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編號
無錫太湖學(xué)院
畢業(yè)設(shè)計（論文）
相關(guān)資料
題目： J5600調(diào)溫器工藝規(guī)程設(shè)計和
系列夾具設(shè)計
信機 系 機械工程及其自動化 專業(yè)
學(xué) 號： 0923808
學(xué)生姓名： 張 燕
指導(dǎo)教師： 張大駿 （職稱：高級工程師 ）
（職稱： ）
2013年5月25日
目 錄
一、畢業(yè)設(shè)計（論文）開題報告
二、畢業(yè)設(shè)計（論文）外文資料翻譯及原文
三、學(xué)生“畢業(yè)論文（論文）計劃、進度、檢查及落實表”
四、實習鑒定表
無錫太湖學(xué)院
畢業(yè)設(shè)計（論文）
開題報告
題目： J5600調(diào)溫器工藝規(guī)程設(shè)計和
系列夾具設(shè)計
信機系 機械工程及其自動化 專業(yè)
學(xué) 號： 0923808
學(xué)生姓名： 張 燕
指導(dǎo)教師： 張大駿 （職稱：高級工程師 ）
（職稱： ）
2012年11月25日
課題來源
本課題是廣西玉林柴油機廠委托無錫市宏業(yè)機械配件廠加工的柴油機零件，此種發(fā)動機在載重汽車及客車上廣泛使用。
科學(xué)依據(jù)（包括課題的科學(xué)意義；國內(nèi)外研究概況、水平和發(fā)展趨勢；應(yīng)用前景等）
（1）課題科學(xué)意義
調(diào)溫器研究報告主要是通過對調(diào)溫器的主要內(nèi)容和配套條件，如市場調(diào)查、資源供應(yīng)、建設(shè)規(guī)模、工藝路線、設(shè)備選型、環(huán)境影響、資金籌措、盈利能力等，從技術(shù) 、經(jīng)濟、工程等方面進行調(diào)查研究和分析比較，并對項目建成以后可能取得的財務(wù)、經(jīng)濟效益及社會影響進行預(yù)測，從而提出該調(diào)溫器項目是否值得投資和如何進行建設(shè)的咨詢意見，為項目決策提供依據(jù)的一種綜合性的分析方法?？尚行匝芯烤哂蓄A(yù)見性、公正性、可靠性、科學(xué)性的特點。調(diào)溫器研究報告是確定建設(shè)項目前具有決定性意義的工作，是在調(diào)溫器投資決策之前，對擬建項目進行全面技術(shù)經(jīng)濟分析論證的科學(xué)方法，在投資管理中，可行性研究是指對擬建項目有關(guān)的自然、社會、經(jīng)濟、技術(shù)等進行調(diào)研、分析比較以及預(yù)測建成后的社會經(jīng)濟效益。
（2）J5600調(diào)溫器的研究狀況及其發(fā)展前景
調(diào)溫器行業(yè)趨勢研究報告是通過對影響調(diào)溫器行業(yè)市場運行的諸多因素所進行的調(diào)查分析，掌握調(diào)溫器行業(yè)市場運行規(guī)律，從而對調(diào)溫器行業(yè)的未來的發(fā)展趨勢特點、市場容量、競爭趨勢、細分下游市場需求趨勢等進行預(yù)測。
調(diào)溫器行業(yè)趨勢研究報告主要分析要點包括：
1） 調(diào)溫器行業(yè)發(fā)展趨勢特點分析。通過對調(diào)溫器行業(yè)發(fā)展影響因素分析，總結(jié)出未來調(diào)溫器行業(yè)總體運行趨勢特點；
2） 預(yù)測調(diào)溫器行業(yè)生產(chǎn)發(fā)展及其變化趨勢。對生產(chǎn)發(fā)展及其變化趨勢的預(yù)測，這是對市場中商品供給量及其變化趨勢的預(yù)測；
3） 預(yù)測調(diào)溫器行業(yè)市場容量及變化。綜合分析預(yù)測期內(nèi)調(diào)溫器行業(yè)生產(chǎn)技術(shù)、產(chǎn)品結(jié)構(gòu)的調(diào)整，預(yù)測調(diào)溫器行業(yè)的需求結(jié)構(gòu)、數(shù)量及其變化趨勢。
4）預(yù)測調(diào)溫器行業(yè)市場價格的變化。企業(yè)生產(chǎn)中投入品的價格和產(chǎn)品的銷售價格直接關(guān)系到企業(yè)盈利水平。在商品價格的預(yù)測中，要充分研究勞動生產(chǎn)率、生產(chǎn)成本、利潤的變化，市場供求關(guān)系的發(fā)展趨勢，貨幣價值和貨幣流通量變化以及國家經(jīng)濟政策對商品價格的影響。
調(diào)溫器行業(yè)趨勢研究報告主要依據(jù)了國家統(tǒng)計局、國家海關(guān)總署、國家發(fā)改委、國家商務(wù)部、國家工業(yè)和信息化部、行業(yè)協(xié)會、國內(nèi)外相關(guān)刊物雜志等的基礎(chǔ)信息，結(jié)合調(diào)溫器行業(yè)歷年供需關(guān)系變化規(guī)律，對調(diào)溫器行業(yè)內(nèi)的企業(yè)群體進行了深入的調(diào)查與研究，對調(diào)溫器行業(yè)環(huán)境、調(diào)溫器市場供需、調(diào)溫器行業(yè)經(jīng)濟運行、調(diào)溫器市場格局、調(diào)溫器生產(chǎn)企業(yè)等的詳盡分析。在對以上分析的基礎(chǔ)上，對調(diào)溫器行業(yè)未來發(fā)展趨勢和市場前景進行科學(xué)、嚴謹?shù)姆治雠c預(yù)測。
研究內(nèi)容
1、機械加工工藝規(guī)程的編制，結(jié)合具體工廠的條件和發(fā)展前景進行考慮。
