ZL50裝載機總體及工作裝置設計
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題 目： 皮帶輪落料拉深復合模設計
學 院： 機械工程學院
專 業(yè)： 材料成型及控制工程
學 號：
姓 名：
指導教師：
完成日期： 2008年2月29日
目 錄
目錄.....................................................1
第一章 零件的工藝性分析..............................2
第二章 毛坯尺寸展開計算..............................3
第三章 拉深工序次數(shù)及拉深系數(shù)確定...................5
第四章 沖裁力與拉深力的計算...........................11
第五章 凸、凹模的設計.................................7
1、 落料凸、凹模尺寸計算.........................7
2、 拉深凸、凹模尺寸計算..........................8
3、 粗糙度的確定.................................9
第六章 模具基本結構的確定...........................13
第七章 模具主要零件的強度校核.........................15
第八章 沖壓設備的選擇...............................16
1、初選設備....................................16
2、設備的校核..................................18
主要參考文獻
附錄
第一章 零件的工藝性分析
1、零件的形狀、尺寸及一般要求
該零件為厚度2mm，大筒直徑為86.8mm，小筒直徑為47mm的皮帶輪，零件材料T8，尺寸精度按圖紙要求。
2、工藝方案的分析及確定
工件由落料、拉深、反拉深三道工序成型，工件形狀較簡單。
根據(jù)計算可知，拉深工序需要進行多次拉深才能完成，如果完全采用連續(xù)模，則模具結構比較復雜會增加沖壓件的生產成本。所以可先采用復合模進行落料和第一步拉深，然后采用連續(xù)模直至拉深完成，再采用單工序模進行反拉深。
本次主要設計其第一道工序，即落料和第一步拉深。
2
課程設計說明書
題 目： 皮帶輪落料拉深復合模設計
學 院： 機械工程學院
專 業(yè)： 材料成型及控制工程
學 號：
姓 名：
指導教師：
完成日期： 2008年2月29日
目 錄
目錄.....................................................1
第一章 零件的工藝性分析..............................2
第二章 毛坯尺寸展開計算..............................3
第三章 拉深工序次數(shù)及拉深系數(shù)確定...................5
第四章 沖裁力與拉深力的計算...........................11
第五章 凸、凹模的設計.................................7
1、 落料凸、凹模尺寸計算.........................7
2、 拉深凸、凹模尺寸計算..........................8
3、 粗糙度的確定.................................9
第六章 模具基本結構的確定...........................13
第七章 模具主要零件的強度校核.........................15
第八章 沖壓設備的選擇...............................16
1、初選設備....................................16
2、設備的校核..................................18
主要參考文獻
附錄
第一章 零件的工藝性分析
1、零件的形狀、尺寸及一般要求
該零件為厚度2mm，大筒直徑為86.8mm，小筒直徑為47mm的皮帶輪，零件材料T8，尺寸精度按圖紙要求。
2、工藝方案的分析及確定
工件由落料、拉深、反拉深三道工序成型，工件形狀較簡單。
根據(jù)計算可知，拉深工序需要進行多次拉深才能完成，如果完全采用連續(xù)模，則模具結構比較復雜會增加沖壓件的生產成本。所以可先采用復合模進行落料和第一步拉深，然后采用連續(xù)模直至拉深完成，再采用單工序模進行反拉深。
本次主要設計其第一道工序，即落料和第一步拉深。
第二章 毛坯尺寸展開計算
旋轉體零件采用圓形毛坯，在不變薄拉深中，材料厚度雖有變化，但其平均值與毛坯原始厚度十分接近。因此，其直徑按面積相等的原則計算，即毛坯面積與拉深件面積（加上修邊余量）相等。
1、確定修邊余量
在拉深的過程中，常因材料機械性能的方向性、模具間隙不均、板厚變化、摩擦阻力不等及定位不準等影響，而使拉深件口部周邊不齊，必須進行修邊，故在計算毛坯尺寸時應按加上修邊余量后的零件尺寸進行展開計算。
修邊余量的數(shù)值可查文獻《實用模具技術手冊》表5-7.
