Management of Factory and Maintenance Information for Multiple Production and Product Life-Cycle Phases2014Conference paper (Refereed)
    Abstract [en]

    Maintenance is crucial for future manufacturing systems. An extended local knowledge is essential to increase precision and efficiency, but also for improvements of the maintained object itself. Approaches exist that closes the loop from end-user to vendor, but intra loops are not so well developed.

    This article discusses ways to interconnect and manage data and knowledge flow between work processes in user and vendor life-cycles. It aims to inspire improvements in existing approaches, closer connections between producer and customer, between users, and improved quality of maintenance work via factory-, company-, or group-wide data and knowledge about similar types of equipment.

  • 179. Schmidt, B.
    et al.
    Gandhi, K.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. School of Engineering Science, University of Skövde, PO Box 408, Skövde, 541 28, Sweden.
    Diagnosis of machine tools: Assessment based on double ball-bar measurements from a population of similar machines2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, Vol. 72, p. 1327-1332Conference paper (Refereed)
    Abstract [en]

    The presented work is toward population-based predictive maintenance of manufacturing equipment with consideration of the automatic selection of signals and processing methods. This paper describes an analysis performed on double ball-bar measurement from a population of similar machine tools. The analysis is performed after aggregation of information from Computerised Maintenance Management System, Supervisory Control and Data Acquisition, NC-code and Condition Monitoring from a time span of 4 years. Economic evaluation is performed with use of Monte Carlo simulation based on data from real manufacturing setup.

  • 180. Schmidt, B.
    et al.
    Gandhi, K.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Galar, D.
    Context preparation for predictive analytics-a case from manufacturing industry2017In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 341-354Article in journal (Refereed)
    Abstract [en]

    Purpose-The purpose of this paper is to exemplify and discuss the context aspect for predictive analytics where in parallel condition monitoring (CM) measurements data and information related to the context are gathered and analysed. Design/methodology/approach-This paper is based on an industrial case study, conducted in a manufacturing company. The linear axis of a machine tool has been selected as an object of interest. Available data from different sources have been gathered and a new CM function has been implemented. Details about performed steps of data acquisition and selection are provided. Among the obtained data, health indicators and context-related information have been identified. Findings-Multiple sources of relevant contextual information have been identified. Performed analysis discovered the deviations in operational conditions when the same machining operation is repeatedly performed. Originality/value-This paper shows the outcomes from a case study in real word industrial setup. A new visualisation method of gathered data is proposed to support decision-making process.

  • 181. Schmidt, B.
    et al.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Minimising Energy Consumption for Robot Arm Movement2013Conference paper (Refereed)
  • 182. Schmidt, B.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Virtual Systems Research Centre, University of Skövde, Sweden .
    Contact-less and programming-less human-robot collaboration2013In: Forty Sixth CIRP Conference on Manufacturing Systems 2013, 2013, p. 545-550Conference paper (Refereed)
    Abstract [en]

    In today's manufacturing environment, safe human-robot collaboration is of paramount importance, to improve efficiency and flexibility. Targeting the safety issue, this paper presents an approach for human-robot collaboration in a shared workplace in close proximity, where real data driven 3D model of a robot and multiple depth images of the workplace are used for monitoring and decision-making to perform a task. The strategy for robot control depends on the current task and the information about the operator's presence and position. A case study of assembly is carried out in a robotic assembly cell with human collaboration. The results show that this approach can be applied in real-world applications such as human-robot collaborative assembly with human operators safeguarded at all time.

  • 183. Schmidt, B.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde, Sweden.
    Galar, D.
    Semantic Framework for Predictive Maintenance in a Cloud Environment2017In: 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Elsevier, 2017, Vol. 62, p. 583-588Conference paper (Refereed)
    Abstract [en]

    Proper maintenance of manufacturing equipment is crucial to ensure productivity and product quality. To improve maintenance decision support, and enable prediction-as-a-service there is a need to provide the context required to differentiate between process and machine degradation. Correlating machine conditions with process and inspection data involves data integration of different types such as condition monitoring, inspection and process data. Moreover, data from a variety of sources can appear in different formats and with different sampling rates. This paper highlights those challenges and presents a semantic framework for data collection, synthesis and knowledge sharing in a Cloud environment for predictive maintenance.

  • 184. Schmidt, Bernard
    et al.
    Galar, D.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Context Preparation for Predictive Analytics – a Case from Manufacturing Industry2016In: Proceedings of the 4th International Workshop and Congress on eMaintenance, Luleå University of Technology, 2016Conference paper (Refereed)
  • 185. Schmidt, Bernard
    et al.
    Galar, Diego
    Wang, Lihui
    University of Skövde, School of Engineering Science University of Skövde, The Virtual Systems Research Centre. KTH.
    Asset Management Evolution: from Taxonomies toward Ontologies2015Conference paper (Refereed)
    Abstract [en]

    This paper addresses the evolution that can be observed in Asset Management in modelling approach. Most traditional Condition Monitoring systems use hierarchical representations of monitored the integration of data from disparate source toward context awareness and Big Data utilization there is a need to include and model more complicated dependencies than hierarchical. Ontology based modelling is gaining recently on popularity in the domain of Condition Monitoring and Asset Management.