2、同樣結(jié)合具體工廠的現(xiàn)有生產(chǎn)條件和發(fā)展前景設(shè)計專用（不少于三副）。
擬采取的研究方法、技術(shù)路線、實驗方案及可行性分析
采用組織分析零件的具體結(jié)構(gòu)，加工精度要求，表面粗糙度要求，制造出初步的加工方案。然后組織學(xué)生下廠參觀，實習，實地了解工廠現(xiàn)有的生產(chǎn)條件，發(fā)展展望及具體的生產(chǎn)水平。在此基礎(chǔ)上編制工藝規(guī)程，填寫工藝文件，設(shè)計專用夾具。待初步完成后再回工廠征集意見，加以改進，定稿。
研究計劃及預(yù)期成果
研究計劃：
2012年11月12日-2012年12月2日：按照任務(wù)書要求查閱論文相關(guān)參考資料，填寫畢業(yè)設(shè)計開題報告書。
2012年12月3日-2013年1月20日：指導(dǎo)專業(yè)實訓(xùn)。
2013年1月21日-2013年3月1日：指導(dǎo)畢業(yè)實習。
2013年3月4日-2013年3月8日：填寫實習報告。
2013年3月9日-2013年3月17日：學(xué)習并翻譯一篇與畢業(yè)設(shè)計相關(guān)的英文材料。
2013年3月25日-2013年4月28日：工藝規(guī)程設(shè)計、工序卡和工藝卡。
2013年4月29日-2013年5月15日：夾具設(shè)計、裝配圖和說明書。
2013年5月16日-2013年5月25日：畢業(yè)論文撰寫和修改工作。
預(yù)期成果：
工藝規(guī)程：工藝卡片，工序卡片，夾具總圖及主要零件圖，設(shè)計說明書
特色或創(chuàng)新之處
工藝規(guī)程可以適用于一般中小型工廠的普通通用機床，也能改進后用于專用機床，或加工中心，適用于范圍較廣。
已具備的條件和尚需解決的問題
現(xiàn)有廣西玉柴機器的生產(chǎn)圖樣，委托加工工廠的現(xiàn)有生產(chǎn)條件及技術(shù)狀況，特別是已有的生產(chǎn)經(jīng)驗。
目前缺少設(shè)計手冊、資料等，對檢測條件也不夠清楚其它資料也缺乏。
指導(dǎo)教師意見
指導(dǎo)教師簽名：
年 月 日
教研室（學(xué)科組、研究所）意見
教研室主任簽名：
年 月 日
系意見
主管領(lǐng)導(dǎo)簽名：
年 月 日
無錫太湖學(xué)院
畢業(yè)設(shè)計（論文）外文資料翻譯
信機 系 機械工程及自動化 專業(yè)
院 （系）： 信 機 系
專 業(yè)： 機械工程及自動化
班 級： 機械97班
姓 名： 張 燕
學(xué) 號： 0923808
外文出處： 機械專業(yè)英語教程
附 件： 1.譯文；2.原文；3.評分表
2013年3月17日
英文原文
Application and development
Of case based reasoning in fixture design
Abstract: Based on the case based designing (CBD) methodology, the fixture similarity is in two respects: the function and the structure information. Then, the computer aided fixture design system is created on case based reasoning (CBR),in which the attributes of the main features of workpiece and structure of fixture as case index code are designed for the retrieve of the similar cases, and the structure and hierarchical relation of case library are set up for store. Meanwhile, the algorithm based on the knowledge guided in the retrieve of the similar cases, the strategy of case adapt at ion and case storage in which the case ident if cat ion number is used to distinguish from similar cases are presented. The application of the system in some projects improves the design efficiency and gets a good result .
Keywords: case based reasoning ;fixture design; computer aided design(CAD)
