【正文】 2 60 工件比例 小 5 60 工件重量 輕 5 60 工件剛度 硬度強(qiáng) 1 60 加工內(nèi)容 孔 3 80 程序要求 完成加工 3 70 定位方法 三個平面 1 100 夾緊方法 不確定 ？ 90 夾具體 復(fù)合 4 80 其他 沒有 0 60 通過查找和計(jì)算相似點(diǎn)，最相似的事例的事例索引碼是19325513321402000，細(xì)節(jié)信息在表2中列出。 表2 最相似事例的事例索引碼特征名稱 特性值 索引碼夾具類型 車床夾具 1 工件形狀 塊狀 9 工件材料 中碳鋼 3 批量 中批 2 工件比例 小 5 工件重量 輕 5 工件剛度 硬度強(qiáng) 1 加工內(nèi)容 孔 3 程序要求 完成加工 3 定位方法 三個平面 1 夾緊方法 不確定 ？ 夾具體 復(fù)合 4 其他 沒有 0 相似點(diǎn)的計(jì)算如下： ，這是在事例庫中用于設(shè)計(jì)的最相似的事例，最相似的事例的結(jié)構(gòu)如圖4所示圖4 最相似的夾具當(dāng)成分替代，修改定位模型和夾緊模型，以及調(diào)節(jié)相關(guān)尺寸之后，新的夾具被設(shè)計(jì)出來，圖形如圖6所示 圖5 需要設(shè)計(jì)的新夾具因?yàn)樵谑吕龓熘袥]有相似夾具，新夾具被儲存到事例庫中。事例索引碼是19325523311402000。6 結(jié)論 基于事例推理，作為一個問題解決的方法，是一個比模仿人類思想的專業(yè)系統(tǒng)更有效的方法，已經(jīng)在很多難獲取知識的領(lǐng)域里得到發(fā)展?；谑吕评淼膬?yōu)點(diǎn)如下：它和人類的思想很相似；一個事例庫通過保存新事例獲得自學(xué)能力，它比有慣例庫更快更容易，它可以更好的傳遞和解釋新的知識，這和慣例庫有很大的不同?；谑吕评碇刑岢龅囊粋€夾具設(shè)計(jì)的框架已經(jīng)被實(shí)行了，使用的是支持基礎(chǔ)數(shù)據(jù)的VC++，UG電腦繪圖軟件。這個框架也已經(jīng)和普通成分庫和典型夾具庫結(jié)合起來。這個發(fā)展的標(biāo)準(zhǔn)系統(tǒng)，用于航空項(xiàng)目，幫助夾具設(shè)計(jì)者提高設(shè)計(jì)效率和重新使用先前的設(shè)計(jì)資源。Application and developmentOf 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 puter aided fixture design system is created on case based reasoning (CBR),in which the attributes of the main features of work piece 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 indent 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。 puter aided design(CAD) Fixtures are devices that serve as the purpose of holding the work piece 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 plicated process, based on experience that needs prehensive qualitative knowledge about a number of design issues including work piece configuration, manufacturing processes involved, and machining environment. This is also a very time consuming work when using traditional CAD tools (such as Epigraphic, 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