外文翻译--智能腔布置设计系统的注塑模具【中英文文献译文】
外文翻译-智能腔布置设计系统的注塑模具【中英文文献译文】,中英文文献译文,外文,翻译,智能,布置,设计,系统,注塑,模具,中英文,文献,译文
外文翻译专 业 机械设计制造及其自动化 学 生 姓 名 朱 丹 萍 班 级 BD机制042 学 号 0420110226 指 导 教 师 刘 道 标 外文资料名称: An Intelligent Cavity Layout Design System for Injection Moulds外文资料出处: International Journal of CAD/CAM Vol 2,No.1,pp 6975(2002) 附 件: 1.外文资料翻译译文 2.外文原文 指导教师评语: 签名: 年 月 日智能腔布置设计系统的注塑模具胡卫刚,Syed Masood朱丹萍 译摘要:本文介绍了多腔注塑模具。多腔注塑模具是一种智能腔布置设计系统。该系统的目的是协助模具设计人员在腔布局设计,在概念设计阶段。该复杂性和原则腔布局设计以及各属地的注塑模具设计介绍。对于腔布局设计,从功能,整体结构和总体过程中一一解释。文中还讨论了这些问题,作为知识表示和基于案例的推理在使用该系统的发展。系统的功能是用一实例说明了腔布局设计问题。关键词:智能设计,腔体布局设计,注塑模具设计,基于案例推理,系统设计。1、导言 在制造,注塑成型,是一个最广泛使用的生产工艺生产塑胶零件与高生产速度和很少或没有整理需要对塑料制品等。过程包括注射液的塑料材料,从一个热点成为一个封闭的模具,从模具中使塑料酷凝固和拔出成品。因为每一个新的塑料制品,注塑成型机,需要有新的注塑模具。设计和制造注塑模,是一个费时和昂贵的过程和传统上需要高度熟练的工具和模具制造商。注塑模具包括几个部分,其中包括结晶器基地,有溶洞,导向销,浇道,盖茨,冷却水渠道,幻灯片和喷射器。模具设计也受其他几个因素,如部分几何,模具素材,每腔模具。 在计算机技术和人工智能智力中得到指示,以减少成本和时间,在设计和制造的一种注塑模具。注塑模具设计一直是主要的研究领域,因为它是一个复杂的过程涉及几个子设计相关的各种组件该模具,每个需要专业的知识和经验。模具设计,也影响到生产率, 模具维修成本,可制造模具, 和高质量的注塑部分。大部分的工作在模具设计工作已经向应用系统,知识为基础的系统和人工智能情报,以补充大量专业知识,在传统的设计过程。 kruth和willems研制出一种智能支持系统的设计注塑模具整合商用CAD / CAM系统,关系数据库和一个专家系统。提出了一个系统化方法论和知识库,为注塑模具设计在并行工程环境。 raviwongse 和allada制定了一个神经网络化设计辅助工具,计算出模具复杂性指数,以帮助模具设计人员,以评估他们提出了模具设计对模具制造。制定了一个计算系统为工艺设计的注塑基于黑板为基础的专家系统和基于案例推理方法,其中包括模具设计, 生产调度,成本估算和注塑参数。讨论了注塑模具设计,从功能性透视使用功能设计知识。发展一个互动的以知识为基础的CAD系统注射模具设计知识和图形模块。 几项研究也取得了改善设计中的具体组成部分的注塑模具。 王景荣等制定了一个以知识为基础的和面向对象设计方法的饲料系统注塑模具,它可以有效地设计类型, 位置和大小相当于一浇注系统在模具。也开发了软件系统,实现自动设计浇注并提供评价浇注设计基于特定的性能参数。提出了一套方法测定方向,在注塑模具设计的基础上自动识别与提取削弱特点。在模具设计中通过计算削弱卷,最大限度地减少破坏了工作,在设计冷却系统在注射模,并提出优化设计根据热分析和设计灵敏度分析该冷却阶段的注射成型工艺。 注塑模具设计中,其中有很少人注意设计的腔布局多腔注塑模具。腔布局设计影响到整个过程的注塑成型,直接, 由于这是其中一个最重要的阶段,在模具设计过程。审议腔布局设计在注塑模具,在概念设计阶段,将改善质量注射成型产品。本文介绍了开发一个设计支持系统,所谓智能腔布局设计系统,为多腔注塑模具基于知识基础和面向对象的方法。 它采用了基于案例,并裁定为基础的推理到达布局解决方案。它是基于对商业软件系统命名为综合开发平台,让顾客发展自己的知识为基础的系统。该目的是要充分利用现有的技术人工智能在协助模具设计师概念设计阶段。2 、型腔布置设计在注塑模具 目前的做法为注塑模具的设计,尤其是腔布局设计,在很大程度上取决于设计师的经验和知识。因此,它将是不可取利用知识工程,人工智能和智能设计技术在创造一个可接受型腔布置设计在注塑模具准确,高效率。在模具设计中,大多数的格局腔布局和规则和原则腔布局设计也可以很容易的代表参与形式的知识, 它可以用来设计系统。例如,以选择合适的布局模式设计主要是依赖于工作环境, 条件和要求的客户,主要基于设计师的技能和经验。作选择相互矛盾的因素,将依靠明显设计师的知识和经验。这是相当适合智能化设计技术,以用于系统设计这样的情况,特别是创新设计。 注射模的设计,主要涉及考虑设计的下列要素:( 1 )模具类型( 2 )有多少腔腔布局( 4 )流道系统( 5 )喷射系统( 6 )冷却系统( 7 )确定冷却系统( 8 )图形结果显示,输出3 、结构和设计过程 结构智能腔布局设计系统是基于案例推理和推理设计围绕软件系统。所示的总体结构可以看出,一般设计过程中开始与定义中的设计规格。该系统检索出类似的案件,从案件基地通过计算之间的相似性案件和新的案例。如果解决不好,那么将利用以规则为基础的推理双方达成一项解决方案。如果解决的办法是仍然不理想的话,那么用户必须修改部分的初步设计规格。使用基于案例的技术,在设计过程中使用户能够获得解决问题的设计问题更迅速和灵活的结构,知识基础和数据库的使用在发展是基于背后知识库和数据库结构,从软件系统是上讲,这是一个在商业上可用软件开发平台。4 、发展4.1 、分类知识 各种逻辑和步骤所涉及的版面设计, 有各种不同的知识,并需要以描述和代表在腔版面设计。该类型的知识,可分为五种基于面向对象(面向对象)的概念,分述如下: ( 1 )设计实例/案例:以前设计的情况下,结合目前的设计实例( 2 )属性:设计变量,特性设计问题( 3)规则:一般设计规则,设计经验( 4 )程序和/或模型:数值计算, 数学建模,分析,评价和程序。4.2 、基于案例的推理 基于案例推理法是依赖于第一案例名词。基于案例检索的基础是相似公制 。因此,如何计算相似度显然很关键。 相似性度量让每一个层面对应于一个领域,其价值是在查询,它们之间的距离的情况和查询(对应点在这多维空间)的计算方法是不同的,为序和名义领域的合作。 4.3 、距离为序领域的距离计算方法是: ( 1 )其中,自dij必须介于0和1 ,还必须介于0和1 。( 2 )其中,因为该公司与dij必须介于0和1 , 还必须介于0和1 。4.4 、验证案例 验证的情况是,以检查是否每条可接受的情况下,找出最合适的一个,所以每个案件应相关的测试方法和测试结果都不同。 不仅如此,根据一定的条件,它的测试结果,设计问题,可视为解决方案原型为进一步完善。 4.5 、准则的有效性降低成本 随着应用空腔布局,两种降低成本。一个是整体理论降低成本所取得的使用系统进行概念设计的注射液模具。另一种是实际成本降低的价值记录在案例中,其中可能被用来做案例库推理,如果案件以降低成本为理论之一,就没有必要的任何标准的有效性,降低成本,因为节省成本将明显地走出来,提高设计质量和回应给客户。对于有效性的实际成本进一步降低。举例来说, 我们可以比较一下,并确定哪一个能更好地适合客户的要求。你还可以使用比例降低成本的公式做比较。该百分比降低成本都可以计算出来。5 、应用实例 一个应用实例, 测定腔布局模式 , 概念设计腔布局 所提供的智能腔布置设计系统,提供以下资料: 如果最初的设计条件是: ( 1 )使用什么类型的模具?两板块( 2 )使用什么类型的转轮? ( 3 )什么形状的产品能使其成型? 矩形,其结果是由于:格局腔布局设计是: Y型矩形布置知识基础,是开发利用的特点。6 、结论 问题的设计型腔布置多重腔注射模具由电脑辅助设计支持系统。 注塑成型由计算机为基础的设计系统提供,极大的节省了时间和成本,在达成最佳布局。 发展智能腔布局设计系统)相信是第一次尝试在这个方向利用知识为基础的方针。该发展注塑模具是基于在Windows环境下PC机。从实际的角度来看,可以用来作为一种工具来设计以落实腔布局设计的注射液模具在概念设计阶段。它提供了一个积极一步的发展,完全自动化注塑模具设计过程中,从产品模型模具制造。