基于智能算法的多设备混联系统动态维护决策研究
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摘要
维护对于工业生产设备、军事装备以及交通运输工具等系统的正常工作或安全运行具有重要作用。随着市场竞争的日趋激烈,企业面临着不断降低成本的巨大压力,设备的维护费用作为企业的最大单个可控费用,越来越受到企业的重视。因此,合理的维护决策对于企业降低维护成本,提高生产效益具有十分重要的意义。目前,事后维护和预防性维护在企业中得到了广泛的应用,并取得了明显的效果,但存在着维修不足或维修过剩的问题,会给企业带来严重的经济损失。此外,已存在的大量维护模型为单设备维护模型,对由多设备组成的生产系统并不适用。本论文针对上述问题,以多设备混联系统为研究对象,以故障诊断和寿命预测技术为支撑,进行动态维护决策及调度方法研究,主要内容如下:
建立多设备混联系统维护模型。模型综合考虑设备的性能衰退特性,设备间的经济相关性和结构相关性,以及维护资源的限制问题。设备性能衰退过程采用威布尔函数模拟,维护调度中采用小修、大修和更换三种维护方式,维护费用包括维护本身的费用和停机损失两部分。考虑到多次维护活动以及维护启动费用,建立维护费用率模型。
基于遗传算法,制定多设备维护调度策略。该策略以单次维护活动产生的维护费用最低为目标,在系统长期运行过程中,每产生一次维护活动,调用一次遗传算法对维护活动进行调度求解。针对模型中维护阈值的优化问题,提出一种用于求解连续空间优化问题的改进蚁群算法。该算法按照随机性的概率选择机制进行信息更新,经过局部搜索和全局搜索两个过程,最终找到目标解。经蚁群算法优化阈值后,将以更低的维护费用和更少的维护次数保证系统的平稳运行。
建立基于Flexsim的维护仿真模型,并实现MATLAB维护决策模型与Flexsim维护仿真模型之间维护数据的实时动态交互。通过Flexsim强大的统计功能,从设备利用率、系统生产量等方面分析维护策略对生产系统的影响。
最后,将本论文的维护策略和仿真技术应用于汽轮机叶片生产系统,应用结果显示本文建立的维护策略在降低生产系统维护费用,提高生产效率上的有效性与实用性。
Maintenance plays an important role in keeping availability and reliability levels of industrial equipment, weapons and transportation facilities, etc. In the face of increasingly fierce market competition, the enterprises are facing enormous pressure for cost reduction; maintenance cost has attracted attention of more and more enterprises as the largest single controllable cost. At present, corrective maintenance and preventive maintenance have been widely used in enterprises, which produce obvious effect. However, these maintenance strategies may lead to insufficient maintenance or over-maintenance which will bring serious economic loss to enterprises. Besides, most existing models are established for single-unit systems, which are not applicable to practical production systems consisting of multiple units. Therefore, reasonable maintenance decision has extremely vital significance in maintenance cost reduction and production efficiency improvement. In order to solve above problems, the thesis takes multi-unit series-parallel system as the research object, studies dynamic maintenance decision and scheduling method based on fault diagnosis and useful life prediction technology. The main contents are described as follows:
A dynamic maintenance decision model for multi-unit series-parallel system is established considering performance degradation of units, economic dependence and structural dependence between units, and constraints of maintenance resources.
The deterioration of units is modeled by Weibull distribution. Three maintenance actions, including minor repair, imperfect overhaul and replacement, are simultaneously considered to arrange the maintenance schedule of a system, maintenance cost include two parts: maintenance activity cost and downtime cost. Considering several maintenance activities in a time period and setup cost, an overall cost rate model is established.
The genetic algorithm (GA) based methodology is employed to obtain the near optimal multi-unit maintenance scheduling which results in a relatively minimal maintenance cost rate. In the running process of the system, whenever a maintenance activity is generated, the GA will be called for solving the schedule activities.
