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黃河科技學(xué)院本科畢業(yè)設(shè)計（論文）任務(wù)書
工 學(xué)院 機(jī)械 系 機(jī)械設(shè)計制造及其自動化 專業(yè) 08 級 1 班
學(xué) 號 080105032 學(xué)生 杜騰飛 指導(dǎo)教師 閆存富
畢業(yè)設(shè)計（論文）題目
MJ—50型數(shù)控車床電動刀架設(shè)計
畢業(yè)設(shè)計（論文）工作內(nèi)容與基本要求（目標(biāo)、任務(wù)、途徑、方法，應(yīng)掌握的原始資料（數(shù)據(jù)）、參考資料（文獻(xiàn)）以及設(shè)計技術(shù)要求、注意事項(xiàng)等）（紙張不夠可加頁）
一、設(shè)計技術(shù)要求、原始資料（數(shù)據(jù)）、參考資料（文獻(xiàn)）
1、設(shè)計要求：主要是電動刀架整體的結(jié)構(gòu)設(shè)計，以結(jié)構(gòu)設(shè)計和關(guān)鍵零部件設(shè)計為主線，以理論計算及計算機(jī)輔助設(shè)計為輔的綜合性題目。
2、參考文獻(xiàn)：數(shù)控機(jī)床構(gòu)造，機(jī)械設(shè)計,金屬工藝學(xué)及熱處理、機(jī)械設(shè)計手冊、機(jī)械工程手冊等資料。
二、設(shè)計目標(biāo)與任務(wù)
1、查閱文獻(xiàn)資料不少于12篇，其中外文資料不少于2篇；編寫文獻(xiàn)綜述（不少于3000字）。
2、翻譯外文科技資料，不少于3000字。
3. 完成開題報告。
4、完成電動刀架系統(tǒng)總體結(jié)構(gòu)設(shè)計，繪制裝配圖、部件圖和零件圖，折合A1圖紙3張以上。
5、編寫設(shè)計說明書，不少于8000漢字。
三、時間安排
1——3周 完成開題報告、文獻(xiàn)翻譯、文獻(xiàn)綜述等
4——11周 完成總體設(shè)計、撰寫說明書等
12——13周 修改論文、資格審查等
14周 畢業(yè)答辯
畢業(yè)設(shè)計（論文）時間： 2012 年 2 月 13 日至 2012 年 5 月 15 日
計 劃 答 辯 時 間： 2012 年 5 月 19 日
專業(yè)（教研室）審批意見：
審批人簽名：
黃河科技學(xué)院畢業(yè)設(shè)計(文獻(xiàn)翻譯 ) 第9 頁
集成制造單元面向多產(chǎn)品類型的形成
和多樣化批量生產(chǎn)技術(shù)
摘要：追求的類型和不同多產(chǎn)品體積(MPTVV)生產(chǎn)快速反應(yīng)、快速的切換，使結(jié)構(gòu)線的轉(zhuǎn)移制造系統(tǒng)不再是一成不變的。細(xì)胞形成(CF)算法的關(guān)鍵技術(shù)是細(xì)胞制造系統(tǒng)(CMS)。目前，CF手段主要擴(kuò)展理念的成組技術(shù)(GT)，涵蓋了許多資源能力匹配分析及其算法。不同的約束都認(rèn)為，但很少利用綜合運(yùn)用。摘要針對生產(chǎn)單元的問題(MC)下形成MPTVV生產(chǎn)模式，形成典型的MC技術(shù)集成分組類型的細(xì)胞(GC)、流量類型(FC),即繼承了細(xì)胞(IC)技術(shù)分析提出了基于自由度。面向?qū)嶋H生產(chǎn)像交貨期約束、生產(chǎn)批號、設(shè)備能力、關(guān)鍵設(shè)備、關(guān)鍵部分和機(jī)共享等，是一個完整的地層模型的建立和內(nèi)部相互關(guān)系綜合分析這些約束。進(jìn)而，形成目標(biāo)的類型及其生成程序變換器在聯(lián)合作用形成的約束和規(guī)則是傳播。在案例研究，形成三個高度平衡氣相色譜第一；然后俱樂部實(shí)施形成基于相同的數(shù)據(jù)表明良好的平衡作用荷載和flow-style細(xì)胞生產(chǎn)關(guān)鍵任務(wù)；當(dāng)任務(wù)是調(diào)整，通過使用IC形成方法在FC配置的結(jié)果上構(gòu)建了一項(xiàng)新計劃，更優(yōu)的性能flow-style生產(chǎn)的表現(xiàn)。該制度的研究比較不同類型的細(xì)胞強(qiáng)烈說明驗(yàn)證的綜合MC形成快速制造資源的支持下MPTVV轉(zhuǎn)變生產(chǎn)方式。
關(guān)鍵詞：多產(chǎn)品批量生產(chǎn)類型和變異，細(xì)胞的形成，流式制造單元，繼承制造單元
1介紹
如今，多種類型和可變的生產(chǎn)模式已成為必然選擇，對于大多數(shù)企業(yè)來說，在適應(yīng)或正在適應(yīng)不斷變化的需求，我們的社會當(dāng)然這是一個自然的結(jié)果。幾個類型和流動的專用生產(chǎn)線和多種類型和離散柔性生產(chǎn)線，多類型和變量生產(chǎn)的小型或中型生產(chǎn)批量生產(chǎn)之間的定位模式，定位系統(tǒng)的變異性和快速反應(yīng)的效率和靈活性兩者的優(yōu)點(diǎn)。細(xì)胞制造業(yè)是一個可容納這種類型的生產(chǎn)模式，并支持快速響應(yīng)制造系統(tǒng)的生產(chǎn)組織形式，細(xì)胞制造的核心是制造資源的重組和重用;自治，協(xié)作為特征的制造單元和靈活性的核心組成部分，因此，細(xì)胞的形成和重構(gòu)技術(shù)是執(zhí)行CMS的鑰匙。
目前，細(xì)胞的形成（CF）技術(shù)主要集中在它的構(gòu)造算法?？赡苄纬傻囊?guī)則和約束方面。如多路線和設(shè)備類型，工作時間分配，批量生產(chǎn)，設(shè)備共享，單位平衡和機(jī)容量已全部參與，但有沒有這些因素的綜合應(yīng)用。研究人員像安田等人[1]和GARBIE等人[2]用于細(xì)胞分析的相似性系數(shù)。TB根據(jù)不斷變化的市場解決集群和細(xì)胞形成的問題，皮萊等[3]，提出了一個健全的設(shè)計方法，結(jié)果細(xì)胞結(jié)構(gòu)竟然是相對穩(wěn)定的。智能算法被引入到CF求解之中，智能算法考慮的因素，如部分?jǐn)?shù)量、路線加工時間、設(shè)備容量設(shè)備的狀態(tài)和細(xì)胞的平衡和細(xì)胞間移動的最小化的目標(biāo)。ASOKAN等[4]，普拉巴卡蘭等[5]，和其他許多學(xué)者采用蟻群算法。