自动化专业英语论文(附译文)(华北电力大学)

分数: ___________

任课教师签字：___________ 华北电力大学本科生结课作业

学年学期：2011-2012学年第二学期

课程名称：专业外语阅读(自动化)

学生姓名：

学号：

提交时间：2012年6月19 日

The Major Component Assembly Line of an

Aircraft

Every Boeing commercial is airplane is customized for a specific customer. Manufacturing processes of some major component are desirable to follow the FMS concept in a customized manufacturing environment. In the case study that follows,a wing assembly process is examined by means of discrete simulation modeling. There are more than thirty complex processes applied to more than fifteen machine classes in this example .Most processes require a different number of labor entities from various labor classes.The overall pace of the whole system is desired to be a variable that impacts the process time of all related processes,as well as the number of assigned laborers.The modular approach to MCM system design not only benefits the overall performance of flexible MCMsystem,but also enhances simulation-modeling exercises.

Discrete event simulation technology in this study employs the same platform concept as in modeling highly flexible and rapid reconfigurable production lines.such modeling methods reflect manufacturing processes according to the every-changing customized demands.Many fundamental manufacturing process parameters,such as layout reconfigurations, and resource re-allocations, can be derived ahead of time from the simulation models.

A high-level process flow of this simulation model is shown below in Figure 5-4-1, where sourcel1 generates incoming parts according to the system takt time with optional statistical distributions. Buffer S receives incoming parts via the only crane resource in the system. The part will then be lifted by the crane to the machine

B where multiple processes will be performed by multiple resources. The part then continues to move from the machine B to the machine P, the end of the process line. Multiple processes are assigned throughout this line on each machine. An additional process is needed in the middle of the line where the part will be transferred to the buffer A followed by a couple of external processes. Afterwards, buffer A receives the part and calls for the overhead crane to transfer the part back to buffer T where the part will continue through the rest of the process. At the end of the line, the part goes from the machine P to the buffer A then to the sink, which is the final destination of all parts in the simulation model.

Two different part-carrying platforms are involved in the system. The “high

speed” dolly transfers parts to and from buffer A. The “low speed” dolly carries one part at a time from machine B all the way to machine P. additional components are introduced to the system from source 2 and 3 at different stages of this process line.

Resource class types in this model consist of labor, machine , and Automatic Guided Vehicle (AGV) elements. The machine class stands alone for each machine, while the labor and AGV classes are managed by their respective controllers. Those thirty plus processes that are stand-alone objects can be assigned to multiple machines. Thus, each machine has from two to six assigned processes . Processes run at all times in an endless do-loop as part of the nature of logic and its assigned time duration on the machine where it resides. After the last process sequence of the last machine class has been executed, the part is transferred to the sink class where it will be logically destroyed and removed from the modeling system.

A Shop Data File containing resource, layout, and process information of an assembly line is used to generate Batch Control Language (BCL) file, according to the process discussed in the next paragraph. This BCL file can then be directly executed in QUEST. The aircraft major component assembly line simulation is created and driven by this BCL file.

Because this model is created from an XML-based Shop Data File, modifying scenarios of the model file can be easily accomplished by changing element attributes of the source XML file. As in the example shown above, the BCL specific commends, such as CREATE PART CLASS, are managed in the XML style sheet. Simulation model object related information, such as the part color and name of the part class “Part737RHwing” are originated from the Shop Data File. A complete new BCLis file generated per flexible manufacturing scenario. This BCL file then executes and generates a customized QUEST simulation model for its matching conceptual FMS environment.

The approach of this simulation modeling successfully manages a flexible customized manufacturing system in a flexibly modulated and customized fashion. For each complicated customized scenario, it is comprehensive that traditional manual modeling modification will take much longer effort than this technique. As compared to alternative approaches to this MCM application, benefit of this innovative methodology is evident in the following points:

●Customizable

●Ease of deployment

●Portability of the XML-base shop data file

●Popularity of the XML language

●Scalable

●Reusable of the modulated seed model file

Additional detailed verification between simulation models and flexible MCM exercises on the shop floor remain to be fully performed once this conceptual process development turns into reality. Nevertheless, approaches and methodologies presented in this work illustrate unparalleled advantages in operating flexible and customized manufacturing systems.

complex optimization methods based for example on evolutionary algorithms have not been selected.