With respect to the optimization of thresholds in the model, an improved ant colony algorithm is proposed to solve the optimization problem in continuous space. This algorithm updates information according to random probability selection mechanism, through local search and global search process, finally finds the optimal solutions. After maintenance thresholds are optimized, we can ensure the system running smoothly at lower maintenance cost and less maintenance frequency.
A maintenance simulation model is established under Flexsim environment, and real-time dynamic interaction of data between MATLAB maintenance decision model and Flexsim maintenance simulation model is realized. Then the influence of maintenance strategy on production system is analysised from equipment utilization, volume of production etc using Flexsim’s powerful statistical function.
Finally, the maintenance policy and simulation technology are applied to turbine blade production system. The results show the effectiveness and practicality of the maintenance strategy in reducing maintenance cost and improving production efficiency.
建立多设备混联系统维护模型。模型综合考虑设备的性能衰退特性,设备间的经济相关性和结构相关性,以及维护资源的限制问题。设备性能衰退过程采用威布尔函数模拟,维护调度中采用小修、大修和更换三种维护方式,维护费用包括维护本身的费用和停机损失两部分。考虑到多次维护活动以及维护启动费用,建立维护费用率模型。
基于遗传算法,制定多设备维护调度策略。该策略以单次维护活动产生的维护费用最低为目标,在系统长期运行过程中,每产生一次维护活动,调用一次遗传算法对维护活动进行调度求解。针对模型中维护阈值的优化问题,提出一种用于求解连续空间优化问题的改进蚁群算法。该算法按照随机性的概率选择机制进行信息更新,经过局部搜索和全局搜索两个过程,最终找到目标解。经蚁群算法优化阈值后,将以更低的维护费用和更少的维护次数保证系统的平稳运行。
建立基于Flexsim的维护仿真模型,并实现MATLAB维护决策模型与Flexsim维护仿真模型之间维护数据的实时动态交互。通过Flexsim强大的统计功能,从设备利用率、系统生产量等方面分析维护策略对生产系统的影响。
最后,将本论文的维护策略和仿真技术应用于汽轮机叶片生产系统,应用结果显示本文建立的维护策略在降低生产系统维护费用,提高生产效率上的有效性与实用性。
Maintenance plays an important role in keeping availability and reliability levels of industrial equipment, weapons and transportation facilities, etc. In the face of increasingly fierce market competition, the enterprises are facing enormous pressure for cost reduction; maintenance cost has attracted attention of more and more enterprises as the largest single controllable cost. At present, corrective maintenance and preventive maintenance have been widely used in enterprises, which produce obvious effect. However, these maintenance strategies may lead to insufficient maintenance or over-maintenance which will bring serious economic loss to enterprises. Besides, most existing models are established for single-unit systems, which are not applicable to practical production systems consisting of multiple units. Therefore, reasonable maintenance decision has extremely vital significance in maintenance cost reduction and production efficiency improvement. In order to solve above problems, the thesis takes multi-unit series-parallel system as the research object, studies dynamic maintenance decision and scheduling method based on fault diagnosis and useful life prediction technology. The main contents are described as follows:
A dynamic maintenance decision model for multi-unit series-parallel system is established considering performance degradation of units, economic dependence and structural dependence between units, and constraints of maintenance resources.
The deterioration of units is modeled by Weibull distribution. Three maintenance actions, including minor repair, imperfect overhaul and replacement, are simultaneously considered to arrange the maintenance schedule of a system, maintenance cost include two parts: maintenance activity cost and downtime cost. Considering several maintenance activities in a time period and setup cost, an overall cost rate model is established.
The genetic algorithm (GA) based methodology is employed to obtain the near optimal multi-unit maintenance scheduling which results in a relatively minimal maintenance cost rate. In the running process of the system, whenever a maintenance activity is generated, the GA will be called for solving the schedule activities.
With respect to the optimization of thresholds in the model, an improved ant colony algorithm is proposed to solve the optimization problem in continuous space. This algorithm updates information according to random probability selection mechanism, through local search and global search process, finally finds the optimal solutions. After maintenance thresholds are optimized, we can ensure the system running smoothly at lower maintenance cost and less maintenance frequency.