Fixtures are devices that serve as the purpose of holding the workpiece securely and accurately, and maintaining a consistent relationship with respect to the tools while machining. Because the fixture structure depends on the feature of the product and the status of the process planning in the enterprise, its design is the bottleneck during manufacturing, which restrains to improve the efficiency and leadtime. And fixture design is a complicated process, based on experience that needs comprehensive qualitative knowledge about a number of design issues including workpiece configuration, manufacturing processes involved, and machining environment. This is also a very time consuming work when using traditional CAD tools (such as Unigraphics, CATIA or Pro/E), which are good at performing detailed design tasks, but provide few benefits for taking advantage of the previous design experience and resources, which are precisely the key factors in improving the efficiency. The methodology of case based reasoning (CBR) adapts the solution of a previously solved case to build a solution for a new problem with the following four steps: retrieve, reuse, revise, and retain [1]. This is a more useful method than the use of an expert system to simulate human thought because proposing a similar case and applying a few modifications seems to be self explanatory and more intuitive to humans .So various case based design support tools have been developed for numerous areas[2-4], such as in injection molding and design, architectural design, die casting die design, process planning, and also in fixture design. Sun used six digitals to compose the index code that included workpiece shape, machine portion, bushing, the 1st locating device, the 2nd locating device and clamping device[5]. But the system cannot be used for other fixture types except for drill fixtures, and cannot solve the problem of storage of the same index code that needs to be retained, which is very important in CBR[6].
1 Construction of a Case Index and Case Library
1.1 Case index
The case index should be composed of all features of the workpiece, which are distinguished from different fixtures. Using all of them would make the operation in convenient. Because the forms of the parts are diverse, and the technology requirements of manufacture in the enterprise also develop continuously, lots of features used as the case index will make the search rate slow, and the main feature unimportant, for the reason that the relative weight which is allotted to every feature must diminish. And on the other hand, it is hard to include all the features in the case index.
