制造物联网环境下混流制造过程自适应调度方法研究
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摘要
混流制造是一种以客户需求为导向、在当前大批量定制生产中的常见生产组织模式。其生产订单存在多品种、周期性、数量多变等特点,但生产过程资源需求模型相对固定。混流制造过程不可避免存在诸多不确定的动态事件,如设备故障、紧急插单、质量事故等,导致生产过程无法遵循预定义的基准计划执行。因此对混流制造采取合理的动态调度机制,以消除动态事件对计划执行的影响,保持制造过程的稳定性,成为一个重要科学问题。
然而,目前对动态调度的研究多集中在一个理想模型下的调度理论研究,其随机事件的加入也大多基于某种理论模型,没有考虑车间信息反馈断层的问题,缺乏在实际应用中的技术支撑环境,在实际应用中无法应对车间现场的瞬息万变。随着物联网技术飞速发展,实时制造环境下的自适应调度,具备了实现的技术基础。
本论文在国家基金“基于RFID的分时段双层实时动态OKP调度理论模型与算法研究(61074146)”支持下,基于制造物联网实时制造环境,对混流制造过程在实时反馈条件下的自适应调度方法进行了研究。
论文的具体研究内容如下：
1)、针对目前我国中小企业制造车间存在的信息断层问题,构建了一个基于制造物联网技术的实时制造系统的框架,为后续混流过程的自适应调度研究提供了技术基础。在此框架下,采用了统一接口构建了RFID中间件实现了Multi-Agent封装模式下RFID对象的即插即用接入。然后设计了一个基于RFID-Bus的实时消息处理模式,实现了实时制造消息的处理和反馈统一机制。基于此机制,构建了一个两级RFID-Bus的实时制造系统环境及其在企业制造车间的部署方法。
2)、针对混流制造系统规模庞大,难以求解的难题,提出了一个基于ROPN的制造系统MPN建模机制,给出了具体的建模流程和方法,缩小了混流制造系统模型规模。论文先分析了混流制造过程带转运／缓存约束的非等价并联机制造的特点,通过将等价并行机建模成一个资源提供节点,提出了一种基于制造系统资源建模方法和建模流程。定义了MPN (Manufacturing Petri Net)模型,在模型中阐述了基于实时制造物联网中智能令牌在模型中映射的知识函数,及路径查找办法。
3)、构建了混流制造系统MPN模型后,对MPN中非等价并联机调度问题进行了分析,针对混流模型中并联机调度难题,构建了一个通过调度变迁触发顺序来进行作业调度的离线调度方案,并给出了基于MMAS的蚁群算法的优化方法,并采用田口实验设计方法对算法中的参数最优配置进行了探求,形成了制造系统执行的基准计划。
4)、针对基准计划在MPN中的执行,首先分析了实时制造环境下大规模定制混流制造过程的动态事件的特点,并将动态事件在MPN中统一映射为资源提供能力的失能事件。根据实时制造环境的特点,采用修正式策略,构建了一个计划与执行交互的在线自适应调度的框架。在这个框架中,通过树结构的决策单元,实时监控制造系统MPN中各作业的执行偏离度,根据偏离度分布情况进行实时修正。然后,根据决策树结构特点,提出了一个基于层级反馈的在线调度方法,并对在线调度方法进行了实现。
5)、根据论文提出的自适应调度框架和理论,开发了一套自适应调度仿真系统,对制造系统进行了仿真和推演,对算法有效性进行了验证。
案例测试结果表明,本论文提出基于制造物联网实时制造环境的自适应调度方法,在某些动态事件模式下,可以有效的消除其对制造系统的影响,提高车间生产效率,验证了论文工作的合理性。
本论文研究内容还有许多不足之处需要不断完善和改进,有待今后进一步研究。
Hybrid Flow Shop (HFS) manufacturing is a kind of customer-demand-oriented production mode which is commonly seen in mass customization production nowadays. Its production orders features multi-species, periodicity and quantity variety. But its resource demand model during the production is relatively stable. Inevitably, there are many uncertain dynamic events in the procedure of HFS manufacturing, such as equipment breakdowns, emergency orders, and quality accidents. And because of that, the pre-scheduled plan cannot execute as its wish. So dynamic scheduling mechanism is desired to eliminate the influence of dynamic events and maintain the stability of the manufacturing process.
However, most of the researches on dynamic scheduling are based on an ideal production model with its random events following some kinds of distribution, without considering the problem of workshop info-feedback failure in acutual shop floor. So it is hard to cope with practical workshop situation. Especially with the rapid development of the Internet of Things (IOT), it opens the way to real-time manufacturing environment, which makes the realtime adaptive scheduling possible.