A maintenance simulation model is established under Flexsim environment, and real-time dynamic interaction of data between MATLAB maintenance decision model and Flexsim maintenance simulation model is realized. Then the influence of maintenance strategy on production system is analysised from equipment utilization, volume of production etc using Flexsim’s powerful statistical function.
Finally, the maintenance policy and simulation technology are applied to turbine blade production system. The results show the effectiveness and practicality of the maintenance strategy in reducing maintenance cost and improving production efficiency.
引文
1于德介，刘坚，李蓉设备e维护模式的理论与技术湖南大学出版社2005：29-33
2李荣融加强设备管理，为安全生产服务中国设备管理2001，1：4-5
3 A H Christer,W Wang A model of condition monitoring of a production plantInternational Journal of Production Research 1992，30(9)：2199-2211
4张海军，左洪福，梁剑，戎翔民航视情维修决策优化模型发展中国工程科学2005，7(11)：142-146
5张友诚德国企业中的设备管理与维护(上)中国设备工程2001：50～52
6 C Sheu，L J Krajewski Decision model for corrective maintenance managementInternational Journal of Production Research 1994，6(32)：1365-1382
7 M Bevilacqua，M Braglia The analytic hierarchy process applied tomaintenance strategy selection Reliability Engineering and System Safety 2000，70(1)：71～83
8 5LX Zhao On preventive maintenance policy of a critical reliability level forsystem subject to degradation Reliability Engineering and System Safety 2003，79(3)：301-308
9 C C Moya The control of the setting up of a predictive maintenance programusing a system of indicators Int J Management Science 2004，32(1)：57～75
10 L Dieulle，L Berenguerx，A Grall，M Roussignol Continuous time predictivemaintenance scheduling for a deteriorating system Annual Reliability andMaintenabmty Symposium 2004：150～155
11周海川，李建新，张富，陈斌堂预测性维修在现代化设备维护中的应用冶金设备2002，5：48～51
12 S Takata．F Kimura．F J A M Van Houten Maintenance：Changing role in lifecycle management Annals of CIRR 2004，53(2)：643～656
13 D Djurdjanovic．J Lee．J Ni Watchdog Agent An infotronics-basedprognostics approach for product performance degradaion assessment andprediction Advanced Engineering Informatics 2003，17(3)：109～125
14许婧，王晶，高峰，束洪春电力设备状态检修技术研究综述电网技术2000，24(8)：48～52
15 P"EL Tu，R C M Yam，RW Tse An integrated maintenance management systemfor an advanced manufacturing company International Journal of AdvancedManufacturing Technology 2001，17(9)：692～703
16徐英，夏良华，王忠强学报2002，2：54-57
17司文杰，郑映烽，蔡琦99-101确定长贮装备定检周期的一种方法火炮发射与控制预防性维修最佳维修周期决策船海工程2006，5
18韩帮军，范秀敏，马登哲，金烨用遗传算法优化制造设备的预防性维修周期模型计算机集成制造系统．CIMS 2003，9(3)：206～209
19杨文霞，刘卫东基于磨损分析的维修决策模型南昌大学学报2005，27(2)：40-43
20王春花灰色系统理论在机械磨损过程中的维修决策模型探讨江西冶金2006，26(6)：4～6
21谢庆华，张琦，卢涌航空发动机单部件视情维修优化决策解放军理工大学学报2005，6(6)：575～578