VENKATARAMANAIAH等[6]，構(gòu)建了一個單元的配置與使用特殊元素的混合啟發(fā)式算法。MAHAPATRA等[ 7]，細(xì)胞負(fù)載平衡和細(xì)胞間移動和就業(yè)，解決遺傳算法的最小化集中。曼蘇里等[8]，使用GA算法來研究瓶頸設(shè)備、特殊零部件和設(shè)備共享的約束。韓元等[9]，采用了模糊ART神經(jīng)網(wǎng)絡(luò)算法來解決復(fù)雜的零部件和設(shè)備的分組問題。DEFERSHA等[10]，引入CF遺傳算法的并行運(yùn)算，在許多實(shí)際限制，如單元的配置，替代工藝，設(shè)備共享，容量和負(fù)載考慮平衡或和生產(chǎn)費(fèi)用。FTS等[11]，切割CF卡的過程分為兩個步驟。首先，構(gòu)建了多目標(biāo)函數(shù)為尺度單位，然后采用一個單一的目標(biāo)函數(shù)來優(yōu)化內(nèi)部和單位之間的移動。白氏等[12]，他們的注意力主要在FC形成的理論和緊急動員一批批量生產(chǎn)的技術(shù)上。作為一個整體，上述研究主要集中在靜態(tài)細(xì)胞形成，而在可持續(xù)發(fā)展的動態(tài)形成的研究很少，甚至不說綜合形成多類型的細(xì)胞。
本文的主要是制造單元（MC）的多產(chǎn)品類型的多樣化和變異量（MPTVV）生產(chǎn)模式下的問題，從多類型的MC，綜合形成模型和基于方法的綜合建設(shè)。統(tǒng)一的約束，制定規(guī)則和算法將會是研究和決策的工具。
2 技術(shù)上的挑戰(zhàn)
根據(jù)MPTVV生產(chǎn)模式，產(chǎn)品類型及數(shù)量是在不斷變化，在不同時期的時間或階段，不同時期市場需求的變化所引起的，因此使制造系統(tǒng)的配置變化的直接原因是動態(tài)的要求。在細(xì)胞制造系統(tǒng)（CMS），這種變化將最終歸咎于細(xì)胞形成，或由細(xì)胞進(jìn)行和實(shí)現(xiàn)。
細(xì)胞的形成和重構(gòu)的實(shí)質(zhì)是優(yōu)化制造資源的分配，它是一種能力制造資源的分配或再分配。資源分配的需要之間的極端情況下的權(quán)衡“一臺機(jī)器是一個細(xì)胞”和“整條生產(chǎn)線也是一個細(xì)胞” 。此外，以實(shí)現(xiàn)快速的資源轉(zhuǎn)化，而不是任務(wù)與資源的相匹配，條件下的資源分配和優(yōu)化比如一批關(guān)鍵設(shè)備、關(guān)鍵零部件、設(shè)備共享，也是必須要考慮的。執(zhí)行不成功的重要原因是傳統(tǒng)的CF技術(shù)的應(yīng)用，缺乏綜合考慮。
CF的結(jié)果是邏輯細(xì)胞，所以有細(xì)胞間和細(xì)胞中的機(jī)器有沒有固定的歸屬、沒有明確的界限。機(jī)器可以作為一個獨(dú)立的“設(shè)備單位” ，對于分散的任務(wù)，或者他們可以分享它們的能力與其他細(xì)胞，并完成任務(wù)與其他機(jī)器一起。在這種情況下，它可能會出現(xiàn)離散單元。結(jié)果配置是一個多元結(jié)構(gòu)的“完整”的單位和一個獨(dú)立的單位組成。傳統(tǒng)的分析，強(qiáng)調(diào)太多，可能會導(dǎo)致部分家庭和細(xì)胞的獨(dú)立性不和諧的生產(chǎn)。因此，瓶頸業(yè)務(wù)和設(shè)備，將出現(xiàn)和交配組裝生產(chǎn)的要求不能得到滿足。此外，細(xì)胞負(fù)荷分布不均，機(jī)器不能被細(xì)胞間的共享。
MPTVV生產(chǎn)模式下的細(xì)胞類型應(yīng)靈活多樣。在生產(chǎn)多種產(chǎn)品的類型和體積小或試生產(chǎn)中，細(xì)胞（GC）組類型的細(xì)胞形態(tài)是必需的，而在大規(guī)模批量生產(chǎn)中，需要實(shí)現(xiàn)連續(xù)生產(chǎn)。此外，在不同時期，繼承可持續(xù)重構(gòu)將是一個基本要求，努力推進(jìn)傳統(tǒng)組技術(shù)（GT）為基礎(chǔ)的技術(shù)的直接原因是，由于需求的快速變化頻繁布局調(diào)整是難以實(shí)現(xiàn)的。作為一個剛性的形成技術(shù)，有太多的努力是物理布局調(diào)整的成本。設(shè)備及零件的相似性為基礎(chǔ)的施工方法上存在的資源要求，只強(qiáng)調(diào)適應(yīng)，而不是生產(chǎn)流程的流暢性，認(rèn)為這也是一個重要的任務(wù)路線組織者同意的問題。流線式運(yùn)行在MC的形成也是一個重要的目標(biāo)。打擊周期性變化的需求，以減少成本和機(jī)器調(diào)整的影響，CF程序具有繼承原有的生產(chǎn)線。存在的CF分析氣相色譜儀，研究主要集中在類型的細(xì)胞（FC）和繼承細(xì)胞（IC）的相對很少，相同的地位，形成約束分析和不同類型的管委會統(tǒng)一建設(shè)提出。
選區(qū)、功能界別和IC分別代表不同的目標(biāo)和CF的目標(biāo)，并在制造系統(tǒng)中是典型的細(xì)胞形態(tài)。面向他們將是進(jìn)行整合形成多類型細(xì)胞的技術(shù)分析。
3 MC的形成和其約束分析的綜合模型
MC形成多個相關(guān)的約束下，在MC的形成，如生產(chǎn)的要求，交貨時間和作為批處理內(nèi)部外部因素，處理時間，機(jī)器的能力，關(guān)鍵設(shè)備和可選擇的機(jī)器一并考慮。此外，在生產(chǎn)周期時間目標(biāo)，成本，設(shè)備必須滿足實(shí)用，因而MC的形成過程又是一個多目標(biāo)優(yōu)化過程，沒有最佳，但許多次優(yōu)的解決方案，其中普遍存在。在這里，約束和目標(biāo)分解和它們的相互關(guān)系，以不同類型的MC如圖1所示。
圖1 MC形成和約束分析的綜合模型
在CF中資源、路線和任務(wù)是三個主要的需要數(shù)據(jù)，還繼承了CF使用前進(jìn)行比較的數(shù)據(jù)源配置模式。CF卡規(guī)則，包括路由選擇，機(jī)器（類型）選擇和機(jī)器任務(wù)分配規(guī)則。這里主要的CF約束是機(jī)器能力，關(guān)鍵還是質(zhì)量和關(guān)鍵設(shè)備。輸出政策的細(xì)胞和設(shè)備，在機(jī)器的能力，在資源分配中，三個加班的情況下，外包和設(shè)備采購，可以選擇短缺的情況下潘氏規(guī)則分區(qū)組成。在不同類型，甚至MC的形成階段的過程中，必須采取量化指標(biāo)，包括相似系數(shù)，操作數(shù)的細(xì)胞間，細(xì)胞負(fù)載和生產(chǎn)節(jié)拍平衡，所有這些規(guī)則，約束和目標(biāo)，構(gòu)建形成多類型的限制細(xì)胞，其中大部分是蹣跚，但一些特殊用途，例如，為FC的形成，是有規(guī)則，強(qiáng)調(diào)操作平衡的路線和設(shè)備的生產(chǎn)節(jié)拍時間，和目標(biāo)細(xì)胞中的節(jié)拍，壓力平衡。
