面向可持续制造的车间能耗建模及优化技术研究

Sustainable manufacturing is an inevitable trend of manufacturing sector in the context of sustainable development strategy. It aims at maximum effectiveness with minimum energy consumption in manufacturing process, which is different in essence with traditional manufacturing industries whose solitary goal is simply in the pursuit of benefit maximization on time, quality, and cost. This project commenced with research in key technologies such as energy consumption modeling on workshop level, its optimization and implementation, proposed that different processing technics should be taken into account as an influence factor of equipment energy consumption when modeling, built up a workshop energy consumption model including equipment processing, adjustment, transfer, wait, and energy consumption of public facilities, and gave the energy consumption characteristics of worn equipment.The project also put forward a multi-dimensional objective function model which took factors, as energy consumption, production costs, production efficiency, etcetera, into consideration and advanced the constraints which took elements such as resource, limited cache, task flexibility and the influence on environment exerted in the course of workshop production.Based on exergy analysis, the model of energy conversion efficiency and objective function of energy consumption and energy(exergy) efficiency are proposed, which reveal the relationship between production efficiency, energy consumption and energy(exergy) efficiency. And therefore, the relationship between efficiency of equipment, production costs and energy consumption is brought out and an artificial intelligence based optimized scheduling methodology of workshop energy consumption is proposed..This research is an important support to the implementation of equipment energy consumption optimization and forecasting, the improvement of energy efficiency, the efficient use of resources and the reduction of enterprises' carbon emissions, and is of great theoretical significance and application value.

可持续制造是制造业在可持续发展战略下的必然趋势，在制造过程中强调最小能耗的最大效益，与传统制造业所追求的时间、质量、成本效益最大化的目标有本质区别。本项目对车间层能耗建模、优化及其实施等关键技术展开研究，提出在能耗建模过程中必须考虑加工参数、以及设备性能对能耗影响的观点；建立了包括设备加工、调整、传输、等待、以及公共设施能耗的车间综合能耗模型，基于统计学和人工智能方法给出了设备性能与能耗的关联关系和作用规律；基于（火用）损理论，建立了能源转化效率模型，构建了综合能耗、能效的目标函数模型，揭示设备生产效率与能耗、能效之间的关系，提出基于人工智能的车间能耗优化调度方法。建立了基于能耗预测、监控、仿真、管控一体化的体系结构。研究工作是实现设备能耗优化及预测、提高能源效率、有效利用资源以及降低企业碳排放量的重要支撑技术，具有重大的理论研究意义与应用价值。

本项目针对车间设备性能衰退及加工能耗建模，机床关键能耗部件的性能监测与评价技术，考虑能耗的多目标车间动态优化决策等技术展开研究。建立了车间机床加工工艺与能耗关系模型；揭示了设备性能衰退和能耗变化之间的定量关系；构建了设备维修性能恢复模型，以及再次衰退过程中的能耗变化规律；提出了综合考虑能耗和能效的多目标的车间动态优化决策方法；以Haas-VF2数控加工中心以及多任务柔性生产车间为例，实现了设备加工的能耗模型和优化决策系统的成果验证，为实现低能耗、可持续的目标提供重要理论基础及技术支持。本项目执行过程中发表研究15篇，其中ESI 3%高被引用研究2篇，SCI检索文章8篇，EI检索11篇（SCI他引128次，Google总他引268次），出版全英文专著1部（Machinery Prognostics and Prognosis Oriented Maintenance Management. John Wiley & Son, Inc., 2015）。课题组成员参加国际学术会议7人次，邀请国际智能维护领域专家来课题组访问12人次；课题组5名博士生赴北美顶尖高校交换学习。在本项目的成果基础上，申请人作为哈工大团队负责人获批了中美自然科学基金（NSFC-NSF）联合资助项目“面向环境可持续性的数字化制造装备设计、制造与运行的基础理论研究”（5141101303）。