Therefore, considering the practicality and the demand of rapid design, the case index includes both the major feature of the workpiece and the structure of fixture. The case index code is made up of 16 digits: 13 digits for case features and 3 digits for case identification number.
The first 13 digits represent 13 features. Each digit is corresponding to an attribute of the feature, which may be one of“*”, “?”, “1”, “2”,…,“A”,“B”,…, “Z”,…, etc. In which, “*” means anyone, “?” uncertain, “0” nothing.
The system rules: fixture type, workpiece shape, locating model cannot be “*”or“?”. When the system is designed, the attribute information of the three items does not have these options, which means the certain attribute must be selected.
The last three digits are the case identification number, which means the 13 digits of the case feature are the same, and the number of these three digits is used for distinguishing them.
The system also rules: “000” is a prototype case, which is used for retrieval, and other cases are “001”,“002”,…, which are used for reference cases to be searched by designers. If occasionally one of them needs to be changed as the prototype case, first it must be required to apply to change the one to “000”, and the former is changed to referential case automatically.
The construction of the case index code is shown in Fig.1.
1.2 Case library
The case library consists of lots of predefined cases. Case representation is one of the most important issues in case based reasoning. So compounding with the index code,.
1.3 Hierarchical form of Case
The structure similarity of the fixture is represented as the whole fixture similarity, components similarity and component similarity. So the whole fixture case library, components case library, component case library of fixture are formed correspondingly. Usually design information of the whole fixture is composed of workpiece information and workpiece procedure information, which represent the fixture satisfying the specifically designing function demand. The whole fixture case is made up of function components, which are described by the function components’ names and numbers. The components case represents the members. (function component and other structure components,main driven parameter, the number, and their constrain relations.) The component case (the lowest layer of the fixture) is the structure of function component and other components. In the modern fixture design there are lots of parametric standard parts and common non standard parts. So the component case library should record the specification parameter and the way in which it keeps them.
2 Strategy of Case Retrieval
In the case based design of fixtures ,the most important thing is the retrieval of the similarity, which can help to obtain the most similar case, and to cut down the time of adaptation. According to the requirement of fixture design, the strategy of case retrieval combines the way of the nearest neighbor and knowledge guided. That is, first search on depth, then on breadth; the knowledge guided strategy means to search on the knowledge rule from root to the object, which is firstly searched by the fixture type, then by the shape of the workpiece, thirdly by the locating method. For example, if the case index code includes the milling fixture of fixture type, the search is just for all milling fixtures, then for box of workpiece shape, the third for 1plane+ 2pine of locating method. If there is no match of it, then the search stops on depth, and returns to the upper layer, and retrieves all the relative cases on breadth.
Retrieval algorithms:
1) According to the case index information of fixture case library, search the relevant case library;
2) Match the case index code with the code of each case of the case library, and calculate the value of the similarity measure;
3) Sort the order of similarity measure, the biggest value, which is the most analogical case.
Similarity between two cases is based on the similarity between the two cases. features. The calculation of similarity measure depends on the type of the feature. The value of similarity can be calculated for numerical values, for example, compareWorkpiece with the weight of 50kg and 20kg. The value can also be calculated between non numerical values, for example, now the first 13 digits index code is all non numerical values. The similarity measure of a fixture is calculated as follows:
where S is the similarity measure of current fixture, n is the number of the index feature, is the weight of each feature, is the similarity measure of the attribute of the i2th feature with the attributeof relative feature of the j-th case in the case library. At the same time, , the value counts as follows:
.
Where is the value of the index attribute of the i-th feature, and is the value of attribute of the relative i-th feature of the j-th case in case library.
So there are two methods to select the analogical fixture. One is to set the value. If the values of similarity measure of current cases were less than a given value, those cases would not be selected as analogical cases. When the case library is initially set up, and there are only a few cases, the value can be set smaller. If there are lots of analogical cases, the value should get larger. The other is just to set the number of the analogical cases (such as10), which is the largest value of similarity measure from the sorted order.