形成三種類型的細(xì)胞，是不是獨(dú)立的，還是相互關(guān)聯(lián)的，主要的階段：設(shè)備集群的資源選擇與分配，細(xì)胞的優(yōu)化和調(diào)整，電池的輸出都可以被重用集群和輸出的過程是完全通用的，而不同的分配和優(yōu)化。規(guī)則、約束和目標(biāo)需求可以選擇不同類型的細(xì)胞。
根據(jù)圖1，選區(qū)和功能界別有兩個基本的細(xì)胞（BC），而且FC是GC和IC的擴(kuò)展也可以看作是基本細(xì)胞BC的一個擴(kuò)展，作為一個整體，GC和FC構(gòu)造一樣，就像BC和IC一樣。
4一體化形成的目的和步驟
為方便起見，采取流動的符號表達(dá)圖約束。
（1）基礎(chǔ)數(shù)據(jù)集：S0={D1，D2，D3，D4} DL表示生產(chǎn)任務(wù)；D2表示部分航線； D3表示設(shè)備資源；D4表示配置方案。
（2）形成規(guī)則的設(shè)置：S1 = {E1{E11，E12，E13，E14，E15}，E2{E21，E22}，E3{E31，E32}} 。E1表示路線的選擇，包括規(guī)則，E1L表示我的第一條路線； E12。表示至少機(jī)器類型；E13表示最短的加工時間；E14表示至少細(xì)胞間運(yùn)行時間；E15表示最高操作平衡指數(shù)E2的代表機(jī)（類型）選擇規(guī)則；E21表示當(dāng)前機(jī)器類型； E22表示最短的加工時間；E23加工節(jié)拍時間限制表示E3的代表機(jī)任務(wù)分配規(guī)則。E31表示任務(wù)分散機(jī)平均使用；E32表示任務(wù)集中和集中使用的機(jī)器。
（3）形成的制約：S2 = {F1，F(xiàn)2 F3，F(xiàn)4，F(xiàn)5 }。 F1表示機(jī)器的能力；F2表示批次； F3鍵表示關(guān)鍵零部件； F4鍵表示質(zhì)量部分； F5表示關(guān)鍵設(shè)備。
（4）設(shè)置的輸出規(guī)則：S3 = {G1，G2 G3} 。G1的表示細(xì)胞的分區(qū)規(guī)則；G2表示部分分區(qū)規(guī)則；G3表示共享設(shè)備的分區(qū)規(guī)則。
（5）形成一套目標(biāo)：S4= {H1{h11，h12}，H2，H3{h31，h32}，H4} 。H1的表示相似系數(shù)，h11表示相似系數(shù)；h12表示聯(lián)合國的相似性系數(shù)。H2表示至少間細(xì)胞的細(xì)胞操作數(shù)；H3的表示細(xì)胞負(fù)載平衡； h31表示細(xì)胞的負(fù)荷率；h32代表比例平衡細(xì)胞。H4表示節(jié)拍時間平衡。
（6）設(shè)備短缺的對待：S5={I1，I2，I3}。 I1表示加班；I2表示外包；I3表示設(shè)備的采購。
（7）對CF的四個步驟描述如下：第1步表示設(shè)備集群； 第二步表示將代表資源分配；第3步表示細(xì)胞的優(yōu)化和調(diào)整；第四步表示模式輸出。
在本文中，四個不同約束條件和目標(biāo)的步驟，標(biāo)記清楚，使用步進(jìn)目標(biāo)的啟發(fā)式算法，將是最合適的解決問題的方法。
5示例分析
以上啟發(fā)式算法已經(jīng)實(shí)現(xiàn)的VC++環(huán)境案例研究中使用表1和表2中的設(shè)備資源數(shù)據(jù)的任務(wù)數(shù)據(jù)它是指出，在表1括號中的數(shù)量后，一部分是我們的任務(wù)數(shù)、序列部分操作數(shù)路線和它的操作數(shù);由三部分P2，P8，P11組成的選擇路線，他們用陰影標(biāo)注出來;加工時間以分鐘為單位，這個任務(wù)的交付時間為兩個月。
表1 任務(wù)資源列表
表2 設(shè)備資源列表
6結(jié)論
（1）綜合模型的構(gòu)建，對MC形成約束進(jìn)行了分析。MC形成受多個相關(guān)的約束。它的目標(biāo)可以被容易的擴(kuò)展，使它可以用于優(yōu)化一種多元化的“更多”的目標(biāo)的問題中。MC形成不同類型的影響及其形成過程相互之間的內(nèi)在聯(lián)系。在細(xì)胞形成的不同時期、不同的約束和規(guī)則逐步付諸實(shí)施。
（2）形成一體化的目標(biāo)和程序提出。細(xì)胞形成約束是數(shù)學(xué)符號和不同階段細(xì)胞 的類型來表示的。形成目標(biāo)的公式描述。應(yīng)用這種約束和目標(biāo)的過程也是詳細(xì)的。
（3）示例分析表明，綜合MC的形成是一個有價值的方法，適應(yīng)MPTVV生產(chǎn)模式。
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Integrated Manufacturing Cell Formation Technology orienting Multi-productType and Variant Volume Production