  • 186. Schmidt, Bernard
    et al.
    Galar, Diego
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Big Data in Maintenance Decision Support Systems: Aggregation of Disparate Data Types2016In: Euromaintenance 2016 Conference Proceedings, 2016, p. 503-512Conference paper (Refereed)
    Abstract [en]

    There is need to obtain reliable information on current and future asset health status to support maintenance decision making process. Within maintenance two main sources of data can be distinguished: Computerized Maintenance Management System (CMMS) for asset registry and maintenance work records; and Condition Monitoring Systems (CM) for direct asset components health state monitoring. There are also other sources of information like SCADA (Supervisory Control and Data Acquisition) for process and control monitoring that can provide additional contextual information leading to better decision making. However data produced acquired and processed and in those system are of disparate types, nature and granularity. This variety includes: event data about failures or performed maintenance work mostly descriptions in unstructured natural language; process variables obtained from different types of sensors and different physical variables from transducers, acquired with different sampling frequencies. Indeed, condition monitoring data are so disparate in nature that maintainers deal with scalars (temperature) through waveforms (vibration) to 2D thermography images and 3D data from machine geometry measuring. Integration and aggregation of those data is not a trivial task and requires modelling of knowledge about those data types, their mutual dependencies and dependencies with monitored processes. There are some attempts of standardisation that try to enable integration of CBM data from different sources. The conversion of those amount of data in meaningful data sets is required for better machine health assessment and tracking within the specific operational context for the asset. This will also enhance the maintenance decision support system with information on how different operational condition can affect the reliability of the asset for concrete contextual circumstances.

  • 187. Schmidt, Bernard
    et al.
    Galar, Diego
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Context Awareness in Predictive Maintenance2016In: Current Trends in Reliability, Availability, Maintainability and Safety, Springer, 2016, p. 197-216Chapter in book (Refereed)
    Abstract [en]

    Maintenance of assembly and manufacturing equipment is crucial to ensure productivity, product quality, on-time delivery, and a safe working environment. Predictive Maintenance approach utilizes the condition monitoring (CM) data to predict the future machine conditions and makes decisions upon this prediction. Recent development in CM leads to context aware approach where in parallel with CM measurements also data and information related to the context are gathered. Context could be operational condition, history of machine usage and performed maintenance actions. In general more obtained information gives better accuracy of prediction. It is important to track operational context in dynamically changing environment. Today in manufacturing we can observe shift from mass production to mass customisation. This leads to changes from long series of identical products to short series of different variants. Therefore implies changing operational conditions for manufacturing equipment. Moreover, where asset consist of multiple identical or similar equipment the context aware method can be used to combine in reliable way information. This should allow to increase accuracy of prediction for population as a whole as well as for each equipment instances. Same of those data have been already recorded and stored in industrial IT systems. However, it is distributed over different IT systems that are used by different functional units (e.g. maintenance department, production department, quality department, tooling department etc.). This paper is a conceptual paper based on initial research work and investigation in two manufacturing companies from automotive industry.

  • 188. Schmidt, Bernard
    et al.
    Sandberg, Ulf
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Next Generation Condition Based Predictive Maintenance2014Conference paper (Refereed)
    Abstract [en]

    Maintenance of assembly and manufacturing equipment is crucial to ensure productivity, product quality, on-time delivery, and a safe working environment. Predictive Maintenance is an approach that utilises the condition monitoring data to predict the future machine conditions and make decisions upon this prediction. The main aim of the presented research is to achieve an improvement in condition based Predictive Maintenance through the Cloud-based approach with usage of the largest information content possible. The objective of this paper is to outline the first steps of a framework to handle and process maintenance, production and factory related data from the first life-cycle phase to the operation and maintenance phase.