由于工件凸緣的相對直徑
d凸/d = 1.1013
查表可得修邊余量δ=3.5mm。
2、毛坯尺寸計算
根據(jù)工件的形狀，可將其分成F1-F8這幾個部分。則可計算出各部分的展開面積如下：
F1 =π/4[2π(4+t/2)(90.8-t)+4.56(4+t/2)2
=π/4[2π×5×88.8+4.56×52]
=222π2+28.5π
F2 =π(d-t)(h-r1-r2-t)
=π(90.8-2)(34-4-2-2)
=2308.8π
F3 =π/4[2π(2+t/2)(90.8-t-2×2-t)+8(2+t/2)2]
=π/4(2π×3×82.8+72)
=124.2π2+18π
F4 =π/4(90.8-2t-2×2)2-π/4(47+2t+2×2)2
=π/4×82.82-π/4×552
=957.71π
F5 =π/4[2π(2+t/2)(47+t)+4.56(2+t/2)2]
=π/4(2π3×49+4.56×32)
=73.5π2+10.26π
F6 =(20-2t-2×2)π(47+t)
=588π
F7 =π/4[2π(2+t/2)(47-2×2)+8(2+t/2)2]
=π/4(2π3×43+8×32)
=64.5π2+18π
F8 =π/4(47-2×2)2
=462.25π
得：π/4D2=222π2+28.5π+2308.8π+124.2π2+18π+957.71π+73.5
π2+10.26π+588π+64.5π2+18π+462.25π
D2=1936.8π+17566.08=23647.632
所以經計算求得毛坯直徑D=154mm
3、確定是否使用壓邊圈
由于D-d>22t,則要使用壓邊圈。
壓邊力的計算：
因為k=D/d=154/(47+4)=3
Fmax=πdt(k-1)бb
=3.14×51×2×2×329=210.7 kN
所以F=0.1[1-18k/(k-1)]k2Fmax
=0.1[1-(18×3)/(3-1)×32×210.7
=0.1×0.65×9×210.7
=123.4kN
第三章 拉深工序次數(shù)及拉深系數(shù)確定
在制定拉深件的工藝過程和設計拉深模具時，必須預先確定是否可以一道工序完成，或者是經過幾道工序才能制成。在確定拉深工序次數(shù)時，必須做到使毛坯內部的應力既不超過材料的強度極限，而且還能充分利用材料的塑性。也就是說每一次拉深工序，應在毛坯側壁強度允許的條件下，采用最大可能的變形程度。
制訂拉深工藝時,為了減少拉深次數(shù),希望采用小的拉深系數(shù)(大的拉伸比)。有力學分析可知，拉深系數(shù)過小，將會在危險斷面產生破裂。因此，要保證拉深順利進行，每次拉深系數(shù)應大于極限拉深系數(shù)。
該零件的拉深系數(shù)，即拉深后圓筒件直徑與拉深前毛坯直徑的比值，為
m=d/D=(47+4)/154=0.33
有凸緣的圓筒件在拉深時還要考慮拉深的相對高度是否大于極限相對高度。計算可得拉深的相對高度為：
h/d=20/（47+4）=0.392
極限拉伸系數(shù)與板料成形性能、毛坯相對厚度、凸凹模間隙及其圓角半徑有關。
通過計算可得：
π/4dF2-756.25π+73.5π2+10.26π+588π+64.5π2+18π
+462.25π=484.2 π2+4391.52π
dF=143.6
所以：法蘭相對直徑dF/d=143.6/（47+2）=2.93