Abstract：What is pursued by multi-product type and variant volume(MPTVV) production is rapid response and quick switching，so that structure of transferring line in manufacturing system is no longer unalterable．Cell formation(CF) algorithm is the key technology of cellular manufacturing system(CMS)．Currently，CF methods are mainly extended on the idea of group technology(GT) that covers a lot on analysis of resource capability matching and its algorithm．Various constraints are considered，but seldom utilized comprehensively．Aimed to the problem of manufacturing cell(MC) formation under MPTVV production mode，integrated formation Technologies for typical MC as group type of cell(GC)，flow type of cell(FC) and inherited cell(IC) are presented based on technical analysis of CF．Oriented to practical production constraints like delivery time，product batch，equipment ability ,key machine，key part and machine sharing，etc，an imegrated formation model is constructed and intemal imterrelations of these constraints are analyzed synthetically．Ulteriorly，formation goals of types of MCs and their formation procedures under joint effect of formation constraints and rules are spread．In casestudy，three highly balanced GC are formed first; then FC formation are implemented based on the same data which indicate good balancing effect of cell load and flow-style production for key tasks；When task is adjusted，a new scheme is constructed on the result of FC configuration by using IC formation method，and more optimal performance of flow-style production is manifested．The proposed comparative study of different type of cells strongly explains the validation of integrated MC formation in support of rapid manufacturing resource transformation under MPTVV production mode．
Keywords：multi-product type and variant volume production，cell formation，flow style manufacturing cell， inheriting manufacturing cell
1 Introduction
Nowadays, multiple type and variable production mode has been an inevitable choice for most enterprises, which is a natural result in the course of adapting or being adapted to the ever changing needs of our society. As a mode positioned between few type and mass production of flowing dedicated production line and multiple type and small or medium production of discrete flexible production line, multiple type and variable production has both advantages of efficiency and flexibility targeting variability and rapid response of system. Cellular manufacturing is a form of production organization which can accommodate to such type of production mode，and well support rapid response of manufacturing system．The core of cellular manufacturing is the reorganization and reuse of manufacturing resources；manufacturing cell characterized with self-government，collaboration and flexibility is the core component．Therefore，technologies of cell formation and reconfiguration are also the keys in implementation of CMS．