This thesis is supported by the NSFC 'Research on multi-stages bi-level realtime dynamic scheduling for OKP based on RFID (61074146)'. The research is about adaptive scheduling method for HFS manufacturing in real-time feedback situation based on the Internet of Manufacturing Things (IOMT).
The specific research contents of the thesis are as follows:
1) To solve the information gap problem in shop floor, a real-time manufacturing system framework is proposed based on the technology of IOMT which provide the technical basis for the follow-up study. In this framework, RFID middleware with unified interface specification is programed to realize the plug-and-play access of RFID object under Multi-Agent encapsulation mode. Then a RFID-Bus is designed to process the real-time manufacturing information in a unified feedback mechanism. Based on this RFID-Bus, a real-time manufacturing system environment and its deployment method in the shop floor are constructed.
2) To solve the problem of large model scale in actual enterprises, a MPN (Manufacturing Petri Net) modeling mechanism based on ROPN (Resource Oriented Petri Net) is proposed to reduce the model scale. A MPN model is defined to do this by modeling the equal-parallel-machine into one resource node, in which elaborated the knowledge function and the path search method which is mapped in the model by the intelligent token.
3) After the analysis of the nonequal-parallel-machine problem in MPN, an offline scheduling algorithm based on MMAS (Max-Min Ant System) is designed. In this algorithm, a transition fire sequence is optimized instead of the token flow sequence. And Taguchi method is used to find the best parameters configurations. By this algorithm, an optimized baseline plan for the MPN can be produced.
4) For execution of the baseline plan in MPN, after analyzing the characteristics of dynamic events in HFS in the real-time situation, the thesis maps the dynamic events into capacity-disable events in the MPN. According to the features of real-time manufacturing environment, using the modification strategy, an online adaptive scheduling framework based on interacting of the plan and execution is proposed. In this framework, a decision tree is structured to monitor the executing deviation of each job in the real-time MPN and makes adaptive scheduling decisions. Then, using the decision tree structure, an online scheduling algorithm based on level-feedback is designed.
5) According to the above researches, an adaptive scheduling system is realized to simulate the operation of MPN system and deduct the plan execution to verify the effectiveness of the algorithm.
A large number of tests and results show that the adaptive scheduling method in IOMT environment proposed by this thesis is able to eliminate the influence by some dynamic events and improve the efficiency of production.
The research of this thesis still has many deficiencies need to improve in further study.
然而,目前对动态调度的研究多集中在一个理想模型下的调度理论研究,其随机事件的加入也大多基于某种理论模型,没有考虑车间信息反馈断层的问题,缺乏在实际应用中的技术支撑环境,在实际应用中无法应对车间现场的瞬息万变。随着物联网技术飞速发展,实时制造环境下的自适应调度,具备了实现的技术基础。
本论文在国家基金“基于RFID的分时段双层实时动态OKP调度理论模型与算法研究(61074146)”支持下,基于制造物联网实时制造环境,对混流制造过程在实时反馈条件下的自适应调度方法进行了研究。
论文的具体研究内容如下：
1)、针对目前我国中小企业制造车间存在的信息断层问题,构建了一个基于制造物联网技术的实时制造系统的框架,为后续混流过程的自适应调度研究提供了技术基础。在此框架下,采用了统一接口构建了RFID中间件实现了Multi-Agent封装模式下RFID对象的即插即用接入。然后设计了一个基于RFID-Bus的实时消息处理模式,实现了实时制造消息的处理和反馈统一机制。基于此机制,构建了一个两级RFID-Bus的实时制造系统环境及其在企业制造车间的部署方法。
2)、针对混流制造系统规模庞大,难以求解的难题,提出了一个基于ROPN的制造系统MPN建模机制,给出了具体的建模流程和方法,缩小了混流制造系统模型规模。论文先分析了混流制造过程带转运／缓存约束的非等价并联机制造的特点,通过将等价并行机建模成一个资源提供节点,提出了一种基于制造系统资源建模方法和建模流程。定义了MPN (Manufacturing Petri Net)模型,在模型中阐述了基于实时制造物联网中智能令牌在模型中映射的知识函数,及路径查找办法。
3)、构建了混流制造系统MPN模型后,对MPN中非等价并联机调度问题进行了分析,针对混流模型中并联机调度难题,构建了一个通过调度变迁触发顺序来进行作业调度的离线调度方案,并给出了基于MMAS的蚁群算法的优化方法,并采用田口实验设计方法对算法中的参数最优配置进行了探求,形成了制造系统执行的基准计划。
4)、针对基准计划在MPN中的执行,首先分析了实时制造环境下大规模定制混流制造过程的动态事件的特点,并将动态事件在MPN中统一映射为资源提供能力的失能事件。根据实时制造环境的特点,采用修正式策略,构建了一个计划与执行交互的在线自适应调度的框架。在这个框架中,通过树结构的决策单元,实时监控制造系统MPN中各作业的执行偏离度,根据偏离度分布情况进行实时修正。然后,根据决策树结构特点,提出了一个基于层级反馈的在线调度方法,并对在线调度方法进行了实现。
5)、根据论文提出的自适应调度框架和理论,开发了一套自适应调度仿真系统,对制造系统进行了仿真和推演,对算法有效性进行了验证。
案例测试结果表明,本论文提出基于制造物联网实时制造环境的自适应调度方法,在某些动态事件模式下,可以有效的消除其对制造系统的影响,提高车间生产效率,验证了论文工作的合理性。