22候文瑞，蒋祖华，金玉兰基于相对劣化度的视情维修决策模型上海交通大学学报2008，42(7)：1090～1094
23张海军，左洪福，梁剑，戎翔民航视情维修决策优化模型发展中国工程科学2005，7(1)：17-20
24 Y Tsai．K Wang．H Teng Optimization preventive maintenance for mechanicalcomponents using genetic algorithms Reliability Engineering and System Safety2001，74(1)：89～97
25 X Zhou．L Xi．J Lee Opportunistic preventive maintenance scheduling for amulti-unit series system based on dynamic programming Int J ProductionEconomics 2009．118：361-366
26宓乐英，吕柏荣多设备串行系统预防性维护的动态决策优化研究设计与研究2008，35(11)：8～10
27程志君，郭波多部件系统机会维修优化模型工业工程2007，10(5)：66～69
28周晓军，沈炜冰，奚立峰，李杰一种考虑修复非新的多设备串行系统机会维护动态决策模型上海交通大学学报2007，41(5)：769～773
29金玉兰，蒋祖华，候文瑞以可靠性为中心的多部件设备预防性维修策略的优化上海交通大学学报2006，40(12)：205 1-2056
30 M Marseguerra．E Zio Condition-based maintenance optimization by means ofgenetic algorithms and Monte Carlo simulation Reliability Engineering andSystem Safety 2002，77：15 1-166
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32王凌维修决策模型和方法的理论与应用研究浙江大学博士论文2007：
16徐英，夏良华，王忠强学报2002，2：54-57
17司文杰，郑映烽，蔡琦99-101确定长贮装备定检周期的一种方法火炮发射与控制预防性维修最佳维修周期决策船海工程2006，5
18韩帮军，范秀敏，马登哲，金烨用遗传算法优化制造设备的预防性维修周期模型计算机集成制造系统．CIMS 2003，9(3)：206～209
19杨文霞，刘卫东基于磨损分析的维修决策模型南昌大学学报2005，27(2)：40-43
20王春花灰色系统理论在机械磨损过程中的维修决策模型探讨江西冶金2006，26(6)：4～6
21谢庆华，张琦，卢涌航空发动机单部件视情维修优化决策解放军理工大学学报2005，6(6)：575～578
22候文瑞，蒋祖华，金玉兰基于相对劣化度的视情维修决策模型上海交通大学学报2008，42(7)：1090～1094
23张海军，左洪福，梁剑，戎翔民航视情维修决策优化模型发展中国工程科学2005，7(1)：17-20
24 Y Tsai．K Wang．H Teng Optimization preventive maintenance for mechanicalcomponents using genetic algorithms Reliability Engineering and System Safety2001，74(1)：89～97
25 X Zhou．L Xi．J Lee Opportunistic preventive maintenance scheduling for amulti-unit series system based on dynamic programming Int J ProductionEconomics 2009．118：361-366
26宓乐英，吕柏荣多设备串行系统预防性维护的动态决策优化研究设计与研究2008，35(11)：8～10
27程志君，郭波多部件系统机会维修优化模型工业工程2007，10(5)：66～69
28周晓军，沈炜冰，奚立峰，李杰一种考虑修复非新的多设备串行系统机会维护动态决策模型上海交通大学学报2007，41(5)：769～773
29金玉兰，蒋祖华，候文瑞以可靠性为中心的多部件设备预防性维修策略的优化上海交通大学学报2006，40(12)：205 1-2056
30 M Marseguerra．E Zio Condition-based maintenance optimization by means ofgenetic algorithms and Monte Carlo simulation Reliability Engineering andSystem Safety 2002，77：15 1-166
31 D J D Wijnmalen．J A M Hontelez Coordinated condition-based repairstrategies for components of a multi-component maintenance system withdiscounts European Journal of Operational Research 1997，98：52～63
32王凌维修决策模型和方法的理论与应用研究浙江大学博士论文2007：论文2007：16-26
49谢胜利求解JSP的遗传算法中不可行调度的方案计算机集成制造系统2002，8(11)：902-906
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58吕涛，闰志华应用混合遗传蚁群算法求解柔性车间调度问题制造技术与机床2009，2：124～128
59李燕，陈华平，王栓狮，叶树昱自适应蚁群算法在双向生产车间调度中的应用运等与管理2008，17(3)：160～165
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62张晓萍，刘玉坤系统仿真软件Flexsim3 0实用教程清华大学出版社2006：-1 90
2李荣融加强设备管理，为安全生产服务中国设备管理2001，1：4-5