Presently,technologies of cell formation(CF)are mainly focusing on its construction algorithm．Likely aspects of formation rules and constraints．such as multi-routes and equipment types，work time assignment，batch production， equipment sharing, balancing of unit and machine capacity have all been involved，but there is an absence of integrated application of these factors．Researchers like YASUDA，et al[1] and GARBIE，et al[2] used similarity coefficient for cell analysis．Tb solve the problem of formation of clusters and cells under changing market，PILLAI，et al[3]，proposed a robust design method based on demand forecast and the result cell structure turned out to be relatively stable．Intelligent algorithm was introduced for CF solving．Considering factors like part number, route，processing time，equipment capacity equipment status and objectives of cell balancing and minimization of inter-cell moving．ASOKAN，et al[4]，PRABHAKARAN，et al[5],and many other scholars adopted ant colony algorithm VENKATARAMANAIAH, et al[6], constructed an unit configuration with exceptional elements using hybrid heuristic algorithm．MAHAPATRA，et a[7]，concentrated on cell load balancing and minimization of inter-cell moving and employed GA for solution．MANSOURI, et al[8]， studied constraints of bottleneck equipments，exceptional parts and equipment sharing using GA method．WON，et al[9]，adopted fuzzy ART N-N algorithm to solve grouping problem of complicated parts and equipments．DEFERSHA，et al[10]，introduced GA parallel arithmetic into CF, in which many practical restriction like cell configuration，substitute process，equipments sharing and capacity and load balancing or them，and production fees were taken into account．FTS，et al[11]，cut CF procedure into two steps． Firstly， multi-objective function was constructed for scaling units，and then a single objective function was employed targeting optimization of moving within and between units．BAI，et al[12]，paid their attention to FC formation theory and technique for emergency mobilization batch volume production．As a whole，above researches are mainly focused on static cell formation，while studies on sustainable dynamic formation are seldom， even not to say integrated formation of multi—cell types．
Main focus of this article will be on the problem of manufacturing cell(MC) diversification under multi-product type and variant volume(MPTVV) production mode． From the view of integrated construction of multi-type MCs，integrated formation model and method based on unified constraints，rules and algorithms will be studied，and decision-making tools will be developed．
2 Technical Challenge
Under MPTVV production mode，product type and volume is on constant change at different period of time or stages of different period stemming from market requirement change．So the direct reason bringing configuration change of manufacturing system is dynamic requirement. In cellular manufacturing system(CMS)，such change will finally impute to cells formed，or be undertaken
and realized by cells．
The essential of cell formation and reconfiguration is optimizing assignment of manufacturing resource．It is a kind of allocation or reallocation of ability of manufacturing resource． Resource assignment needs to tradeoff between extreme cases of “one machine is one cell” and “the whole line is also one cell”．Moreover．to