  • 189. Schmidt, Bernard
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Active Collision Avoidance for Human-Robot Collaborative Manufacturing2012In: Proceedings of the 5th International Swedish Production Symposium, SPS 12, 6-8 November 2012, Linköping, Sweden, The Swedish Production Academy , 2012, p. 81-86Conference paper (Refereed)
  • 190. Schmidt, Bernard
    et al.
    Wang, Lihui
    Automatic Robot Calibration via a Global-Local Camera System2012Conference paper (Refereed)
    Abstract [en]

    In a human-robot collaborative manufacturing application where working object can be placed in an arbitrary position, there is a need to calibrate the actual position of the work object. This paper presents an approach for automatic calibration in flexible robotic systems. It consists of two subsystems: a global positioning system based on fixed cameras mounted around robotic workspace, and a local positioning system based on the camera mounted on the robot arm. The aim of the global positioning is to detect work object in working area and roughly estimate the position, whereas the local positioning is to define the object frame according to the 3D position and orientation of the work object with higher accuracy. For object detection and localization, coded visual markers have been utilized. For each object, several markers have been used to increase the robustness and accuracy of localization and calibration procedure. This approach can be used in robotic welding or assembly applications.

  • 191. Schmidt, Bernard
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Automatic work objects calibration via a global-local camera system2014In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 30, no 6, p. 678-683Article in journal (Refereed)
    Abstract [en]

    In a human robot collaborative manufacturing application where a work object can be placed in an arbitrary position, there is a need to calibrate the actual position of the work object. This paper presents an approach for automatic work-object calibration in flexible robotic systems. The approach consists of two modules: a global positioning module based on fixed cameras mounted around robotic workspace, and a local positioning module based on the camera mounted on the robot arm. The aim of the global positioning is to detect the work object in the working area and roughly estimate its position, whereas the local positioning is to define an object frame according to the 3D position and orientation of the work object with higher accuracy. For object detection and localization, coded visual markers are utilized. For each object, several markers are used to increase the robustness and accuracy of the localization and calibration procedure. This approach can be used in robotic welding or assembly applications.

  • 192. Schmidt, Bernard
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Cloud-based Predictive Maintenance2015In: Proceedings of the 25th International Conference on Flexible Automation and Intelligent Manufacturing, 2015, Vol. 1, p. 224-231Conference paper (Refereed)
    Abstract [en]

    Maintenance of assembly and manufacturing equipment is crucial to ensure productivity, product quality, on-time delivery, and a safe working environment. Predictive Maintenance is an approach that utilises the condition monitoring data to predict the future machine conditions and makes decisions upon this prediction. The main aim of the presented research is to achieve an improvement in Predictive Condition-based Maintenance Decision Making through the Cloud-based approach with usage of wide information content. For the improvement it is crucial to identify and track not only condition related data but also context data. Context data allows better utilisation of condition monitoring data as well as analysis based on a machine population. The objective of this paper is to outline the first steps of a framework and methodology to handle and process maintenance, production and factory related data from the first lifecycle phase to the operation and maintenance phase.

  • 193. Schmidt, Bernard
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde, Sweden.
    Depth camera based collision avoidance via active robot control2014In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 33, no 4, p. 711-718Article in journal (Refereed)
    Abstract [en]

    A new type of depth cameras can improve the effectiveness,of safety monitoring in human-robot collaborative environment. Especially on today's manufacturing shop floors, safe human-robot collaboration is of paramount importance for enhanced work efficiency, flexibility, and overall productivity. Within this context, this paper presents a depth camera based approach for cost-effective real-time safety monitoring of a human-robot collaborative assembly cell. The approach is further demonstrated in adaptive robot control. Stationary and known objects are first removed from the scene for efficient detection of obstacles in a monitored area. The collision detection is processed between a virtual model driven by real sensors, and 3D point cloud data of obstacles to allow different safety scenarios. The results show that this approach can be applied to real-time work cell monitoring.

  • 194. Schmidt, Bernard
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Predictive Maintenance: Literature Review and Future Trends2015Conference paper (Refereed)
    Abstract [en]

    In manufacturing industry machines and systems become more advanced and complicated. Proper maintenance is crucial to ensure productivity, product quality, on-time delivery, and safe working environment. Recently, the importance of the predictive maintenance has been growing rapidly. Well applied predictive maintenance can be in many cases more cost effective than traditional corrective and preventive approaches to maintenance. Targeting this vibrant field, this paper reviews the literature of Predictive Maintenance (PdM). Published literature is systematically categorised and then methodically reviewed and analysed. Methodology for data acquisition, feature extraction, failure detection and prediction are presented. The connection between Maintenance field and Information Fusion has been highlighted. Statistical analysis based on Elsevier’s Scopus abstract and citation database has been performed. Various emerging trends in the field of Predictive Maintenance are identified to help specifying gaps in the literature and direct research efforts.

