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Data interoperability for reconfigurable manufacturing process monitoring systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The ability for manufacturing organisation to be responsive to changing market conditions is imperative for sustainable market competitiveness, and enabling self preservation. Responsive behaviour requires the incorporation of not only robust sustainable manufacturing process chains, but the functional capacity to facilitate reconfiguration and adaption. Manufacturing process chains require process monitoring and condition based monitoring systems to achieve high accuracy manufacturing systems, sustainable production capability, and resource efficiency. The focus of this research is aimed at developing a novel data interoperability architecture to enable the creation of reconfigurable process monitoring systems. To achieve reconfigurable process monitoring capability an information communication paradigm known as agent based design is reviewed, and an emerging agent based standard known as MTConnect is also reviewed. Through this research a novel data interoperability system is developed and defined to enable dynamic data acquisition for reconfigurable process monitoring. A case study is carried out to demonstrate the validity of the architecture to achieve multi data stream unification. This case study demonstrates the ability to actively condition monitor a HURCO VM2 three axis CNC machine dynamically, through the measurement of machine energy requirements and vibration, which are examples of process variables associated with condition based machine monitoring.
Rocznik
Strony
64--79
Opis fizyczny
Bibliogr. 22 poz., rys.
Twórcy
autor
  • Mechanical and Manufacturing Engineering Department, Trinity College Dublin, Dublin 2, Ireland
  • Mechanical and Manufacturing Engineering Department, Trinity College Dublin, Dublin 2, Ireland
  • Mechanical and Manufacturing Engineering Department, Trinity College Dublin, Dublin 2, Ireland
Bibliografia
  • [1] TETI T., JEMIELNIAK K.., O’DONNELL G., DORNFELD D., 2010, Advanced monitoring of machining operations, CIRP Annals - Manufacturing Technology, 59/2, 717-739
  • [2] KOREN Y., HEISEL U., JOVANE F., MORIWAKI T., PRITSCHOW G., ULSOY G., van BRUSSEL H., 1999, Reconfigurable Manufacturing Systems, CIRP Annals - Manufacturing Technology, 48/2, 527-540.
  • [3] MONOSTORI L., Cs CSAJI B., KADAR B., PFEIFFER B., ILIE-ZUDOR E., KEMENY Zs., SZATHMARI M., 2010, Towards adaptive and digital manufacturing, Annual Reviews in Control, 34/1, 118-128.
  • [4] TIKKALA V.M.., LIISA S., JOUNELA J., 2012, Monitoring of caliper sensor fouling in a board machine using self-organising maps, Expert Systems with Applications, 39/12, 11228-11233.
  • [5] ABELE E., SIELAFF T., SCHIFFLER A., 2012, Method for chatter detection with standard PLC systems, Production Engineering, 6/6, 611-619.
  • [6] VIJAYARAGHAVAN A., DORNFELD D., 2010, Automated energy monitoring of machine tools, CIRP Annals - Manufacturing Technology, 59/1, 21-24.
  • [7] ECKSTEIN M., MANKOVA I., 2012, Monitoring of drilling process for highly stressed aeroengine components, CIRP Conference on High Performance Cutting, 5/1, 604 - 609.
  • [8] GRAUER M., KARADGI S., METZ D., 2010, Proactive control of manufacturing processes using historical data, Knowledge-based and intelligent information and engineering systems, 14/2, 399-408.
  • [9] BRECHER C., RUDOLF T., 2009, Adaptive logging module for monitoring applications using control internal digital drive signals, Production Engineering, 3/3, 305-312.
  • [10] GUNTER P., ALTINTAS Y., JOVANE F., KOREN Y., MITSUISHI M., TAKATA S., van BRUSSEL H., WECK M., YAMAZAKI K., 2001, Open controller architecture – past, present and future, CIRP Annals - Manufacturing Technology, 50/2, 463-470.
  • [11] MONOSTORI L., VANCZA J., KUMARA S.R.T., 2006, Agent-based systems for manufacturing, CIRP Annals - Manufacturing Technology, 55/2, 697-720.
  • [12] WOOLDRIDGEY M.J., CIANCARINI P., Agent-oriented software engineering: The state of the art, 2001, Springer-Verlag Berlin Heidelberg, 1/1, 1-28.
  • [13] LEITAO P., 2009, Agent-based distributed manufacturing control: A state-of-the-art survey, Engineering Applications of Artificial Intelligence, 22/7, 979-991.
  • [14] LEIT P., VRBA P., Recent developments and future trends of industrial agents, 2001, International conference on Industrial applications of holonic and multi-agent systems for manufacturing, 5/1, 15-28.
  • [15] BARBATI M., BRUNO G., GENOVESE A., 2012, Applications of agent-based models for optimization problems: A literature review, Expert Systems with Applications, 39/5, 6020-6028.
  • [16] DELSING J., ELIASSON J., KYUSAKOV R., COLOMBO A.W., JAMMES F., NESSAETHER J., KARNOUSKOS S., DIEDRICH C., 2011, A migration approach towards a SOA-based next generation process control and monitoring, Annual Conference on IEEE Industrial Electronics Society, 37/1, 1-6.
  • [17] MTConnect®, 2011, Getting started with MTConnect - Connectivity Guide.
  • [18] MTConnect®, 2012, MTConnect® Standard Part 2 - Overview and Protocol.
  • [19] MTConnect®, , 2011, Project report sustanable aerospace manufacturing initiative.
  • [20] Reddy, M., 2011, API Design for C++2011, 30 Corporate Drive, Suite 400, Burlington MA 01803, USA, Elsevier.
  • [21] National-Instruments, 2011, Connecting LabVIEW to 3rd Party Software Packages.
  • [22] National-Instruments, 2012, Using the LabVIEW shared variable.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-296c375a-e91d-4c98-96b5-f7b949a904a1
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