realize rapid resource transformation，other than matching between task and resource， resource assignment and optimization under conditions like delivery time，batch，key
machine， key part and equipment sharing have to be considered also． Important reason of unsuccessful implementation applying traditional CF technologies is in
1ack of comprehensive consideration．
The outcome of CF is logical cells，so there are no clear boundaries among cells and machines in cells have no fixed attribution．Machines may act as a standalone “device unit” for scattered tasks，or they can share their capacity with other cells and accomplish tasks with other machines．In this case，it’s possible that discrete units will emerge．The result configuration is a plural structure composed by ‘‘complete” units and a discrete unit．Traditional analysis emphasizes independence of part family and cells too much that may result in unharmonious production． Thus， bottleneck operations and equipments will appear and requirement of mating production for assembly cannot be satisfied．Moreover, cell load distribution is uneven and machines cannot be shared among cells．
Cell types under MPTVV production mode should be flexible and various． In multi-product type and small volume or trial production，cell form of group type of
cell(GC)is required，while in mass volume production， continuous production has to be realized． Furthermore，during different period，inheriting sustainable reconfiguration will be a basic demand．The direct reason of hard advancing of traditional group technology(GT) based technologies is that frequent layout adjustment due to rapid change of requirement is difficult to realize．As a rigid
formation technology，too many efforts have to be cost on physical layout adjustment．Construction method based on similarity of equipments and parts only emphasizes adaptation of existed resources to requirements，but not fluency of production flow in the view of routes of tasks which is also an important problem consented by organizers．Flow line type running is also an important objective in MC formation．Against periodical changing requirements， to lessen cost and influence of machine adjusting，CF procedure has to inherit original production line．Existed CF analysis mainly focuses on GC，researches on type of cell(FC)and inherited cell(IC)are comparatively seldom，and same status presents in formation constraint analysis and unified construction of different types of MCs．
GC，F(xiàn)C and IC represent different objectives and targets of CF and are typical cell forms in manufacturing system．Technical analysis on integrate formation for multi-type cell will be carried out orienting them．