3 Case adaptation and Case Storage
3.1 Case adaptation
The modification of the analogical case in the fixture design includes the following three cases:
1) The substitution of components and the component;
2) Adjusting the dimension of components and the component while the form remains;
3) The redesign of the model.
If the components and component of the fixture are common objects, they can be edited, substituted and deleted with tools, which have been designed.
3.2 Case storage
Before saving a new fixture case in the case library, the designer must consider whether the saving is valuable. If the case does not increase the knowledge of the system, it is not necessary to store it in the case library. If it is valuable, then the designer must analyze it before saving it to see whether the case is stored as a prototype case or as reference case. A prototype case is a representation that can describe the main features of a case family. A case family consists of those cases whose index codes have the same first 13 digits and different last three digits in the case library. The last three digits of a prototype case are always “000”. A reference case belongs to the same family as the prototype case and is distinguished by the different last three digits.
From the concept that has been explained, the following strategies are adopted:
1) If a new case matches any existing case family, it has the same first 13 digits as an existing prototype case, so the case is not saved because it is represented well by the prototype case. Or is just saved as a reference case (the last 3 digits are not “000”, and not the same with others) in the case library.
2) If a new case matches any existing case family and is thought to be better at representing this case family than the previous prototype case, then the prototype case is substituted by this new case, and the previous prototype case is saved as a reference case.
3) If a new case does not match any existing case family, a new case family will be generated automatically and the case is stored as the prototype case in the case library.
4 Process of CBR in Fixture Design
According to the characteristics of fixture design, the basic information of the fixture design such as the name of fixture, part, product and the designer, etc. must be input first. Then the fixture file is set up automatically, in which all components of the fixture are put together. Then the model of the workpiece is input or designed. The detailed information about the workpiece is input, the case index code is set up, and then the CBR begins to search the analogical cases, relying on the similarity measure, and the most analogical case is selected out. If needed, the case is adapted to satisfy the current design, and restored into the case library. The flowchart of the process is shown in Fig.3.
5 Illustrating for Fixture Design by CBR
This is a workpiece (seeFig.4). Its material is 45# steel. Its name is seat. Its shape is block, and the product batch size is middle, etc. A fixture is turning fixture that serves to turn the hole, which needs to be designed.
The value of feature, attribute, case index code and weight of the workpiece is show n in Tab.2.
Through searching, and calculating the similarity, the case index code of the most similar case is 19325513321402000, and the detailed information is show n in Tab. 3.
The similarity is calculated as follows:
So the value of similarity measure of the fixture which needs to be designed with the most analogical case in case library is 0.806, and the structure of the most analogical case is shown in Fig.5.
After having been substituted the component, modified the locating model and clamp model, and adjusted the relative dimension, the new fixture is designed, and the figure is show n in Fig.6.
As there is not the analogical fixture in the case library, the new fixture is restored in to the case library. The case index code is 19325513311402000.
6 Conclusion
CBR, as a problem solving methodology, is a more efficient method than an expert system to simulate human thought, and has been developed in many domains where knowledge is difficult to acquire. The advantages of the CBR are as follows: it resembles human thought more closely; the building of a case library which has self learning ability by saving new cases is easier and faster than the building of a rule library; and it supports a better transfer and explanation of new knowledge that is more different than the rule library. A proposed fixture design framework on the CBR has been implemented by using Visual C ++, UG/Open API in U n graphics with Oracle as database support, which also has been integrated with the 32D parametric common component library, common components library and typical fixture library. The prototype system, developed here, is used for the aviation project, and aids the fixture designers to improve the design efficiency and reuse previous design resources.