本论文研究内容还有许多不足之处需要不断完善和改进,有待今后进一步研究。
Hybrid Flow Shop (HFS) manufacturing is a kind of customer-demand-oriented production mode which is commonly seen in mass customization production nowadays. Its production orders features multi-species, periodicity and quantity variety. But its resource demand model during the production is relatively stable. Inevitably, there are many uncertain dynamic events in the procedure of HFS manufacturing, such as equipment breakdowns, emergency orders, and quality accidents. And because of that, the pre-scheduled plan cannot execute as its wish. So dynamic scheduling mechanism is desired to eliminate the influence of dynamic events and maintain the stability of the manufacturing process.
However, most of the researches on dynamic scheduling are based on an ideal production model with its random events following some kinds of distribution, without considering the problem of workshop info-feedback failure in acutual shop floor. So it is hard to cope with practical workshop situation. Especially with the rapid development of the Internet of Things (IOT), it opens the way to real-time manufacturing environment, which makes the realtime adaptive scheduling possible.
This thesis is supported by the NSFC 'Research on multi-stages bi-level realtime dynamic scheduling for OKP based on RFID (61074146)'. The research is about adaptive scheduling method for HFS manufacturing in real-time feedback situation based on the Internet of Manufacturing Things (IOMT).
The specific research contents of the thesis are as follows:
1) To solve the information gap problem in shop floor, a real-time manufacturing system framework is proposed based on the technology of IOMT which provide the technical basis for the follow-up study. In this framework, RFID middleware with unified interface specification is programed to realize the plug-and-play access of RFID object under Multi-Agent encapsulation mode. Then a RFID-Bus is designed to process the real-time manufacturing information in a unified feedback mechanism. Based on this RFID-Bus, a real-time manufacturing system environment and its deployment method in the shop floor are constructed.
2) To solve the problem of large model scale in actual enterprises, a MPN (Manufacturing Petri Net) modeling mechanism based on ROPN (Resource Oriented Petri Net) is proposed to reduce the model scale. A MPN model is defined to do this by modeling the equal-parallel-machine into one resource node, in which elaborated the knowledge function and the path search method which is mapped in the model by the intelligent token.
3) After the analysis of the nonequal-parallel-machine problem in MPN, an offline scheduling algorithm based on MMAS (Max-Min Ant System) is designed. In this algorithm, a transition fire sequence is optimized instead of the token flow sequence. And Taguchi method is used to find the best parameters configurations. By this algorithm, an optimized baseline plan for the MPN can be produced.
4) For execution of the baseline plan in MPN, after analyzing the characteristics of dynamic events in HFS in the real-time situation, the thesis maps the dynamic events into capacity-disable events in the MPN. According to the features of real-time manufacturing environment, using the modification strategy, an online adaptive scheduling framework based on interacting of the plan and execution is proposed. In this framework, a decision tree is structured to monitor the executing deviation of each job in the real-time MPN and makes adaptive scheduling decisions. Then, using the decision tree structure, an online scheduling algorithm based on level-feedback is designed.
5) According to the above researches, an adaptive scheduling system is realized to simulate the operation of MPN system and deduct the plan execution to verify the effectiveness of the algorithm.
A large number of tests and results show that the adaptive scheduling method in IOMT environment proposed by this thesis is able to eliminate the influence by some dynamic events and improve the efficiency of production.
The research of this thesis still has many deficiencies need to improve in further study.
引文
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