3 Integrated Model of MC Formation and Its Constraints Analysis
MC is formed under multiple related constraints．During MC formation，external factors like production requirement，delivery time and internal ones as batch，processing time，machine ability, key equipment and selectable machine have to be considered together．Also，production goals in cycle time，cost，equipment utility have to be satisfied，thus the course of MC formation is again one multi-objective optimization procedure，in which no optimum but many suboptimum solution exists commonly．Here，constraints and goals are decomposed and their interrelations to
different type of MCs are illustrated in Fig．1．
Resource.route and task are three main data needed in CF, yet inherited CF has to use former configuration schemas as source data for comparing．CF rules include route selection。machine(type)selection and machine task assignment rules．Main CF constraints here are machine ability batch，key or mass pans and key equipment．Output policies are composed of partition rules for cell and equipment and pan family In case of shortage of machine ability in resource assignment，three scenarios of overtime，outsource and equipment procurement can be selected．In the process of different types or even stages of MC formation， quantitative indexes including similarity coefficient，inter-cell operation number, cell load and takt time balancing have to be adopted． All these rules，constraints and goals construct formation constraints of multi-type cell．Most of them are shamble，but some are for special purpose．For example，for FC formation，there’re rules that emphasize operation balancing of route and production takt time of equipment，and goals that stress takt
balancing in cell．
Formation of three type of cell is not independent but interrelated， main stages： equipment cluster' resource selection and assignment，cell optimization and adjusting
and cell output can all be reused．Cluster and output process are entirely universal， while assignment and optimization is different for different type of cell that rules，
constraints and goals can be selected in demand．
According to Fig．1，GC and FC are two basic cell(BC)，and that FC is extended on GC and IC can be seemed as extension of BC．As a whole．GC constructs the constraints of FC like that BC to IC．
4 Objective and Procedure of Integrated Formation
For convenience，the flowing symbols are taken to express constraints in Fig．1．
(1)Base data set：S0={D1，D2，D3，D4}．Dl denotes production tasks； D2 denotes part routes； D3 denotes equipment resources；D4 denotes configuration schemes．
(2)Formation rules set：S1={El{e11，e12，e13，e14，e15}，E2{e2l，e22}，E3{e3l，e32}}．El denotes routes selection rules，including；e1l denotes me first route; e12 denotes least machine type；e13 denotes shortest machining time；e14 denotes least inter-cell operation time；e15 denotes highest balancing index of operations．E2 denotes machine(type) selection rules； e2l denotes current machine type； e22