毛坯的相對厚度t/D×100=2/154×100=1.3
依文獻《沖壓工藝學》，查表4-10，查得零件的極限拉深系數(shù)
[m]=0.32
依文獻《實用模具技術手冊》，查表5-16，查得第一次拉深的最大相對高度[h/d]=0.18
可知拉深系數(shù)大于極限拉深系數(shù)，拉深的相對高度大于極限相對高度，所以不能一次拉深成形。
由于本設計只進行第一次拉深的設計，所以對以后的多次拉深不進行計算。
第四章 沖裁力與拉深力的計算
1、沖裁力的計算
計算沖裁力的目的是為了合理地選用壓床和設計模具。壓床的噸位必須大于所計算的沖裁力，以適應沖裁的要求。
平刃模具沖裁時，其沖裁力F0可按下式計算：
F0=Ltτ
式中× t——材料厚度，[t]為mm
τ——材料抗剪強度，[τ]為MPa
L——沖裁周長，[L]為mm
考慮到模具刃口的磨損，凸、凹模間隙的波動，材料機械性能的變化，材料厚度偏差等因素，實際所需沖裁力還須增加30%，即
F=1.3F0=1.3Ltτ
所以沖裁力F=1.3×2π×154/2×2×260=326.89 kN
因為模具采用剛性卸料裝置，所以不用計算卸料力。
而F頂件力=K2F=0.06×326.89=19.62 kN
(依文獻《沖壓工藝學》查表2-10得K2=0.06）
所以總沖裁力為：
F0=326.89+19.62=346.51 kN
2、拉深力的計算
在確定拉伸件所需的壓力機噸位時，必須先求的拉深力。在拉深帶法蘭的圓筒件的生產中常用如下經驗公式計算：
F = πd1tσbK
式中 t——料厚；
d1——第一次拉深半成品圓筒直徑；
σb——抗拉強度
由于零件材料為T8鋼，查得其抗拉強度
為329MPa；
K——系數(shù)，依文獻《沖壓工藝學》查表4-11
查得K =1；
由上求得拉深力 F = 103.3 kN ;
第五章 凸、凹模設計
1、落料凸、凹模尺寸計算
因為落料形狀為圓形，形狀簡單，所以采用凸、凹模分開加工的方法。
查文獻《沖壓工藝學》表2-3可知
沖裁模的雙面間隙為：Zmin=0.12mm, Zmax=0.16mm
則凸模和凹模的制造公差分別為：
δp=0.4(Zmax-Zmin)=0.4(0.16-0.12)=0.016
δd=0.6(Zmax-Zmin)=0.6(0.16-0.12)=0.024
設工件尺寸為D-△。落料時首先確定凹模尺寸，使凹模公稱尺寸接近或等于工件輪廓的最小極限尺寸，再減小凸模尺寸以保證最小合理間隙Zmin。則凸、凹模的尺寸計算公式如下：
Dd=(D-x△）+δd
DP=(Dd-Zmin)-δp=(D-x△-Zmin)-δp
式中 Dd、DP——落料凹、凸模尺寸，[Dd]與[DP]為mm
△—工件制造公差，[△]為mm
Zmin—最小合理間隙（雙面），[Zmin]為mm
δp、δd—凸、凹模的制造公差，[δp][δd]為mm
x△—磨損量，其中系數(shù)x是為了使沖裁件的實際尺寸
盡量接近沖裁件公差帶的中間尺寸
查文獻《沖壓工藝學》表2-7，可知x=0.75.
2、拉深凸、凹模尺寸計算
一、凹模圓角半徑rd
rd與毛坯厚度、零件的形狀尺寸和拉深方法有關
因為D-dd(凹模內徑)>30時，應取較大的rd值
查文獻《沖壓工藝學》表4-6，可得
rd=9mm
二、凸模圓角半徑rp
一般可取rp =rd。最后一道拉深時rp等于零件的圓角半徑.
所以取 rp =rd = 9mm.
