Continuously improving availability, performance and quality of manufacturing units, reducing the overall equipment effectiveness gap between actual and ideal manufacturing performance, and enhancing manufacturing processes to be more energy and resource efficient in order to drive all elements of waste out of manufacturing processes is crucial to daily production management and key to advancing manufacturing productivity and competitiveness.
To help manufacturing plants address these challenges, achieve maximum manufacturing asset performance and operational efficiency, and increase factory overall equipment effectiveness, the Manufacturing Execution & Control (MEC) research group focuses on developing advanced decision support technologies that will support agile decision-making at the shop floor and enhance the real-world awareness capability of manufacturing systems.
Technology focus is on:
- Analysing and modeling resources and energy usage patterns and working on energy and resource aware production control solutions that lead to reduction of energy usage and efficient use of resources in shop floor,
- Developing big-data intelligence and visualization systems for visualizing production status, throughput and other key performance indicators, developing real-time analytical applications to enable users to explore, analyse, and understand data in real-time and use the data for continuous improvement of quality and efficiency,
- Developing advanced monitoring solutions that will continually monitor, diagnose, and optimize process parameters and performance, and automatically capture and classify process knowledge, discern patterns and trends, and recommend appropriate responses to assist workers in responding to complexity,
- Developing diagnostic and prognostic technologies for analysing and modeling faults and failures of factory equipments, and characterising health degradation and remaining useful life for cost effective predictive maintenance
Download this brochure for more information.
9 technology disclosures have been filed:
- System and Methods for Automated Personnel's Time and Location Tracking in Confined Space (TD-E-12-020)
- System and Methods for Automated Process Recipe Tuning and Management (TD-E-12-027)
- Density-Grid Hybrid Clustering Method for Multivariate Anomaly Detection to Achieve Zero Defective Product with Minimum False Reject Rate (TD-E-11-037)
- Method for Determining of Optimal Maintenance Scheduling for Semiconductor Equipment (TD-E-11-038)
- 'Near field RF sensing for proximity and object condition with improved measurement techniques' (TD-E-10-019)
- 'RFID Asset Management System (RAMS) Design' (TD-E-10-031)
- Method and Apparatus for Multiple Simultaneous Thermal Bonding of Polymer Substrates (TD-V-09-032 filed jointly with MMP)
- System and Methods for Active Tracking of Passive RFID Tags in Shop Floor Level Object Tracking (TD-E-09-013, Provisional filed)
- Near Field RF Sensing for Proximity and Object Condition with Improved Measurement Techniques (TD-E-09-019, Provisional filed)
Honours and Awards:
- 2012 IASTED EAS Best Paper Award: C. K. Pang, X. Wang, and J. H. Zhou, "A Mixed Time-/Condition-Based Precognitive Maintenance Framework Using Support Vectors".
- The Ministry of Transport Minister's Innovation Award 2011 for the RFID project on Personnel Tracking in MRT Downtown Line Construction.
- 8th Asian Control Conference 2011 Best Application Paper Award: C. K. Pang, J. -H. Zhou, Z. -W. Zhong, and F. L. Lewis, "Industrial Fault Detection and Isolation Using Dominant Feature Identification," in Proceedings of the ASCC 2011, TuB3.1, pp. 1018-1023, Kaohsiung, Taiwan, May 15-18, 2011.
- The Institute of Engineers Singapore (IES) Prestigious Engineering Achievement Award 2011 for the research project entitled "Development of Intelligent Techniques for Modeling, Controlling and Optimising Complex Manufacturing Systems".
- Winner of the 1st Prize of SIMTech Awards 2007 (Outreach Category) for the project "X'periment-2007 Wonders of RFID", 29 February 2008
- URECA student MsWang WenwenattachedMEC(Aug. 2007- July 2008, Supervisor: Li Xiang) for the project of "Development of Parameter Free Clustering Technology" has won NTU 2008 "Engineering Award".
- Best paper award at 5th Annual IEEE Conference on Automation Science and Engineering (CASE) for the paper on "Closed-Loop Determinism for Non-Deterministic Environments: Verification for IEC 61499 Logic Controller" by Lindsay V. Allen, University of Michigan, Dr. Goh Kiah Mok, SIMTech, and Professor Dawn Tilbury, University of Michigan.
- L. V. Allen, K. M. Goh and D. M. Tilbury, "Input Order Robustness: Application to IEC 61499 Controllers", 2009 The fifth annual IEEE Conference on Automation Science and Engineering, 22th - 25th Aug, 2009, Bangalore.
- SIMTech Award 2005 - 2007 - Industry Category.
- IES Prestigious Engineering Achievement Award 2003.
Commercialisation and Licensing:
The following technologies have been licensed:
- RFID-based Personnel Tracking System and RFID Garment Tracking System
- Integrated Shop Floor Tracking and Production Planning System
- RFID Middleware was successfully licensed to O'Connor's Singapore Pte Ltd and a total licensing fee of $53,700 was received for year 2009.