中文譯文
基于事例推理的夾具設(shè)計研究與應(yīng)用
摘要:根據(jù)基于事例的設(shè)計方法,提出采用工序件的特征信息和夾具的結(jié)構(gòu)特征信息來描述夾具的相似性,并建立了包括這2方面主要特征信息為基礎(chǔ)的事例索引碼,設(shè)計了事例庫的結(jié)構(gòu)形式,創(chuàng)建了層次化的事例組織方式；同時,提出了基于知識引導(dǎo)的夾具事例檢索算法,以及事例的修改和采用同族事例碼進行相似事例的存貯,形成了基于事例推理的夾具設(shè)計。所開發(fā)的原型系統(tǒng)在型號工程夾具設(shè)計等項目的設(shè)計過程中得到了應(yīng)用,并取得了令人滿意的使用效果。
關(guān)鍵詞: 基于事例的推理 夾具設(shè)計 CAD
夾具是以確定工件安全定位準確為目的的裝置，并在加工過程中保持工件與刀具或機床的位置一致不變。因為夾具的結(jié)構(gòu)依賴于產(chǎn)品的特點和在企業(yè)規(guī)劃中加工工序的地位,所以它的設(shè)計是制造過程中的瓶頸,制約著效率的提高。 夾具設(shè)計是一個復(fù)雜的過程,需要有從大量的設(shè)計論文中了解質(zhì)量知識的經(jīng)驗，這些設(shè)計論文包括工件的結(jié)構(gòu)設(shè)計、涉及加工工藝，和加工環(huán)境。當用這些擅長繪制詳細設(shè)計圖的傳統(tǒng)的CAD工具（如Unigraphics、CATIA、Pro/E)時,這仍然是一項非常耗時的工作，但是利用以往的設(shè)計經(jīng)驗和資源也不能提供一些益處,而這正是提高效率的關(guān)鍵因素。 基于事例推理 (CBR) 的方法適應(yīng)以往個案解決的辦法,建立一個新問題的方法,主要有以下四步驟：檢索、利用、修改,并保留。這是一個比用專業(yè)系統(tǒng)模仿人類思維有用的使用方法，因為提出一個類似的情況,和采用一些修改,似乎不言自明,而且比人類更直觀。所以支持不同事例的設(shè)計工具已經(jīng)在諸多領(lǐng)域中發(fā)展起來，如在注射成型及設(shè)計、建筑設(shè)計、模具設(shè)計投死, 規(guī)劃過程中,還有夾具設(shè)計。 孫用六個數(shù)字組成代碼參數(shù),包括工件的形狀、機械部分、軸襯,第一定位裝置,第二定位裝置和夾緊裝置。 但這個系統(tǒng)不能用于除鉆床夾具外的其他夾具類型,不能解決儲存需要保留的同一參數(shù)代碼的問題,這在CBR中是非常重要的。
1 事例參數(shù)和事例圖書館的建立
1.1 事例參數(shù)
事例參數(shù)應(yīng)該由工件的所有的特征組成，來區(qū)別不同的夾具。 使用他們能夠使操作方便. 因為零件的形狀是多種多樣的, 在生產(chǎn)企業(yè)中制造的技術(shù)要求也不斷發(fā)展,許多特征作被用做事例參數(shù)將會使搜索速度降低,其主要特征是不重要的,因為分配給每個特征的比重必須減少。 另一方面,事例參數(shù)包含所有的特征是困難的。
因此,考慮到實際和快速設(shè)計的需求,事例參數(shù)要包含工件的主要特征和夾具的結(jié)構(gòu)。事例參數(shù)代碼由16位數(shù)組成：13位數(shù)是事例特征3位數(shù)是事例識別數(shù)字。
前13位數(shù)代表13個特征。 每個數(shù)字與特征的一個屬性相一致,這可能是"*"、"?"、"1"、"2"，…，"A"、"B"，…，"Z"，…，等其中的一個。其中，"*"是指任何一個,"?"代表不確定,"0"代表沒有。
