华晨宝马博士生研究课题 |
副课题或具体内容 |
技术重点 |
研究所属领域
(包含但不限于) |
Sustainability, Energy, CO2 Management: Deep Learning Methods of Production Energy Optimization 深度学习方法在生产系统能源优化方面的研究
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1. Build CO2 footprint model for finished vehicle logistics and supply chain logistics, applying state-of-art optimization methods on reducing logistics CO2 footprint. 2. Build energy model for key processes in Press shop, Body shop, Paint shop, develop deep learning methods and applying methods to optimize PUE of key processes in production. |
1. Simulation pipeline modeling of manufactering process. 2. Deep learning methods of optmization control parameters |
081200 计算机科学与技术 Computer Science and Technology 0811J1 机器人科学与工程 Robot Science and Engineering |
Advanced Industrial Data Mining and Data Value Stream Analytics Technology 先进的工业数据挖掘和数据价值流分析技术 |
1. Research on efficient frameworks for big industry data processing 2. Research on the new data analytic approach to lower the entry level 3. Research on data value stream mapping methodology among complex production chain. |
New technology & algorithm for data value stream analytics |
080800 电气工程 Electrical Engineering 081200 计算机科学与技术 Computer Science and Technology
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Base on Multiple Trading Partner Behavior Analysis To Research Automobile Industry Receivable and Payable Credit Risk & Application 基于大数据和行为分析学，调研汽车行业贸易伙伴信用风险与智能应用 （课题内容具体待修订）
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Non-Series Material (Spare Parts/Tools/Consumables) Business Model 非量产物料业务模式与数字化应用
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1. Analyze BBA as-is process, planning and system logic, reconstruct the business model and process from the perspective of the supply chain based on historical preventive maintenance data. 2. Use operational data to transparentize the real daily logistics operations, capture and set key business characteristics, and establish statistical models to describe operations and plans. 3. Keep tracking all negative incident in preventive maintenance and logistics area, focusing on backtracking scenarios such as excessive lead time and out of stock, in-depth analysis of business logic loopholes, and establish a spare parts supply chain database to provide valuable data for machine learning to handle the dynamic demand for spare parts and build an AI supply chain platform. 4. Exploit dependencies between maintenance strategy and supply strategy. 5. See what can be learned from solutions for this kind of problem in other industries.
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Build up the model for machine learning regarding dynamic demand for spare parts.
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081200 计算机科学与技术 Computer Science and Technology 081203 计算机应用技术Computer Applied Technology
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Sustainability- Recycling Material in Plastic Parts and CO2 Emission Reduction 可持续性-回收塑料在汽车零部件中的应用及CO2减排 |
1. Introducing the recycling plastic material into BMW components is one major measure in this working package. 2.Deeply research the recycled material applications in the exterior and interior plastic parts, such as PC, ABS, PP, PA66 and etc. 3.Deeply research the recycled material in chemical and physical properties, chemical reaction mechanism and also plastic material property change. 4.Deeply research the recycled material segment(such as PIR and PCR), manufacturing process, and also the latest development concept of recycled material. |
Seeking the technical solutions to achieve recycled material ratio target for current and new project, and then achieve CO2 emission reduction per vehicle. |
070303 有机化学 Organic Chemistry 0805Z1 高分子材料 Polymer Material |
Correlation Study of Energy Efficiency and Cost Impact for Manufacture 能源效率和成本控制的关系 |
1. Energy structure for the supply chain. 2. Cost impact to energy structure. 3. CO2 reduction strategy based on energy reduction, new energy implementation, digitalization to optimize the efficiency, circularity. 4. Potentials for energy transfer to green energy. |
Buid up the model for the energy efficiency and cost effiency. |
0807Z1 能源与环境工程 Energy and Environmental Engineering 083002 环境工程 Environmental Engineering |