  • 195. Shen, W.
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council of Canada .
    Hao, Q.
    Agent-Based Distributed Manufacturing Process Planning and Scheduling: A State-of-the-Art Survey2006In: IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews, ISSN 1094-6977, E-ISSN 1558-2442, Vol. 36, no 4, p. 563-577Article in journal (Refereed)
    Abstract [en]

    Manufacturing process planning is the process of selecting and sequencing manufacturing processes such that they achieve one or more goals and satisfy a set of domain constraints. Manufacturing scheduling is the process of selecting a process plan and assigning manufacturing resources for specific time periods to the set of manufacturing processes in the plan. It is, in fact, an optimization process by which limited manufacturing resources are allocated over time among parallel and sequential activities. Manufacturing process planning and scheduling are usually considered to be two separate and distinct phases. Traditional optimization approaches to these problems do not consider the constraints of both domains simultaneously and result in suboptimal solutions. Without considering real-time machine workloads and shop floor dynamics, process plans may become suboptimal or even invalid at the time of execution. Therefore, there is a need for the integration of manufacturing process-planning and scheduling systems for generating more realistic and effective plans. After describing the complexity of the manufacturing process-planning and scheduling problems, this paper reviews the research literature on manufacturing process planning, scheduling as well as their integration, particularly on agent-based approaches to these difficult problems. Major issues in these research areas are discussed, and research opportunities and challenges are identified

  • 196. Shen, Weiming
    et al.
    Brooks, Christopher
    Li, Yinsheng
    Lang, Sherman Y. T.
    Wang, Lihui
    National Research Council Canada .
    XML-Based Message Services for Internet Based Intelligent Shop Floors2001In: Proceedings Volume 4566, Internet-based Enterprise Integration and Management, SPIE - International Society for Optical Engineering, 2001, Vol. 4566, p. 135-144Conference paper (Refereed)
    Abstract [en]

    Previously, we reported some preliminary results of our long-term research work on iShopFloor (Intelligent Shop Floor). This paper reports some of our recent work on the implementation of XML-based message services for Internet-based intelligent shop floors. The objective is to investigate XML for message exchange among Internet-based shop floor devices that are represented by intelligent agents. The paper discusses the advantages of using XML for message services and presents our initial implementation. From this implementation, we have seen some advantages, including: (1) simplification and standardization of message services in Internet-based intelligent shop floors; (2) facilitation of the integration of an agent-based scheduling system with other intelligent shop floor systems, including Web-based shop floor monitoring and control systems, etc.

  • 197. Shen, Weiming
    et al.
    Ghenniwa, H.
    Wang, Lihui
    National Research Council of Canada.
    Agent-Supported Web-based Cooperative Design2003In: Agent Supported Cooperative Work, Boston: Kluwer Academic Publishers, 2003, p. 231-253Chapter in book (Refereed)
  • 198. Shen, Weiming
    et al.
    Lang, Sherman Y. T.
    Korba, L.
    Wang, Lihui
    National Research Council, Canada.
    Wong, B.
    Reference Architecture for Internet Based Intelligent Shop Floors2000In: Proceedings of SPIE Conference on Network Intelligence: Internet-Based Manufacturing, SPIE - International Society for Optical Engineering, 2000, Vol. 4208, p. 63-72Conference paper (Refereed)
    Abstract [en]

    Global competitiveness is causing manufacturing companies to change the way they do business. New ways of viewing markets and competition have led the movement from legacy information systems to Internet-based environments. Success in manufacturing depends on being able to respond quickly, accurately and consistently to the changing needs of the marketplace. The need to control and optimize processes and to vary the necessary parameters to obtain the best product on time and on specification has fostered a change from centralized or hierarchical to distributed manufacturing control systems. This paper proposes a reference architecture for Internet-based intelligent shop floors. Internet, Web technologies, and intelligent agents are the key technologies adopted in this approach. The reference architecture provides the framework for components of a complex control system to work together as a whole rather than as a disjoint set. It encompasses both information architecture and integration methodologies. The primary aspects of the reference architecture under consideration include: (1) statement of scope and purpose; (2) domain analysis; (3) architectural specification; and (4) methodology for architectural development and system design.

  • 199. Shen, Weiming
    et al.
    Lang, Sherman Y. T.
    Wang, Lihui
    iShopfloor: An Internet-enabled agent-based intelligent shop floor2005In: IEEE transactions on systems, man and cybernetics. Part C, Applications and reviews, ISSN 1094-6977, E-ISSN 1558-2442, Vol. 35, no 3, p. 371-381Article in journal (Refereed)
  • 200. Shen, Weiming
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council Canada.
    Web-Based and Agent-Based Approaches for Collaborative Product Design: An Overview2003In: International journal of computer applications in technology, ISSN 0952-8091, E-ISSN 1741-5047, Vol. 16, no 2/3, p. 103-112Article, review/survey (Refereed)
    Abstract [en]

    A number of emerging technologies including CSCW, distributed objects, intelligent agents, internet and web based technologies have been proposed to implement collaborative product design systems, while web-based and agent-based approaches are dominant in this area. This paper reviews the state-of-the-art of applications of the Web and Agent technologies to collaborative product design, and discusses the opportunities as well as challenges in this exciting research area.

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