denotes shortest machining time；e23 denotes machining time limited by takt time． E3 denotes machine task assignment rules；e31 denotes task dispersed and average
use of machines；e32 denotes task concentrated and focus use of machines．
(3)Formation constraints set：S2={F1,F2,F3,F4,F5}．F1 denotes machine ability；F2 denotes batch；F3 denotes key parts；F4 denotes mass parts；F5 denotes key equipment．
(4)Output rules set：S3={G1，G2，G3}．G1 denotes cell partition rules；G2 denotes part partition rules；G3 denotes sharable equipment partition rules．
(5)Formation goals set：S4={H1{h11，h12}，H2，H3{h3l，h32}，H4}．Hl denotes similarity coefficient，h11 denotes similarity coefficient：hl2 denotes un—similarity coefficient．H2 denotes least inter-cell operation number；H3 denotes cell load balancing；h31 denotes cell load ratio；h32 denotes ratio of balanced cell load．H4 denotes takt time balancing in cell．
(6)Treatment set for shortage of equipment：S5={I1，I2，I3}．Il denotes overtime；I2 denote outsource；I3 denote equipment procurement．
(7) Four steps of CF are described as follows：STEP 1 denotes equipment cluster； STEP2 denotes resource assignment；STEP3 denotes cell optimization and adjusting；STEP4 denotes schema output．
In this paper, four steps with different constraints and objectives are marked out clearly， so that heuristic algorithm with stepped objective would be the most
suitable problem solving method．
5 Case Study
Above heuristic algorithm has been realized in VC++ environment．Case study uses task data in Table 1 and equipment resource data in Table 2．It is noted that in Table l the number in bracket after part is number in our task；sequence number of part operation is composed of route and its operation number；three parts P2，P8，P11 have selectable route，and they’re marked out using shadow；machining time uses minute as unit．Delivery time of this task is two months．
6. Conclusions
(1)Integrated Model of MC fornation is constructed and formation constraints are analyzed． MC formation is impacted by intermal or extemal factors that it is the outcome of multiple interrelated constraints．Its objective can be easily extended to make it an optimization problem of multi¨more”objectives．MC formation of different
type is impact each other and their formation procedures are interlinked．At different
stage of cell formation，different constraints and rules are put into effect gradually．
(2) Objectives and procedure of integrated formation are presented．Cell formation constraints are denoted by mathematic symbols and for different stages of types of cells． Formula description for formation goals is given．Application process of such constraints and goals is also detailed．
(3)Case study shows that integrated MC formation is a valuable method adaptive to MPTVV production mode．