三、凸、凹模間隙c
決定凸、凹模間隙時，不僅要考慮材質和板厚，還要考慮工件的尺寸精度和表面質量要求。
由于該拉深要使用壓邊圈，則
C = tmax+kt ；取C=2mm
式中 tmax——材料最大厚度；
k——間隙系數(shù)。
由于零件的尺寸標注在內徑上，則依凸模為準，間隙取在凹模上，即增大凹模尺寸得到間隙。
四、凸、凹模尺寸及制造公差
最后一道拉深模的尺寸公差決定了零件的尺寸精度，故其尺寸、公差應按零件要求來確定。
對于多次拉深的第一次拉深和中間工序的毛坯尺寸公差沒有必要限制，此時，可取模具尺寸等于毛坯過渡尺寸。若取凸模為基準，則
凸模尺寸 DP=D-δp
凹模尺寸 Dd=（D+2c)+δd
根據(jù)拉深系數(shù)m=0.32，即d/154=0.32，d=50則，D=50-2t=46
凸、凹模的制造公差依文獻《沖壓工藝學》查表4-7，依工件的厚度和拉深直徑，查得
δd=0.08， δp=0.05
則：DP=46-0.05 ; Dd=50+0.08
3、粗糙度的確定
凸凹模的刃口部位要求較高，粗糙度選用0.4，凸模及凹模鑲塊用于固定的部位選用0.8，對于固定板上的孔，由于加工較困難，可選用1.6，其它不太重要的部位選用6.3。
第六章 模具基本結構的確定
模具的基本結構和組成如下所示：
1、凸、凹模的結構形式
一、落料凸模與拉深凹模
采用凸緣形式，用螺栓與上模板緊固。
模具結構如下圖所示
二、落料凹模
模具結構如下圖所示
三、拉深凸模
采用嵌入式結構，用螺釘與下模板緊固。
模具結構如下圖所示：
2、模具其他部分的作用與選材如下：
上模座：
上模座的作用是通過模柄與壓力機相連接，將模具的上模部分安裝在壓力機上。材料選用HT200。因為上模座在模具工作中只承受沖擊力，要求材料具有較好的強度和韌性。上模座尺寸選用315mm ×200mm×45mm
上模墊板
上模墊板在模具工作過程中，承受卸料組件、沖頭傳遞過來的較大的沖擊載荷。因此要求材料有較好的強度、硬度和一定的韌性。選用45，調質到HRC38~43。
卸料板
本模具選用固定卸料板，用螺栓和銷釘固定在下模上，能承受的卸料力較大，常用于厚板沖壓件的卸料。厚度為6mm，材料選用45鋼，調質HRC38~43。
定位板
定位板在過程中起到保證單個毛坯在拉深過程中有正確位置的作用,以保證拉深出合格的制件。通過螺釘與凹模固定板連接，以毛坯外形進行定位。厚度為5mm,材料選用45鋼，調質HRC38~43。
拉深凸模固定板
該固定板在模具中不僅起穩(wěn)定拉深凸模的作用，還通過其與下模板之間的彈簧的作用起到壓邊圈的作用。在工作過程中要承受來自落料凸模的沖擊，因此要求材料有較好的強度、硬度和一定的韌性。選用45，調質到HRC38~43。
下模固定板
承受很大的沖擊載荷。需要有較好的韌性和強度。選用45鋼。
下模座
其作用與上模座相似，選用HT200。尺寸選用315mm ×200mm×55mm。
2、模架
選定模具的基本形式后，開始選擇模架。依凹模尺寸及壓力機 工作臺尺寸選取。根據(jù)文獻《實用模具技術手冊》，選用后側導柱模架，選用HT200。其各尺寸參數(shù)如下：
凹模周界 D=200 mm
B=200mm， L=315mm
閉合高度 190~230mm
導套 32mm×160mm
導柱 32mm×43mm×110mm
其結構形式如下圖：
本模具采用人工送料。
第七章 模具主要零件的強度校核
1、 壓力中心的確定
為了保證壓力機和模具正常的工作，必須使沖模的壓力中心與壓力機滑塊中心線相重合。否則在沖壓時會使沖模與壓力機滑塊歪斜，引起凸、凹模間隙不均和導向零件加速磨損，造成刃口和其它零件的損壞，甚至還會引起壓力機導軌磨損，影響壓力機精度。本制件為圓形，壓力中心在圓心。
2、模具主要零件強度設計
凸、凹模
凸模長度確定以后，一般不作強度計算，且該凸模直徑較大，不會造成縱向失穩(wěn)或折彎，故可不進行校核。
同理，凹模外形尺寸確定以后，可以保證凹模具有足夠的強度和剛度，也不做強度校核。
墊板
墊板的作用是為了平均分布模板所受到的壓力，可根據(jù)凸模傳給的壓力來決定墊板是否合格。
第八章 沖壓設備的選擇
沖壓設備的選擇直接關系到設備的合理使用、安全、產品質量、模具壽命、生產效率和成本等一系列問題。
1、初選設備
沖壓生產中主要應用的是曲柄壓力機和液壓機。由于本零件的成型屬于落料淺拉深，且根據(jù)其幾何尺寸和精度要求，選用具有C形床身的開式曲柄壓力機。雖然開式壓力機的剛度差，并且由于床身變形而破壞了沖模的間隙分布，降低了沖模的壽命和制件的質量。但是，它卻具有操作空間三面敞開，操作方便，容易安裝機械化的附屬設備和成本低廉等優(yōu)點。
在壓力機的類型選定以后，應進一步根據(jù)變形力的大小，沖壓件的尺寸和模具尺寸來確定設備的規(guī)格。
由于沖裁工序與拉深工序不是同時進行，所以只需考慮兩工序中所需壓力較大的工序。
沖裁力為 F = 346.51 kN，依沖壓力的計算圖與沖壓設備需要負荷圖對比，故可選用公稱壓力為 450 kN的壓力機。根據(jù)國標 JB/T 9965-1999 ，初選壓力機的型號為 J21-45。
依文獻《沖壓模具簡明設計手冊》表13.10，可查得該壓力機個技術參數(shù)如下：
標稱壓力/kN 450
標稱行程/mm 3.2
滑塊行程/mm 120
行程次數(shù)/次·min-1 80
最大閉合高度/mm 270
封閉高度調節(jié)/mm 60
滑塊中心線到機身距離/mm 225
工作臺尺寸 左右/mm 810
前后/mm 440
工作臺孔尺寸/mm 150
模柄孔尺寸 直徑/mm 50
深度/mm 60
電動機功率/kW 5.5
2、設備校核
裝模高度校核
為使模具正常工作，模具閉合高度必須與壓力機閉合高度相適應，應介于壓力機最大和最小閉合高度之間，一般按如下關系確定：
h最大-5mm >= h模 >= h最小+10mm
所設計模具的閉合高度為 220mm ，而壓力機的閉合高度為 210mm ~270mm，在可調范圍之內。
