Developing performance measurement system for Internet of Things and smart factory environment

References

• Braz, Renata Gomes Frutuoso, Luiz Felipe Scavarda, and Roberto Antonio Martins. 2011. “Reviewing and Improving Performance Measurement Systems: An Action Research.” International Journal of Production Economics 133 (2): 751–760.10.1016/j.ijpe.2011.06.003
   Web of Science ®Google Scholar
• Dai, Qingyun, Runyang Zhong, George Q. Huang, Qu Ting, T. Zhang, and T. Y. Luo. 2011. “Radio Frequency Identification-enabled real-time Manufacturing Execution System: A Case Study in an Automotive Part Manufacturer.” Review of. International Journal of Computer Integrated Manufacturing 25 (1): 51–65.
   Web of Science ®Google Scholar
• Desbiens, Eric, and Amin Chaabane. 2014. “Visual Notation Approach for MES Integration.” Paper presented at the IIE Annual Conference, Proceedings, Montreal.
   Google Scholar
• Fang, Ji, George Q. Huang, and Zhi Li. 2013. “Event-driven Multi-agent Ubiquitous Manufacturing Execution Platform for Shop Floor Work-in-progress Management.” International Journal of Production Research 51 (4): 1168–1185.10.1080/00207543.2012.693644
   Web of Science ®Google Scholar
• Gupta, Pardeep, and Sachit Vardhan. 2016. “Optimizing OEE, Productivity and Production Cost for Improving Sales Volume in an Automobile Industry through TPM: A Case Study.” International Journal of Production Research 54 (10): 2976–2988.10.1080/00207543.2016.1145817
   Web of Science ®Google Scholar
• Hao, Yuqiuge, Rafael Karbowski, Ahm Shamsuzzoha, and Petri Helo. 2013. “Designing of Cloud-based Virtual Factory Information System.” In Advances in Sustainable and Competitive Manufacturing Systems, edited by Américo Azevedo, 415–426. Switzerland: Springer International.
   Google Scholar
• Kádár, Botond, Walter Terkaj, and Marco Sacco. 2013. “Semantic Virtual Factory Supporting Interoperable Modelling and Evaluation of Production Systems.” CIRP Annals - Manufacturing Technology 62 (1): 443–446.10.1016/j.cirp.2013.03.045
   Web of Science ®Google Scholar
• Kern, Daniel, Roger Moser, Evi Hartmann, and Marco Moder. 2012. “Supply Risk Management: Model Development and Empirical Analysis.” International Journal of Physical Distribution & Logistics Management 42 (1): 60–82.10.1108/09600031211202472
   Web of Science ®Google Scholar
• Mejjaouli, Sobhi, and RaduF Babiceanu. 2014. “Holonic Condition Monitoring and Fault-recovery System for Sustainable Manufacturing Enterprises.” In Service Orientation in Holonic and Multi-agent Manufacturing and Robotics, edited by Theodor Borangiu, Damien Trentesaux, and Andre Thomas, 31–46. Switzerland: Springer International.
   Google Scholar
• Meyer, Sonja, Andreas Ruppen, and Carsten Magerkurth. 2013. “Internet of Things-Aware Process Modeling: Integrating IoT Devices as Business Process Resources.” In Advanced Information Systems Engineering, edited by Camille Salinesi, Moira C Norrie, and Óscar Pastor, 84–98. Berlin: Springer.10.1007/978-3-642-38709-8
   Google Scholar
• Muchiri, P., and L. Pintelon. 2008. “Performance Measurement Using Overall Equipment Effectiveness (OEE): Literature Review and Practical Application Discussion.” International Journal of Production Research 46 (13): 3517–3535.10.1080/00207540601142645
   Web of Science ®Google Scholar
• Muchiri, Peter N., Liliane Pintelon, Harry Martin, and Anne-Marie De Meyer. 2009. “Empirical Analysis of Maintenance Performance Measurement in Belgian Industries.” Review of International Journal of Production Research 48 (20): 5905–5924.
   Web of Science ®Google Scholar
• Muthiah, K. M. N., and S. H. Huang. 2007. “Overall Throughput Effectiveness (OTE) Metric for Factory-level Performance Monitoring and Bottleneck Detection.” International Journal of Production Research 45 (20): 4753–4769.10.1080/00207540600786731
   Web of Science ®Google Scholar
• Ou-Yang, C., and Y. D. Lin. 2008. “BPMN-based Business Process Model Feasibility Analysis: A Petri Net Approach.” International Journal of Production Research 46 (14): 3763–3781.10.1080/00207540701199677
   Web of Science ®Google Scholar
• Prades, L., F. Romero, A. Estruch, A. García-Dominguez, and J. Serrano. 2013. “Defining a Methodology to Design and Implement Business Process Models in BPMN according to the Standard ANSI/ISA-95 in a Manufacturing Enterprise.” Procedia Engineering 63: 115–122.10.1016/j.proeng.2013.08.283
   Google Scholar
• Qu, Ting, Matthias Thürer, Junhao Wang, Zongzhong Wang, Huan Fu, Congdong Li, and George Q. Huang. 2016. “System Dynamics Analysis for an Internet-of-things-enabled Production Logistics System.” International Journal of Production Research. doi:10.1080/00207543.2016.1173738.10.1080/00207543.2016.1173738
   PubMed Web of Science ®Google Scholar
• Saenz de Ugarte, B., A. Artiba, and R. Pellerin. 2009. “Manufacturing Execution System – A Literature Review.” Production Planning & Control 20 (6): 525–539.10.1080/09537280902938613
   Web of Science ®Google Scholar
• Tsarouhas, Panagiotis H. 2013. “Evaluation of Overall Equipment Effectiveness in the Beverage Industry: A Case Study.” International Journal of Production Research 51 (2): 515–523.10.1080/00207543.2011.653014
   Web of Science ®Google Scholar
• Unver, Hakki Ozgur. 2013. “An ISA-95-Based Manufacturing Intelligence System in Support of Lean Initiatives.” The International Journal of Advanced Manufacturing Technology 65 (5–8): 853–866.10.1007/s00170-012-4223-z
   Web of Science ®Google Scholar
• Yoon, Joo-Sung, Seung-Jun Shin, and Suk-Hwan Suh. 2012. “A Conceptual Framework for the Ubiquitous Factory.” International Journal of Production Research 50 (8): 2174–2189.10.1080/00207543.2011.562563
   Web of Science ®Google Scholar
• Zhong, Ray Y., Q. Y. Dai, T. Qu, G. J. Hu, and George Q. Huang. 2013. “RFID-enabled Real-time Manufacturing Execution System for Mass-customization Production.” Robotics and Computer-Integrated Manufacturing 29 (2): 283–292.10.1016/j.rcim.2012.08.001
   Web of Science ®Google Scholar