Strategy A: First free line

This is probably the simplest of all scheduling policies but unfortunately in many cases not a very efficient one. It has been considered in this work as a base for comparison with other, more advanced, strategies. First free line strategy will order the batches by increasing estimated start time. These batches will then be sent to the first production line becoming available. The choice of the production line doesn’t depend on any specific criterion. This is the worst-case scenario and therefore only poor results are expected.

Strategy B: Priority to oven temperature

This strategy is slightly more advanced than the first free line strategy: priority is given to the reduction of setup times for the production lines. Longest setup times appear to be for the soldering oven, where temperature changes may take up to an hour. It makes sense therefore to sort batches out according to their required soldering temperature.

Strategy B categorizes batches according to their soldering temperature and in each category, those batches are ordered by increasing start time. Production lines are then affected to a specific oven temperature in order to minimize setups.

Strategy C: Improved oven temperature priority

Based on the strategy B, this strategy keeps the characteristics described above. Main improvement is made on the simulation termination, where strategy B had the disadvantage to let some lines run empty much earlier than other ones, depending on the workload for a specific oven setting. With strategy C, when a production line runs empty, state of the workshop is observed. If another production line has an important remaining workload and several orders in its queue line, then part of this production will be rerouted to the empty production line. This way, oven setup is only done when no other batch is available for a given production line.

Strategy D: Mixed strategy

Mixed strategy is a result of observations made on the previous strategy. Changing the oven temperature is a long process but doesn’t necessarily penalize production when done in an intelligent fashion. Production lines rarely run completely empty for a specific temperature setting, so strategy C would never apply in a real case. However it is not considered clever for example to run a production line when

only few orders are scheduled at a much later date. For this reason it is possible to introduce time windows in which strategy C would apply.

Mixed strategy starts production based on an oven temperature priority. However, when workload diminishes and a production line runs empty in a given time window, then orders will be rerouted from the production line with the heaviest workload. After completion, production can go back to normal.

译文：

飞机主要构件装配线

波音公司的每一架商业飞机都是为特定的顾客定制的。在这样一个定制的环境下，按照FMS思想的指导，一些主要构件的制造过程是理想的。在下面研究的例子中，一个机翼的装配过程被用许多分离的仿真模型检测。

这个例子中，三十多种复杂工序应用在十五中以上的机器种类中，大部分程序需要各种不同等级的劳动者的数量不同。整个系统的节奏理想上是个变量，该变量会影响所有相关进程的处理时间，以及所分配的劳动者的人数。这种用MCM 系统设计的元件，不仅对整个弹性MCM系统的性能有益，而且还能提高仿真模型的运作。

在这个研究中，为了能够建立高度柔性和快速可重构的生产线，分散事件仿真技术使用了同一个平台。这种建模方法反映了根据不断变化和个性化需求的生产过程。许多基本的生产过程变量，比如设计的重新配置，资源再分配，能够从仿真模型中提前导出。

源自这个仿真模型的一个高水平过程如下：在这个过程中，资源1根据选择性统计进入的模块得到的系统计划运转时间得到零部件，缓冲器S通过系统为一的升降架接受零部件，随后这个部件将通过升降架运送到机器B，在这里，多重过程将被多种资源表现出来。部件将继续从机器B转移到机器P，工艺流程的结束机器。多重过程通过这条工艺流程被分配到每一个机器中，这个工艺的中间需要附加一个工程，在这里元件将被运送到缓冲器A，它后面还有两个额外的过程。然后缓冲器A接受元件并要求前面的升降架将元件传送回缓冲器T，元件在缓冲器T将继续通过剩余的程序。在过程的最后，元件将从机器P到达缓冲器A，然后进入废垢槽，这里是仿真模型中所有元件的终点站。

这个系统包含两个不同的载物台，高速小车从缓冲器A中运进和运出元件，低俗小车在某一时间从机器B携带元件一直到机器P，额外构件在这个过程的不同阶段。

在这个模型中，资源种类形式有劳动者、机器和AGV元素。对每一台机器来说，机器的类型都是独一无二的，而劳动者和AGV都是由各自的控制器所决定。这三种相加撤程序是独一无二的物体，能够被分配到不同的机器中，这样每一台机器都有2到6个指定程序。作为建模环境的部分性质，程序一直处于无休止的循环运行中，一旦程序运行的条件满足，程序将在它寄存的机器上执行逻辑和分配的持续时间。在最后一台机器的最后一道程序执行后，元件将被送至废垢槽中，在槽中，元件将被从逻辑上摧毁并从建模系统中除去。