七、参考文献1 Menges, G. et. al. (1986), “How to Make InjectionMolds”, Hanser Publisher, Munich.2 Kruth, J.P. and Willems, R. (1994), “Intelligent supportsystem for the design of injection moulds”, Journal of Engineering Design, 4(5), 339-351.3 Lee, R-S, Chen, Y-M, and Lee, C-Z (1997), “Developmentof a concurrent mould design system: a knowledge basedapproach”, Computer Integrated Manufacturing Systems,10(4), 287-307.4 Raviwongse, R. and Allada, V. (1997), “Artificial neuralnetwork based model for computation of injection mouldcomplexity”, International Journal of AdvancedManufacturing Technology, 13(8), 577-586.5 Kwong, C.K. and Smith, G.F. (1998), “A computationalsystem for process design of injection moulding: combining blackboard-based expert system and casebasedAdvanced Manufacturing Technology, 14(4), 239-246.6 Britton, G.A., Tor, S.B., et. al. (2001), “Modellingfunctional design information for injection mould design”,International Journal of Production Research, 39(12),2501-2515.7 Mok, C.K., Chin, K.S., and Ho, J.K.L. (2001), “Aninteractive knowledge-based CAD system for moulddesign in injection moulding processes”, InternationalJournal of Advanced Manufacturing Technology, 17(1),27-38.8 Ong, S.K. Prombanpong, S. and Lee, K.S. (1995), “Anobject-oriented approach to computer-aided design of aplastic injection mould”, Journal of IntelligentManufacturing, 6(1), 1-10.9 Irani, R.K. Kim, B.H. and Dixon, J.R. (1995), “Towardsautomated design of the feed system of injection mouldsby integrating CAE, iterative redesign and features”,Transactions ASME Journal Engineering for Industry,117(1), 72-77.10 Nee, A.Y.C., Fu, M.W. et. al., (1997), “Determination ofoptimal parting directions in plastic injection mould design”, Annals CIRP, 46(1), 429-432.11 Chen, L-L and Chou, S-Y (1995), “Partial visibility forselecting a parting direction in mould and die design”,Journal of Manufacturing Systems, 14(5), 319-330.12 Park, S.J. and Kwon, T.H. (1998), “Thermal and Designsensitivity analyses for cooling system of injection mould.Part 2:Design sensitivity analysis”, Transactions ASMEJournal Manufacturing Science & Engineering, 120(2),296-305.13 Lin, J.C. (2001), “Optimum gate design of freedominjection mould using the abductive network”, InternationalJournal of Advanced Manufacturing Technology, 17(4),297-304.14 Maher, M.L. et. al. (1996), “Developing Case-BasedReasoning for Structural Design”, Intelligent System & Their Applications, IEEE Expert, USA, June.15 The Haley Enterprise, Inc. (1994), “Documentation ofRETE+”.An Intelligent Cavity Layout Design System for Injection MouldsWeigang Hu and Syed Masood* Abstract - This paper presents the development of an Intelligent Cavity Layout Design System (ICLDS) for multiple cavityin jection moulds. The system is intended to assist mould designers in cavity layout design at concept design stage. Thecomp lexities and principles of cavity layout design as well as various dependencies in injection mould design are introduced. The knowledge in cavity layout design is summarized and classified. The functionality, the overall structure and general process of ICLDS are explained. The paper also discusses such issues as knowledge representation and case-based reasoning used in the development of the system. The functionality of the system is illustrated with an example of cavity layout design problem.Keywords: Intelligent design, cavity layout design, injection mould design, case-based reasoning, design support system1. Introduction In manufacturing, the injection moul ding is one of he most widely used production processes for producing plastic parts with high production rate and little or no finishing required on plastic products. The process consists of injecting molten plastic material from a hot chamber into a closed mould, allowing the plastic to cool and solidify and ejecting the finished product from the mould. For each new plastic product, the injection moul ding machine requires a new injection mould. Design and manufacture of injection mould is a time consuming and expensive process and traditionally requires highly skilled tool and mould makers. An