系統(tǒng)規(guī)定:夾具的類型，工件的形狀，位置模式不能是"*"和"?"。在設(shè)計系統(tǒng)時,三個項目的屬性信息沒有這些選擇,這就意味著必須選擇確定的屬性。
最后三位數(shù)是事例識別號碼,如果事例特征的13位數(shù)是一樣的,這三個數(shù)字就用來區(qū)別他們。
該系統(tǒng)還規(guī)定:"000"是用于修正的一個典型事例,其他事例"001"、"002"、…,這些是用于設(shè)計師查找參考事例的。 如果其中一個偶爾需要改變成典型事例,首先它必須要求改成"000",前面的自動變成參考事例。
事例索引碼的結(jié)構(gòu)如圖1所示。
1—夾具類型； 6—工件重量； 11—夾緊模型；
2—工件形狀； 7—工件剛度； 12—夾具體；
3—工件材料； 8—加工內(nèi)容； 13—其他；
4—批 量； 9—過程所有物； 14到16—事例識別碼；
5—工件比例； 10—定位模型；
圖1 事例索引碼的結(jié)構(gòu)
1.2 事例庫
事例庫由許多預(yù)定義的事例組成。事例的描述是基于事例推理的最重要的問題之一。所以由索引碼復(fù)合。
1.3 事例的層次化
夾具的結(jié)構(gòu)相似被認為是整個夾具，成分和內(nèi)容相似。所以，整個夾具事例庫，成分事例庫，夾具的成分事例庫形成相同。整個夾具的設(shè)計資料通常是由工件資料和工件加工資料組成,這就意味著夾具的設(shè)計應(yīng)滿足特別功能的需求。全部夾具事例是由功能成分組成，它是用功能成分的名字和數(shù)字來進行描述的。成分事例代表成員（成分功能和其他結(jié)構(gòu)成分，主要驅(qū)動參數(shù)，數(shù)字，和它們的約束關(guān)系）。成分事例（夾具的最低層）是功能成分和和其他成分的結(jié)構(gòu)。在現(xiàn)代夾具設(shè)計中有很多參數(shù)化準件和普通非標準件。所以成分事例圖書館應(yīng)記錄特殊參數(shù)和保持它們的方法。
2 事例修改的策略
在基于事例的夾具設(shè)計中，最重要的是相似點的修改，這樣能有助于獲得最相似的事例，以及縮短適應(yīng)時間。根據(jù)夾具設(shè)計的需求，事例修改的策略使最接近的事例方法和知識指導(dǎo)結(jié)合起來。首先在深度上查找，然后在寬度上；知識指導(dǎo)策略意味著在來自客觀事物根源的知識規(guī)則上查找，這就要首先查找固定類型，然后查找工件的形狀，第三查找定位方法。例如，如果事例索引碼包括夾具類型的磨削夾具，就只查找所有的磨削夾具，然后查找工件形狀的盒子，第三查找一個平面兩個銷的定位方法。如果沒有合適的，就查找深度標點，然后回到最上層，然后再找所有與寬度相關(guān)的事例。
修改方法：
1) 根據(jù)夾具事例庫的事例索引信息，查找有關(guān)事例庫。
2) 將事例索引碼與事例庫的每個事例碼匹配，然后計算相似尺寸的價值。
3) 整理相似尺寸的次序，最大的架子是最類似的事例。
兩個事例之間的相似點是基于兩個事例特征之間的相似點。相似點尺寸的計算依靠特征的類型。相似點的價值可以通過數(shù)字化的價值來計算，例如比較重量分別是50kg 和 20kg的工件。非數(shù)字化的價值也能計算，例如，現(xiàn)在前13位索引碼都是非數(shù)字化的價值。一個夾具的相似尺寸的計算公式如下：
其中S表示通用夾具的相似尺寸，n表示索引特性數(shù)，表示每個特性的重量，表示事例庫中特性和相關(guān)夾具的特性的相似尺寸。同時， ，數(shù)值計算如下：