工厂数据库包含资源、布局和装配线工艺信息，根据下一段讨论的工序，它

被用于得到BCL文件。BCL文件然后可以直接在QUEST中运行，飞机主要构件配线的仿真模型就是通过BCL文件产生和驱动的。

因为这个模型是基于XML工厂数据库得到的，所以模型的方案通过改变XML文件的元素属性很容易实现。如同上面的例子，BCL具体的优势，比如CREST PART CLASS,就在XML类型表格中设计。仿真模型对象相关的信息，比如元件颜色和元件类名“Part737RHwing”就是源于工厂数据库。一个完全的BCL 文件通过每一个柔性制造方案产生。这个BCL文件然后运行并且为它相称的概念上的FMS环境产生一个特定的QUEST仿真模型。

这个仿真模型的获取在柔性调整和定制的形式下，成功的控制了一个柔性定制制造系统，对各个复杂的定制方案来说，可以理解的是传统的手工建模的修改要比这个方案花费更多的精力，与解决MCM应用的方案比较，这种穿心的方法的优点是很明显的，表现在以下几点：

可定制

易于部署

基于XML数据库的可携性

XML语言的广泛性

可扩展

调制子模型文件的可重复使用性。

一旦这个概念的过程发展变成现实，车间的仿真模型和灵活的MCM演习之间附加详细的核查将继续得到充分执行。然而，在这项工作中表现的方案和技术，说明了它在灵活操作和定制的制造系统中独一无二的优势。

阅读材料

调度策略的比较

一些非常简单的调度策略在仿真模型上得到了测试，用仿真模型是最简单的途径，并且实现它们只需要极少的适应的生产工具，因为在当前的系统状态下，他们主要是指操作者行为的变化，因此观察这些辩护如何影响过程输出是很有趣的。

然后，它的缺点是优化方法是有限的，并且必须保持简单，在以下部分展现了四种不同的调度策略，他们其中的三种已被仿真模型进行了测试。然后，混合策略将需要改变模型的结构，并用外部软件来运行优化算法。处于相同的原因，更复杂的优化方法，比如进化算法，没有被选择。

策略A：第一自由线

这可能是所有调度策略中最简单的，但不幸的是，在许多情况下，它不是非常有效的一个，因此比较起来，它一直被认为是其它更先进策略的基础。第一自由线策略通过增加估计的起始时间来，命令批生产量，然后这些批次将被发送到第一生产线，生产线的选择不依赖于具体的准则。这是最坏的方案，因此期望的只有很差的结果。

策略B：焊炉温度优先级

这个策略稍微比第一自由线策略先进，它优先考虑生产线，以减少调试时间，最长的调试时间出现在炉中软纤焊中，它里面的温度变化可能需要长达一个小时。因此，根据他们需要的焊接温度理清批次是很有道理的。

策略B根据它们需要的焊接温度对批进行分类，而且在每一类中，对此批次通道增加的启动时间进行排序。因此减少了设置，生产线将受一个特定的焊炉温

度的影响。

策略C：改进的焊炉温度优先级

基于策略B，这个策略继承了上面描述的特征，主要的改进是在仿真的终止，因为策略B有比其它策略容易使仿真线路空运的缺点，而改进的策略是基于一个特定的我焊炉工作量来设置的。所以当一条生产线空运时，策略C车间的状态将被观测到。如果另一条生产线具有重要的剩余工作量，并且队列中还有几个命令，部分生产将被改到空的生产线上。焊炉只在没有其它批次可用的情况下设置。

策略D：混合策略

混合策略是对以前策略提出意见的结果。改变焊接温度时一个很长的过程，但在一个正确的形式下，不需要乘法生产。生产线在设定的特定温度下很少完全空运，所以策略C在实际中将不被应用。然而，它也并不是一个非常好的方法，比如只有极少的命令被安排在更晚的情况下运行一条生产线。处于这个原因，推出时间窗是可能的，这样策略C将得到应用。

在焊炉温度优先级的基础上，混合策略开始生产。然而，当工作量减少和生产线在一个给定的时间窗口下进行空运时，命令将从生产线改到最终的工作量上。项目建立以后，生产可以恢复正常。

摘自《English for Specific Purpose of Automatization》主编：杨春生北京理工大学出版社。