injection mould consists of several components, which include mould base, cavities, guide pins, a sprue, runners, gates, cooling water channels, support plates, slides and ejector mechanism 1. Design of mould is also affected by several other factors such as part geometry, mould material, parting line and number of cavities per mould. With the advances in computer technology and artificial intelligence, efforts have been directed to reduce the cost and lead time in the design and manufacture of an injection mould. Injection mould design has been the main area of research since it is a complex processinvolving several sub-designs related tovari ous components of the mould, each requiring expert knowledge and experience. Mould design also affects the productivity ,mould maintenance cost, manufacturability of mould ,and the quality of the mould ed part. Most of the workin mould design has been directed to the application of expert systems, knowledge based systems and artificial intelligence to eliminate or supplement the vast amount of human expertise required in traditional design process. Kruth and Willems 2 developed an intelligent support system for the design of injection moulds integrating commercial CAD/CAM, a relational database and an expert system. Lee et. al. 3 proposed a systematic methodology and knowledge base for injection mould design in a concurrent engineering environment. Raviwongse and Allada 4 developed a neural networkbased design support tool to compute the mould complexity index to help mould designers to assess their proposed mould design on mould manufacturability. Kwong and Smith 5 developed a computational system for the process design of injection moulding based on the blackboard-based expert system and the case-based reasoning approach, which includes mould design, production scheduling, cost estimation and determination of injection moulding parameters. Britton et. al. 6discussed the injection mould design from a functional perspective using functional design knowledge and a number of knowledge libraries. Mok et. al. 7 developed an interactive knowledge-based CAD system for injection mould design incorporating computational, knowledgeand graphic modules. Several studies have also been made on improving the design of specific components of an injection mould. On get. al. 8 developed a knowledge-based and objectorientedapproach for the design of the feed system for injection moulds, which can efficiently design the type, location and size of a gating system in the mould. Iraniet. al. 9 also developed a software system for automatic design of gating and runner systems for injection moulds and provide evaluation of gating design based on specified performance parameters. Nee et. al. 10 proposed a methodology for determination of optimal parting directions in injection mould design based on automatic recognition and extraction of undercut features. Chen and Chou 11 developed algorithms for selecting a parting line in mould design by computing the undercut volumes and minimising the number of undercuts. Park and Kwon 12 worked on the design of cooling systems in injection moulds and proposed an optimal design based on thermal analysis and design sensitivity analysis of the cooling stage of the injection moulding process. Lin 13 worked on the use of gate size and gate position as the major parameters for simulated injection mould performance prediction. One area in injection mould design, which hasreceived little attention, is the design of cavity layout in a multiple cavity injection mould. Cavity layout design affects the whole process of injection moulding directly, since it is one of the most important phases in mould design process. Consideration of cavity layout design in injection mould at concept design stage will improve the quality of injection moulded products because it is