机械专业英语论文

《专业英语》读书报告

姓名：柳佳琛

专业：机械设计制造及其自动化

班级：08624

学号：2008301390088

分数：

日期：2011年12月11日

PART 1 English-Chinese Translation

Lesson 48 Capitalizing on CAPP 后半部分

原文：

The first of these is the variant or retrieval method.In this method,the computer makes a search through its store of a number of standard or partially completed process plans that have been previously developed by human https://www.360docs.net/doc/401933914.html,ing the current design data supplied by the CAD system,it searches for a plan that was based on a part of similar design.This search can make effective use of group technology design coding to simplify the search for similar code numbers,and hence for similar part designs.This original plan is then modified or completed by the human planner to suit the exact requirements of the current part design.The use of a computer and group technology to search for the most similar past design,and to retrieve the process plan for that design,significantly reduces the work required of the process planners.Their task becomes one of modifying the existing plan to suit the particular dimensions of the current part.They are required to perform the entire process planning method only in the case of a completely new part design.

第一种是检索式工艺过程设计方法。在该方法中,计算机通常搜索已存储的大量标准或部分完成的计划（由规划者先前规划的）。通过使用由CAD系统供应的现存设计数据，设计者为新设计搜索的数据都是基于相似的零件设计。这个搜索能能有效地利用成组技术译码来简化了为寻找相似代码或者相似零件设计的搜索过程。随后，在最初的计划被规划者修改或完成来符合当前零部件设计的精确

要求。对计算机，搜索过去最相似的设计所使用的成组技术，以及为设计所检索的过程设计的使用，能有效减少过程的计划者的工作要求。他们的任务变成了为现有计划修改以适应当前零件的特定范围。他们被要求只在全新的零件的案例设计中演绎的整个过程规划方法。

The second method of computerized process planning is the generative method.In this method,the computer uses stored manufacturing and design data to generate a complete list of all possible process plans that could be used to manufacture the current part.It then exhaustively searches this list for the one which optimizes a specified cost function.This method always yields the optimal process plan for manufacturing a particular part.However,it has a very high cost in time and computer processing expenses.The computations required to produce even a single process plan for an arbitrary part design can be enormously complex.To repeat this for every feasible process plan of a part can become prohibitive.

第二种方法是派生式工艺过程设计方法。在该方法中,计算机利用储存的制造和设计数据来生成一个完整的列表所有可能的工艺计划（可以用于制造当前零件）。然后计算机为这个计划详尽地搜索这个列表来优化其中规定的价值功能。该方法总能生产为制造特定零件所需要的最佳工艺计划。然而，在时间和计算机处理的花费方面，该方法的代价很高。计算机的估算要求能够为一个零件工序设计一个单一的工序计划，并且这个估算相当复杂。然而重复每一个可行的零件计划可以被禁止。

Both of these methods of computerized process planning can also be enhanced through the application of artificial intelligence(AI)technologies in the form of expert systems.In the variant method,AI techniques can be applied to perform the modifications to the selected process plan that are currently performed by a human planner.This involves formalizing the process by which the human planner modifies a retrieved process plan.This process is then captured in the expert system.

两种计算机化过程规划的方法可以通过应用人工智能技术，以专家系统的形式来提高。在检索式工艺过程方法中,可运用人工智能技术进行修改以来选择工艺计划（曾经被人工计划完成）。这涉及到通过人工修订派生式工艺过程设计来使这

个过程正式化。接着这个过程就能被专家系统捕捉到。

This enables the expert system,in conjunction with the existing search process,to produce finished process plans of equivalent quality to the human finished plans.

这使得专家系统通过结合现有的搜索过程来生产并完成工艺过程计划，并且这个计划与人工完成的计划等同。

PART 2 Technical Writing

The Book Report of CAPP

Process planning translates design information into the process steps and instructions to efficiently and effectively manufacture products. As the design process is supported by many computer-aided tools, computer-aided process planning has evolved to simplify and improve process planning and achieve more effective use of manufacturing resources.

Alternatively, process planning is the systematic determination of the detailed methods by which parts can be manufactured from raw material to finished product. In recent years, computer aided process planning has been recognised as a key element in computer integrated manufacturing . In spite of the fact that tremendous efforts have been made in developing CAPP systems, the benefits of CAPP in real-life manufacturing environments are yet to be seen. With the rapid development of computer-aided techniques, both the design and implementation of CAPP have changed greatly since its development.

