A Framework for Cloud Manufacturing Enabled Optimisation for Machining

Cloud Manufacturing is considered to be one of the paradigms that could revolutionize the way manufacturing has been realized in the industrial sector. Cloud Manufacturing services could be applied in most sectors of manufacturing since services can get integrated in the existing workflows. However, one of the most challenging while also most promising aspect is the reinterpretation of workflows and the creation of new workflows which could lead to more cost effective operations in the manufacturing industry. In this paper a framework for the optimization of cutting conditions in machining as part of a Cloud Manufacturing environment is presented. The aim of the framework is to provide users with an easier to use, cost efficient and well-informed solution that promotes sustainability in workshops. The main challenges, drivers and limitations in creating such an environment are discussed.

[1]  Robert X. Gao,et al.  AN INTEGRATED CYBER-PHYSICAL SYSTEM FOR CLOUD MANUFACTURING , 2014 .

[2]  Weidong Li,et al.  Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing , 2013 .

[3]  Nikolaos Tapoglou,et al.  Optimal Machining Parameter Selection Based on Real-Time Machine Monitoring Using IEC 61499 Function Blocks for Use in a Cloud Manufacturing Environment: A Case Study for Face Milling , 2014 .

[4]  Xun Xu,et al.  Cloud Manufacturing in Support of Sustainability , 2014 .

[5]  Dazhong Wu,et al.  Cloud manufacturing: Strategic vision and state-of-the-art☆ , 2013 .

[6]  Andrew Y. C. Nee,et al.  Advanced Design and Manufacturing Based on STEP , 2009 .

[7]  P. Mell,et al.  The NIST Definition of Cloud Computing , 2011 .

[8]  Lihui Wang,et al.  Machine availability monitoring and machining process planning towards Cloud manufacturing , 2013 .

[9]  Lihui Wang,et al.  A review of function blocks for process planning and control of manufacturing equipment , 2012 .

[10]  Nikolaos Tapoglou,et al.  Cloud based platform for optimal machining parameter selection based on function blocks and real time monitoring , 2015 .

[11]  Xun Xu,et al.  An interoperable solution for Cloud manufacturing , 2013 .

[12]  Dazhong Wu,et al.  Cloud Manufacturing: Drivers, Current Status, and Future Trends , 2013 .

[13]  Lei Ren,et al.  Cloud manufacturing: key characteristics and applications , 2017, Int. J. Comput. Integr. Manuf..

[14]  Xun Xu,et al.  A novel energy demand modelling approach for CNC machining based on function blocks , 2014 .

[15]  Jonathan Follett,et al.  Designing for Emerging Technologies: UX for Genomics, Robotics, and the Internet of Things , 2014 .

[16]  Alois Zoitl,et al.  Real-Time Execution for IEC 61499 , 2008 .

[17]  Lei Ren,et al.  Intelligent User Interface in Cloud Manufacturing , 2014 .

[18]  Dimitris Mourtzis,et al.  Machine Availability Monitoring for Adaptive Holistic Scheduling: A Conceptual Framework for Mass Customization , 2014 .

[19]  Li Weidong,et al.  A cloud based feature recognition system to support collaborative and adaptive process planning , 2014 .

[20]  Xun Xu,et al.  From cloud computing to cloud manufacturing , 2012 .