面向车间能耗的维护调度系统研究
发布时间：2019-07-06 14:33
【摘要】：能源是关系到未来社会经济增长和繁荣的根本要素。中国经济飞速发展的同时，人口的过快增长、自然资源的减少和能源的短缺等现象日益突显，使得中国不能再通过不顾后果的能源消耗的方法换取经济增长。制造业作为能耗大户，本身应承担更多的环境影响责任。本课题研究的设备维护调度在可持续制造体系下扮演着重要的角色，即设备的维修更换需要考虑设备的能耗因素。本文考虑能耗因素对设备进行再利用、更换以及废弃处理的影响，提供一种面向车间层能耗的维护调度方法，从而在保证设备利用率的情况下，，更大限度的减少设备的能源消耗，对今后的可持续制造体系下，设备维护的研究方向具有指导意义。 本文针对生产制造系统的车间层设备建立了面向能耗的维护调度模型。使用可靠性概率函数建立设备性能衰退的数学模型。定义了设备的各种维护动作（包括小修、中修、大修和更换）。同时，使用Malik役龄比例恢复模型进行设备在维护活动之后的性能恢复的数学建模。之后引入人工神经网络进行设备性能和能耗的映射函数建立。 在以上模型的基础上，设计了基于可靠性和考虑设备能耗的两种维护策略。考虑设备及其子系统的特征，引入设备的多性能衰退、能耗和维护性几项属性，并设计了相应的维护指标评价方法。设计了基于Fisher算法的维护策略分类算法，使用经验数据对算法进行训练，在对待维护的设备子系统进行各项属性评价，使用分类算法对其进行维护策略分类。 本文引入了人工免疫算法，并设计了针对维护调度寻优的克隆人工免疫算法，并详细叙述了算法的编码方法、交叉算子、变异算子、亲和度、浓度和激励度函数，最后使用该算法对车间层维护调度问题进行优化求解。设计了滑动轴承生产车间的维护案例，使用了基于可靠性和考虑能耗的维护策略对该案例进行维护调度求解，对仿真结果进行了比较和分析。 最后，从管理系统的基本功能需求角度，详细介绍了设备智能维护与管理系统的设计方法。使用Visual Basic6.0进行软件的界面开发，通过ActiveX接口技术实现了VB调用Matlab软件中函数的功能，并且详细介绍了该系统软件的设备维护决策模块，能耗预测模块以及车间层调度模块。最后完成了该设备智能维护与管理系统的开发。
文内图片：
图片说明：加工过程功率曲线图
[Abstract]:Energy is the fundamental element related to the future social and economic growth and prosperity. With the rapid development of China's economy, the rapid growth of population, the reduction of natural resources and the shortage of energy have become increasingly prominent, so that China can no longer exchange for economic growth through reckless energy consumption. As a big consumer of energy consumption, manufacturing industry itself should bear more responsibility for environmental impact. The equipment maintenance scheduling studied in this paper plays an important role in the sustainable manufacturing system, that is, the maintenance and replacement of equipment needs to consider the energy consumption of equipment. Considering the influence of energy consumption factors on the reuse, replacement and disposal of equipment, this paper provides a maintenance scheduling method for workshop energy consumption, so as to reduce the energy consumption of equipment to a greater extent under the condition of ensuring the utilization rate of equipment, which is of guiding significance for the research direction of equipment maintenance in the future sustainable manufacturing system. In this paper, a maintenance and scheduling model for energy consumption is established for the workshop equipment of the production and manufacturing system. The mathematical model of equipment performance decline is established by using reliability probability function. Various maintenance actions of equipment (including minor repair, medium repair, overhaul and replacement) are defined. At the same time, the Malik service age proportional recovery model is used to model the performance recovery of the equipment after maintenance activities. Then the artificial neural network is introduced to establish the mapping function of equipment performance and energy consumption. On the basis of the above model, two maintenance strategies based on reliability and considering equipment energy consumption are designed. Considering the characteristics of the equipment and its subsystems, the multi-performance decline, energy consumption and maintenance properties of the equipment are introduced, and the corresponding maintenance index evaluation method is designed. A maintenance strategy classification algorithm based on Fisher algorithm is designed, which uses empirical data to train the algorithm, evaluates the attributes of the maintenance equipment subsystem, and uses the classification algorithm to classify the maintenance strategy. In this paper, the artificial immune algorithm is introduced, and a cloned artificial immune algorithm for maintenance scheduling optimization is designed, and the coding method, crossover operator, mutation operator, affinity, concentration and incentive function of the algorithm are described in detail. Finally, the algorithm is used to optimize the workshop maintenance scheduling problem. The maintenance case of sliding bearing production workshop is designed, and the maintenance scheduling strategy based on reliability and energy consumption is used to solve the case, and the simulation results are compared and analyzed. Finally, from the point of view of the basic functional requirements of the management system, the design method of the equipment intelligent maintenance and management system is introduced in detail. The interface of the software is developed by Visual Basic6.0, and the function of VB calling functions in Matlab software is realized by ActiveX interface technology. The equipment maintenance decision module, energy consumption prediction module and workshop scheduling module of the system software are introduced in detail. Finally, the intelligent maintenance and management system of the equipment is developed.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH18;TP18
