》  Research Fields

· Sustainable manufacturing and scheduling

· Intelligent optimization algorithms

· Data driven modeling and deep learning

· Prognostics and health management

》  Courses

》  Projects

1. PI, National Natural Science Foundation of China (Youth Program), “Collaborative optimization of energy-saving scheduling and maintenance for heat treatment with incompatible jobs under time-varying effects,” 01/01/2023-12/31/2025 (Grant No. 62203336)

2. PI, Shanghai Soft Science Key Program (Youth Program), “Evaluation system of sustainable scheduling indicators for manufacturing enterprises in the Yangtze River Delta under the high-quality development pattern,” 05/01/2021-04/30/2022 (Grant No. 21692196100)

3. PI, Shanghai Pujiang Talent Program, “Big-data-driven sintering burdening decision support platform for iron and steel enterprises toward energy conservation and emission reduction,” 07/01/2018-06/30/2020 (Grant No. 18PJ1432000)

4. Co-PI, National Natural Science Foundation of China (Key Program), “Interactive learning and collaborative decision-making with total factor fusion for industrial production system,” 01/01/2022-12/31/2026 (Grant No. 62133011)

5. Core member, National Natural Science Foundation of China, “Collaborative optimization strategies and methods for sustainable manufacturing scheduling based on hybrid intelligence,” 01/01/2020-12/31/2023 (Grant No. 61973237)

6. Core member, National Natural Science Foundation of China, “Collaborative optimization of energy distribution and production scheduling based on a multi-view energy model,” 01/01/2013-12/31/2016 (Grant No. 61273046)

》  Publications

l Selected Papers

1. P. Zhang, F. Qiao, J. Wang, and J. W. Sutherland, "Novel multi-criteria sustainable evaluation for production scheduling based on fuzzy analytic network process and cumulative prospect theory-enhanced VIKOR," IEEE Robotics and Automation Letters, 2022, 7(4): 9969-9976.

2. L. Zhang, F. Qiao, J. Wang, and X. Zhai, “Equipment health assessment based on improved incremental support vector data description,” IEEE Transactions on Systems, Man and Cybernetics: Systems, 2021, 51(5): 3205-3216.

3. J. Wang, H. Du, J. Xing, F. Qiao, and Y. Ma, “Novel energy- and maintenance-aware collaborative scheduling for a hybrid flow shop based on dual memetic algorithms,” IEEE Robotics and Automation Letters, 2020, 5(4): 5613-5620.

4. J. Wang, F. Qiao, F. Zhao, and J. W. Sutherland, “Batch scheduling for minimal energy consumption and tardiness under uncertainties: a heat treatment application,” CIRP Annals-Manufacturing Technology, 2016, 65(1):17-20.

5. J. Wang, F. Qiao, F. Zhao, and J. W. Sutherland, “A data driven model for energy consumption in the sintering process,” Journal of Manufacturing Science and Engineering-Transactions of the ASME, 2016, 138(10), p. 101001/1-12.

l Monograph

1. J. Wang, and F. Qiao, “Collaborative optimization technology towards energy-efficient manufacturing scheduling,” Shanghai: Tongji University Press, 2022, ISBN: 978-7-5765-0132-2 (in Chinese)

l Selected Patents

1. Control Method, Medium, and Equipment for Flexible Flow Shop Scheduling Considering Fatigue, Patent No.: ZL202110516138.7 (in Chinese)

2. A Hybrid Flow Shop Production Equipment Scheduling and Control Method, Patent No.: ZL202010575648.7 (in Chinese)

3. Optimization Control Method and Control Device for Sintering burdening Based on ISAA Algorithm, Patent No.: ZL201911014041.5 (in Chinese)

4. An Energy Consumption Prediction Method for Sintering Based on Integrated Models, Patent No.: ZL2015102254098 (in Chinese)