A service-oriented energy assessment system based on BPMN and machine learning

[1]  Andrei Chis,et al.  BPMN Extension for Multi-Protocol DataOrchestration , 2022, Domain-Specific Conceptual Modeling.

[2]  H. Gong,et al.  Research on compression deformation behavior of aging AA6082 aluminum alloy based on strain compensation constitutive equation and PSO-BP network model , 2021 .

[3]  Paul Grefen,et al.  Using business process models for the specification of manufacturing operations , 2020, Comput. Ind..

[4]  Kuldip Singh Sangwan,et al.  A systematic literature review on machine tool energy consumption , 2020 .

[5]  Shun Jia,et al.  An investigation into the method of energy monitoring and reduction for machining systems , 2020 .

[6]  Yan Wang,et al.  A generic energy prediction model of machine tools using deep learning algorithms , 2020 .

[7]  Mohiuddin Ahmed,et al.  The k-means Algorithm: A Comprehensive Survey and Performance Evaluation , 2020, Electronics.

[8]  Atsushi Kanai,et al.  Service-Oriented Software Design Model for Communication Robot , 2020, 2020 IEEE International Conference on Service Oriented Systems Engineering (SOSE).

[9]  Abdennaceur Kachouri,et al.  Improved node localization using K-means clustering for Wireless Sensor Networks , 2020, Comput. Sci. Rev..

[10]  P. Kynclova,et al.  Composite index as a measure on achieving Sustainable Development Goal 9 (SDG-9) industry-related targets: The SDG-9 index , 2020 .

[11]  J. Ling-Chin,et al.  A review of the current automotive manufacturing practice from an energy perspective , 2020 .

[12]  Fei Tao,et al.  An OPC UA based framework for predicting energy consumption of machine tools , 2020 .

[13]  Michael Affenzeller,et al.  Machine learning based concept drift detection for predictive maintenance , 2019, Comput. Ind. Eng..

[14]  Yixuan Zhang,et al.  Comparison of BP, PSO-BP and statistical models for predicting daily global solar radiation in arid Northwest China , 2019, Comput. Electron. Agric..

[15]  Jie Chen,et al.  Energy modelling and energy saving strategy analysis of a machine tool during non-cutting status , 2019, Int. J. Prod. Res..

[16]  Marcello Pellicciari,et al.  Optimization of the energy consumption of industrial robots for automatic code generation , 2019, Robotics and Computer-Integrated Manufacturing.

[17]  Rajaa Saidi,et al.  Proposal of BPMN extensions for modelling manufacturing processes , 2019, 2019 5th International Conference on Optimization and Applications (ICOA).

[18]  J. Ling-Chinb,et al.  A review of the current automotive manufacturing practice from an energy perspective , 2019 .

[19]  Rundong Chen,et al.  Real-Time Carbon Emissions Monitoring Tool for Prefabricated Construction: An IoT-Based System Framework , 2018 .

[20]  Chen Peng,et al.  Minimising the energy consumption of tool change and tool path of machining by sequencing the features , 2018 .

[21]  Yan He,et al.  Modeling Method for Flexible Energy Behaviors in CNC Machining Systems , 2018 .

[22]  Xiangfei Ji,et al.  Multivariate Rational Response Surface Approximation of Nodal Displacements of Truss Structures , 2018 .

[23]  Yan Wei,et al.  A new multi-source and dynamic energy modeling method for machine tools , 2018 .

[24]  Li Li,et al.  A framework for energy monitoring of machining workshops based on IoT , 2018 .

[25]  Ivo Paixao de Medeiros,et al.  Forecasting fault events for predictive maintenance using data-driven techniques and ARMA modeling , 2018, Comput. Ind. Eng..

[26]  Fei Liu,et al.  A novel approach for acquiring the real-time energy efficiency of machine tools , 2017 .

[27]  Shun Jia,et al.  An investigation into reducing the spindle acceleration energy consumption of machine tools , 2017 .

[28]  Konrad Wegener,et al.  The Total Energy Efficiency Index for machine tools , 2016 .

[29]  W. Alec Cram,et al.  Information systems control alignment: Complementary and conflicting systems development controls , 2016, Inf. Manag..

[30]  Yuchun Xu,et al.  Towards lean transformation: the analysis of lean implementation frameworks , 2015 .

[31]  Shun Jia,et al.  Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing , 2014, J. Intell. Manuf..

[32]  King Lun Choy,et al.  Application of intelligent data management in resource allocation for effective operation of manufacturing systems , 2014 .

[33]  Xun Xu,et al.  A holistic approach to achieving energy efficiency for interoperable machining systems , 2014 .

[34]  Wei Wang,et al.  A feature-based method for NC machining time estimation , 2013 .

[35]  Paul Xirouchakis,et al.  Evaluating the use phase energy requirements of a machine tool system , 2011 .

[36]  Günther Seliger,et al.  Methodology for planning and operating energy-efficient production systems , 2011 .

[37]  Sami Kara,et al.  Unit process energy consumption models for material removal processes , 2011 .

[38]  Liu Fei,et al.  Service-oriented information integration system for workshop manufacturing process , 2010 .

[39]  Alexander Verl,et al.  A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing , 2009 .

[40]  A. Verl,et al.  ENERGY CONSUMPTION FORECASTING AND OPTIMISATION FOR TOOL MACHINES , 2009 .

[41]  Soumitra Paul,et al.  Modelling of specific energy requirement during high-efficiency deep grinding , 2008 .

[42]  John W. Sutherland,et al.  A comparison of manufacturing and remanufacturing energy intensities with application to diesel engine production , 2008 .

[43]  T. Gutowski,et al.  A Thermodynamic Characterization of Manufacturing Processes , 2007, Proceedings of the 2007 IEEE International Symposium on Electronics and the Environment.

[44]  Wim Dewulf,et al.  Pro-active Life Cycle Engineering Support Tools , 2003 .