滑塊行程校核
在拉深中為了便于安放毛坯和取出工件,其行程一般大于拉深件高度的2.5倍。工件高度為9mm,而壓力機行程為 60mm,故該壓力機行程符合規(guī)定。
模具安裝空間尺寸校核
包括工作臺面的大小和模柄孔尺寸。經校核比較該模具可在壓力機工作上正確安裝和定位。且臺面上的漏料孔與所選工藝相適應。
主 要 參 考 文 獻
主要參考文獻
[1] 王孝培,沖壓手冊（修訂本）.機械工業(yè)出版社.1988
[2] 薛啟翔.冷沖壓實用技術.北京：機械工業(yè)出版社.2006
[3] 鄭家賢.沖壓工藝與模具設計實用技術.北京：機械工業(yè)出 版社.2005
[4] 郝濱海.實用模具技術手冊.北京：化學工業(yè)出版社.2004
[5] 周良德，朱泗芳等.現(xiàn)代工程圖學.湖南：湖南科學技術出版社.2000
[6] 肖景容，姜奎華.沖壓工藝學.北京：機械工業(yè)出版社.2004
[7] 陳錫棟、周小玉，實用模具技術手冊。北京：機械工業(yè)出版社.2005
[8] 模具實用技術叢書編委會.沖模設計應用實例.北京：機械工業(yè)出版社.2000
[9] 高為國.模具材料.北京：機械工業(yè)出版社.2005
[10] 王衛(wèi)衛(wèi).材料成形設備.北京：機械工業(yè)出版社.2005
[11] 俞漢清，陳金德.金屬塑性成形原理.北京：機械工業(yè)出版社.2003
[12] 廖念釗，莫雨松，李碩根，楊興駿等.互換性與技術測量.北京：中國計量出版社.2003
[13] 楊可楨，程光蘊.機械設計基礎（第四版）.北京：高等教育出版社.1999
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大連交通大學2017屆本科生畢業(yè)設計外文翻譯
knowledge-based blackboard framework for stamping process planning in progressive die design
S.B. Tor · G.A. Britton · W.Y. Zhang
Springer-Verlag London Limited 2004
Abstract： It is widely accepted that stamping process planning for the strip layout is a key task in progressive die design. How-ever, stamping process planning is more of an art rather than a science. This is in spite of recent advances in the field of artificial intelligence, which have achieved a lot of success in incorporating built-in intelligence and applying diverse know-ledge to solving this kind of problem. The main difficulty is that existing knowledge-based expert systems for stamping process planning lack a proper architecture for organizing heterogeneous knowledge sources (KSs) in a cooperative decision making en-vironment. This paper presents a knowledge-based blackboard framework for stamping process planning. The proposed ap-proach speeds up the progressive die design process by automat-ing the strip layout design. An example is included to show the effectiveness of the proposed approach.
Keywords ：Knowledge-based · Object-oriented · Progressive die design · Stamping process planning
1.Introduction
Progressive dies for producing sheet metal parts in mass pro-duction have been widely applied in various industries such as aerospace, electronics, machine tools, automobiles, and re-frigeration. These dies can perform piercing, notching, cut-off, blanking, lancing, bending, shaving, drawing, embossing, coin-ing, trimming, and other miscellaneous forming operations at a single setup. Hence, a progressive die is generally very com-plex. Stamping process planning and die structure design are difficult and demanding tasks.