associated with the determination of many key factors affecting the design and quality of mould. Such factors include number of cavities; parting line; type of mould; type and position of gate; runner system; cooling system and ejection system. Some of these factors are difficult to build as true mathematical models for analysis and design. This paper presents the development of a design support system, called Intelligent Cavity Layout Design System (ICLDS), for multiple-cavity injection moulds based on knowledge based and object oriented approaches. It uses the case-based and ruled-based reasoning in arriving at the layout solution 14. It is based on the commercial software system named “RETE+”, which is an integrated development platform for customers to develop their own knowledge-based systems 15. The objective is to make full use of available techniques in artificial intelligence in assisting mould designers at concept design stage.2. Cavity Layout Design in Injection Moulds Current practice for injection mould design, especially cavity layout design, depends largely on designers experiences and knowledge. It would therefore be desirable to use knowledge engineering, artificial intelligence and intelligent design techniques in generating an acceptable cavity layout design in injection mould accurately and efficiently. In mould design, most of patterns of cavity layout and rules and principles of cavity layout design can also be easily represented in the form of knowledge, which can be used in most of knowledge-based design systems. For example, for the layout patterns shown in Fig. 1, the criteria to select the suitable layout pattern for design are mainly dependent on working environments, conditions and requirements of customer and are mainly based on designers skill and experience. To make a choice of contradictory factors will rely obviously on designers knowledge and experiences. It is rather suitable for intelligent design techniques to be used in systems designed for such situations, especially for routine or innovation design. Design of injection mould mainly involves consideration of design of the following elements or sub-systems:(1) mould type(2) number of cavities(3) cavity layout(4) runner system(5) ejector system(6) cooling system(7) venting(8) mounting mechanism Most of the elements are inter-dependent such that itis virtually impossible to produce a meaningful flowchart covering the whole mould design process. Someof the design activities form a complicated design network as shown in Fig. 2.Obviously, in injection mould design, it is difficult for designer to monitor all design parameters. Cavity design and layout directly affects most of other activities. The application of advanced knowledge based techniques to assist designer in cavity layout design at concept design stage will greatly assist in the development of a comprehensive computer-aided injection mould design and manufacturing system. It is noted from Fig. 1 that a number of different layout patterns are possible with multiple cavities inside a mould. Higher the number of cavities of mould, higher the productivity of the injection mould. But this may lead to difficulties with issues such as balancing the runners or products with the complicated cavity shapes, which in turn may lead to problems of mould manufacturability. It is also possible that the number of cavities and the pattern of cavity layout will influence the determination of parting line, type of gate, position of gate, runner system and cooling system. Most of the main activities of mould design are therefore linked to cavity layout design. Fig. 3 shows the relations between cavity layout design and other design activities. The cavity layout design problem therefore depends upon a number of functionalities of the overall mould design system, which includes:(1) definition