3 A H Christer,W Wang A model of condition monitoring of a production plantInternational Journal of Production Research 1992，30(9)：2199-2211
4张海军，左洪福，梁剑，戎翔民航视情维修决策优化模型发展中国工程科学2005，7(11)：142-146
5张友诚德国企业中的设备管理与维护(上)中国设备工程2001：50～52
6 C Sheu，L J Krajewski Decision model for corrective maintenance managementInternational Journal of Production Research 1994，6(32)：1365-1382
7 M Bevilacqua，M Braglia The analytic hierarchy process applied tomaintenance strategy selection Reliability Engineering and System Safety 2000，70(1)：71～83
8 5LX Zhao On preventive maintenance policy of a critical reliability level forsystem subject to degradation Reliability Engineering and System Safety 2003，79(3)：301-308
9 C C Moya The control of the setting up of a predictive maintenance programusing a system of indicators Int J Management Science 2004，32(1)：57～75
10 L Dieulle，L Berenguerx，A Grall，M Roussignol Continuous time predictivemaintenance scheduling for a deteriorating system Annual Reliability andMaintenabmty Symposium 2004：150～155
11周海川，李建新，张富，陈斌堂预测性维修在现代化设备维护中的应用冶金设备2002，5：48～51
12 S Takata．F Kimura．F J A M Van Houten Maintenance：Changing role in lifecycle management Annals of CIRR 2004，53(2)：643～656
13 D Djurdjanovic．J Lee．J Ni Watchdog Agent An infotronics-basedprognostics approach for product performance degradaion assessment andprediction Advanced Engineering Informatics 2003，17(3)：109～125
14许婧，王晶，高峰，束洪春电力设备状态检修技术研究综述电网技术2000，24(8)：48～52
15 P"EL Tu，R C M Yam，RW Tse An integrated maintenance management systemfor an advanced manufacturing company International Journal of AdvancedManufacturing Technology 2001，17(9)：692～703
16徐英，夏良华，王忠强学报2002，2：54-57
17司文杰，郑映烽，蔡琦99-101确定长贮装备定检周期的一种方法火炮发射与控制预防性维修最佳维修周期决策船海工程2006，5
18韩帮军，范秀敏，马登哲，金烨用遗传算法优化制造设备的预防性维修周期模型计算机集成制造系统．CIMS 2003，9(3)：206～209
19杨文霞，刘卫东基于磨损分析的维修决策模型南昌大学学报2005，27(2)：40-43
20王春花灰色系统理论在机械磨损过程中的维修决策模型探讨江西冶金2006，26(6)：4～6
21谢庆华，张琦，卢涌航空发动机单部件视情维修优化决策解放军理工大学学报2005，6(6)：575～578
22候文瑞，蒋祖华，金玉兰基于相对劣化度的视情维修决策模型上海交通大学学报2008，42(7)：1090～1094
23张海军，左洪福，梁剑，戎翔民航视情维修决策优化模型发展中国工程科学2005，7(1)：17-20
24 Y Tsai．K Wang．H Teng Optimization preventive maintenance for mechanicalcomponents using genetic algorithms Reliability Engineering and System Safety2001，74(1)：89～97
25 X Zhou．L Xi．J Lee Opportunistic preventive maintenance scheduling for amulti-unit series system based on dynamic programming Int J ProductionEconomics 2009．118：361-366
26宓乐英，吕柏荣多设备串行系统预防性维护的动态决策优化研究设计与研究2008，35(11)：8～10
27程志君，郭波多部件系统机会维修优化模型工业工程2007，10(5)：66～69
28周晓军，沈炜冰，奚立峰，李杰一种考虑修复非新的多设备串行系统机会维护动态决策模型上海交通大学学报2007，41(5)：769～773
29金玉兰，蒋祖华，候文瑞以可靠性为中心的多部件设备预防性维修策略的优化上海交通大学学报2006，40(12)：205 1-2056
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