本文编号：2511088
文内图片：
图片说明：加工过程功率曲线图
[Abstract]:Energy is the fundamental element related to the future social and economic growth and prosperity. With the rapid development of China's economy, the rapid growth of population, the reduction of natural resources and the shortage of energy have become increasingly prominent, so that China can no longer exchange for economic growth through reckless energy consumption. As a big consumer of energy consumption, manufacturing industry itself should bear more responsibility for environmental impact. The equipment maintenance scheduling studied in this paper plays an important role in the sustainable manufacturing system, that is, the maintenance and replacement of equipment needs to consider the energy consumption of equipment. Considering the influence of energy consumption factors on the reuse, replacement and disposal of equipment, this paper provides a maintenance scheduling method for workshop energy consumption, so as to reduce the energy consumption of equipment to a greater extent under the condition of ensuring the utilization rate of equipment, which is of guiding significance for the research direction of equipment maintenance in the future sustainable manufacturing system. In this paper, a maintenance and scheduling model for energy consumption is established for the workshop equipment of the production and manufacturing system. The mathematical model of equipment performance decline is established by using reliability probability function. Various maintenance actions of equipment (including minor repair, medium repair, overhaul and replacement) are defined. At the same time, the Malik service age proportional recovery model is used to model the performance recovery of the equipment after maintenance activities. Then the artificial neural network is introduced to establish the mapping function of equipment performance and energy consumption. On the basis of the above model, two maintenance strategies based on reliability and considering equipment energy consumption are designed. Considering the characteristics of the equipment and its subsystems, the multi-performance decline, energy consumption and maintenance properties of the equipment are introduced, and the corresponding maintenance index evaluation method is designed. A maintenance strategy classification algorithm based on Fisher algorithm is designed, which uses empirical data to train the algorithm, evaluates the attributes of the maintenance equipment subsystem, and uses the classification algorithm to classify the maintenance strategy. In this paper, the artificial immune algorithm is introduced, and a cloned artificial immune algorithm for maintenance scheduling optimization is designed, and the coding method, crossover operator, mutation operator, affinity, concentration and incentive function of the algorithm are described in detail. Finally, the algorithm is used to optimize the workshop maintenance scheduling problem. The maintenance case of sliding bearing production workshop is designed, and the maintenance scheduling strategy based on reliability and energy consumption is used to solve the case, and the simulation results are compared and analyzed. Finally, from the point of view of the basic functional requirements of the management system, the design method of the equipment intelligent maintenance and management system is introduced in detail. The interface of the software is developed by Visual Basic6.0, and the function of VB calling functions in Matlab software is realized by ActiveX interface technology. The equipment maintenance decision module, energy consumption prediction module and workshop scheduling module of the system software are introduced in detail. Finally, the intelligent maintenance and management system of the equipment is developed.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2012
【分类号】：TH18;TP18
【参考文献】
相关期刊论文 前7条
1 郑建明,李言,黄玉美;刀具磨损切削力功率谱特征多分辨分析[J];机床与液压;2002年04期
2 刘克胜,曹先彬,郑浩然,王煦法;基于免疫算法的TSP问题求解[J];计算机工程;2000年01期
3 李兆前，田志仁，艾兴;刀具磨损的随机模型及其在刀具可靠性试验中的应用[J];机械工程学报;1994年04期
4 李茂军,罗安,童调生;人工免疫算法及其应用研究[J];控制理论与应用;2004年02期
5 张姣;李永红;;应用MATLAB进行寿命数据分析[J];机械工程与自动化;2010年03期
6 王琳;机械设备故障诊断与监测的常用方法及其发展趋势[J];武汉工业大学学报;2000年03期
7 蒋兴恒;朱素蓉;;基于Levenberg-Marquardt算法改进BP神经网络的卷烟销量预测模型研究[J];中国烟草学报;2011年05期
相关博士学位论文 前1条
1 周晓军;生产系统智能维护决策及优化技术研究[D];上海交通大学;2006年
本文编号：2511088
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