At present, there are two general approaches to computer aided process planning variant and generative; each one is associated with specific planning techniques.

1.V ariant Process Planning

It follows the principle that similar parts require similar plans. Therefore, the process requires a human operator to classify a part, input part information, retrieve a similar process plan from a database, and edit the plan to produce a new variation of the

pre-existing process plan. Planning for a new part involves retrieving of an existing plan and modification. In some variant systems parts are grouped into a number of part families, characterized by similarities in manufacturing methods and thus related to group technology.

2.Generative Process Planning

Generates process plans utilizes decision logic, formulae, manufacturing rules, geometrybased data to determine the processes required to convert the raw materials into finished parts.It develops new plan for each part based on input about the part’s features and attributes. Due to the complexity of this approach a generative CAPP system is more difficult to design and implement than a system based on the variant approach. But a generative CAPP system does not require the aid of a human planner, and can produce plans not belonging to an existing part family. It stores the rules of manufacturing and the equipment capabilities in a computer system. The generative approach is complex and a generative system is difficult to develop.

Proper combination of the two approaches can make an efficient CAPP system. First the system will check whether the process planning is possible for a new part by variant approach. If variant system is unable to identify the part to be of a previous group or family it will use generative technique for process planning. So both the variant and generative processplanning approaches need further development in parallel.

Significant benefits can result from the implementation of CAPP. In a detailed survey of twenty-two large and small companies using generative-type CAPP systems, the following estimated cost savings were achieved:

1.58% reduction in process planning effort

2.10% saving in direct labor

3.4% saving in material

4.10% saving in scrap

5.12% saving in tooling

6.6% reduction in work-in-process

In addition, there are intangible benefits as follows:

1.Reduced process planning and production leadtime; faster response to

engineering changes

2.Greater process plan consistency; access to up-to-date information in a central

database

3.Improved cost estimating procedures and fewer calculation errors

4.More complete and detailed process plans

5.Improved production scheduling and capacity utilization

6.Improved ability to introduce new manufacturing technology and rapidly update

process plans to utilize the improved technology

For the past three decades, computer-aided process planning has attracted a large amount of research interest. A huge volume of literature has been published on this subject. Today, CAPP research faces new challenges owing to the dynamic markets and business globalisation. Thus, there is an urgent need to ascertain the current status and identify future trends of CAPP. Covering articles published on the subjects of CAPP in the past 10 years or so, this article aims to provide an up-to-date review of the CAPP research works, a critical analysis of journals that publish CAPP research works, and an understanding of the future direction in the field. First, general information is provided on CAPP. The past reviews are summarised. Discussions about the recent CAPP research are presented in a number of categories, i.e.

feature-based technologies, knowledge-based systems, artificial neural networks, genetic algorithms, fuzzy set theory and fuzzy logic, Petri nets, agent-based technology, Internet-based technology, STEP-compliant CAPP and other emerging technologies. Research on some specific aspects of CAPP is also provided. Discussions and analysis of the methods are then presented based on the data gathered

from the Elsevier's Scopus abstract and citation database. The concepts of ‘Subject Strength’ of a journal and ‘technology impact factor’ are introduced and used for discussions based on the publication data. The former is used to gauge the level of focus of a journal on a particular research subject/domain, whereas the latter is used to assess the level of impact of a particular technology, in terms of citation counts. Finally, a discussion on the future development is presented.

The importance of CAPP in a modern manufacturing facility cannot be underestimated. CAPP provides a direct link between design and manufacturing. It reduces the time spent between part design and actual manufacture. The CAPP systems of the future should be dynamic, flexible and intelligent. The successors to intelligent systems will be "learning systems" that can monitor production and feed data back to the system. This feedback wilt become the teacher. The systems will be able to learn from manufacturing mistakes and therefore improve the performance. The advantages of a learning and self-adapting system should include more accurate time and cost estimates, improve productivity, ability to monitor processes, less variability, more reliability and reduced human involvement. The CAPP area has been greatly developed in the last two decades and many techniques have been involved. An attempt has been made to present the state-of-the-art of CAPP systems developed during the period 1989-1996. Some of the welt-known CAPP systems are discussed in this paper. The discussion focuses on the general aspects of the systems, such as, functions, working steps, approaches of implementation, methodologies of knowledge

representation, programming language, architecture, and pros and cons of the system.