Stamping process planning starts with an unfolding of a model of stamped metal part to produce a flat pattern, followed by nesting the pattern to produce a blank layout. Next, stamping operations are planned and operations are assigned to die sta-tions. The resulting plan is typically represented as a strip layout, which guides the subsequent die structure design. The produc-tivity, accuracy, cost, and quality of a progressive die mainly depends on the strip layout, and hence a stamping process. How-ever, stamping process planning still remains more of an art rather than a science. Historically, this activity is mainly car-ried out manually, based on designers’ trial-and-error experience, skill and knowledge.
Recent advances in the field of artificial intelligence (AI) have given rise to the possibility to construct AI-based systems that incorporate built-in intelligence and apply diverse knowledge to solving progressive die design problems, including strip layout design automation. The diverse knowledge sources (KSs) re-lated to stamping process planning include unfolding knowledge to produce a flat pattern, nesting knowledge to produce a blank layout, mapping knowledge to transform stamping features into stamping operations, and staging knowledge to sequence the stamping operations. A discussion of some knowledge-based pro-gressive die design work related to our study can be found in Sect. 2. However, the existing work is based on the conventional architecture of knowledge-based expert systems, which are in-capable of managing heterogeneous KSs effectively. This limits both their practicability and scalability.
To address the above issue, it is necessary to provide a coop-erative problem solving strategy that can foster communication between diverse KSs, and accommodate different knowledge representation schemes within an integrated framework. Hence, a knowledge-based blackboard framework consisting of a black- board control system and a few independently executing KSs have been developed. This framework provides a cooperative de-cision making environment and facilitates a hybrid knowledge representation scheme, including procedures, production rules, and object-oriented representations.
A prototype system has been implemented using the object-oriented expert system shell CLIPS (C Language Integrated Pro-duction System) [1], which is interfaced with a parametric- and feature-based CAD system, Solid Edge through C++. An ex-ample is provided to demonstrate our approach and to show its effectiveness in stamping process planning.