of design specifications including analysis and description of characteristics of design problem(2) determination of mould type(3) determination of number of cavities(4) determination of orientation of product(5) determination of runner type and runner configuration(6) determination of type and position of gate(7) cavity layout conceptual design(8) evaluation of ejection ability, manufacturingability and economic performances(9) determination of cooling system(10) graphic results display and output3. Structure of ICLDS and the Design Process The structure of the Intelligent Cavity Layout Design System (ICLDS) is based on case-based reasoning and ruled-based reasoning designed around the RETE+software system. Fig. 4 shows the overall structure of ICLDS schematically. Fig. 5 shows the general design process of ICLDS. The design process starts with the definition of design specifications. The ICLDS system retrieves similar cases from case base by computing the similarity between the cases and the new case. If the solution is satisfactory, then results are displayed graphically. If the solution is not satisfactory, then ICLDS will use rule-based reasoning with forward or backward chaining or a mixture of both to arrive at a solution. If the solution is still unsatisfactory, then the user has to modify some of the initial design specifications. The use of case-based technology in the design process in ICLDS allows the user to obtain the solution(s) of design problem more quickly and flexibly. The structure of knowledge base and database used in the development of ICLDS is based on the underlying knowledge base and database structure from the RETE+ software system, which is a commercially available software development platform.4. Development of ICLDS4.1. Classifications of Knowledge For various logic and steps involved in layout design, there are different kinds of knowledge that needs to be described and represented in cavity layout design. The types of knowledge can be classified into five kinds based on object oriented (OO) concept as described below:(1) Design instance/case: previous design cases and current design instances(2) Relation: superclass-class-subclass relation, classin stance relation(3) Attribute: design variables, features, attributes of design problem(4) Rule: general design rules, design experiences(5) Procedure and/or model: numeric calculation, mathematical modeling, analysis, evaluation and procedures.4.2. Knowledge Representations To describe each of these types of knowledge, the internal data structures of the ECLIPSE language, included in RETE+ inherently, can be used to make the object orientated representation of the design process as explained earlier.4.3. Case-based Reasoning Case-Based Reasoning (CBR) is dependent firstly on case retrieved. Case-based retrieval is based on “Similarity Metric”. Therefore, how to calculate the similarity is obviously the key technique in CBR, and it is described in detail as below. which, since dij must range between 0 and 1, must also range between 0 and 1. which, since Wj and dij must range between 0 and 1, must also range between 0 and 1.4.4. Validation of Case Validation of case is to check up whether each acceptable case is suitable for current problem and to find out the most suitable one, so each case should be associated with testing methods and tested results on it. Only the case, under the given conditions, for which all tested results on it match those of the current design problem, can be considered as the solution prototype for further refining.4.5. Criteria for Validity of Cost Reduction With the application of ICLDS for cavity layout, two kinds of cost reduction can be expected. One is the overall theoretical cost reduction achieved in using the system to carry out the concept
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