2.Related work
Research in the computer-aided stamping process planning has been widely reported since the 1970s. The advantages of auto-mated process planning are productivity improvements, cost re-ductions, and design automation.
From the mid 1970s to mid 1980s, the first generation of CAD/CAM systems for progressive die design were de-veloped [2–5], though few of them are based on AI techniques. These early systems are characterized by basic computer graph-ics facilities, standardization of die components, and standard-ization of design procedures. They reduced design and drafting lead time. However, as these systems represent design know-how in the form of conventional procedural programming languages, only generation of the die part list and drafting of the assembly and part drawings are executed using computers. The designer still needs to decide most of the important decisions interactively, including strip and die layouts.
Since the late 1980s, significant efforts have been made by worldwide researchers to integrate a wide variety of AI and traditional CAD approaches to develop dedicated progressive die design automation systems, including strip layout design automation.
Knowledge-based approach is a popular AI technique that has been used in intelligent stamping process planning and die design system. For example, researchers at the University of Massachusetts, USA have described a knowledge-based sys-tem for design of progressive stamping dies for a simple hinge part [6]. The system generates the flat pattern geometry and de-velops a strip layout automatically. Researchers at the National University of Singapore have been developing an intelligent pro-gressive die (IPD) design system since the late 1980s. They used feature modeling and rule-based approach to realize automatic punch shape selection, strip layout development, and 3-D die configuration [7, 8]. Based on a feature-relationship tree that de-scribes the stamped metal part and its topological information, model-based reasoning and spatial reasoning techniques have been employed to reason out certain stamping processes and guide the overall planning process to develop the strip layout automatically. Researchers at the Indian Institute of Technology have developed a computer-aided die design system, CADDS, for sheet-metal blanks [9], based on heuristic rule-based reason-ing and parametric programming techniques. The greatest advan- tage achieved by the system is the rapid generation of the most efficient strip layouts. Researchers at the University of Liverpool have worked on design automation for progressive piercing and blanking dies [10, 11]. Their work is based on applying a coding technique to characterize the stamped part geometric features, which is subsequently used to generate the type and layout of the die punches, and then develop the strip layout automatically. Researchers at Huazhong University of Science and Technol-ogy, China, have developed an intelligent progressive die design system, HPRODIE [12]. With feature mapping, rule-based rea-soning and case-based reasoning techniques, most of the design processes including strip layout design can be carried out auto-matically. Researchers at Pusan National University, Korea, have developed a compact computer-aided process planning (CAPP) system for progressive die design [13]. Based on production rules, the work is capable of carrying out an intelligent stamp-ing process planning work with automatic development of blank layout, strip layout and die layout.
Though knowledge-based systems have achieved a lot of suc-cess in stamping process planning, most of the intelligent pro-gressive die design automation prototypes reviewed above are rather restricted to specific application domains, or still need considerable interactive input from experienced designers to de-velop strip layouts. This is because they still inherit the disadvan-tages of the conventional architecture of knowledge-based expert systems, which are incapable of managing heterogeneous KSs effectively.
Researchers at the National Taiwan Institute of Technology have adopted various AI techniques including fuzzy reasoning, pattern recognition, rule-based reasoning, back-propagation neu-ral network, genetic algorithms and Petri nets for the stamping process planning and design of progressive shearing cut and bending dies [14–16]. However their work lacks an explicit and consistent model to integrate these AI techniques into a compre-hensive design environment.
In this paper, another popular AI technique, blackboard ar-chitecture, is adopted to develop a blackboard-based stamping process planning system. In the last two decades, blackboard ar-chitecture has been successfully used in a wide variety of areas, such as speech recognition, signal processing, engineering de-sign and process planning. Thompson and Lu [17] used a black-board architecture to provide a cooperative decision making en-vironment that is suitable for concurrent product and process design. Srihari et al. [18] developed a real-time CAPP system for printed circuit board (PCB) assembly by integrating multiple KSs, including planning expert and dynamic information pro-cessing modules in the blackboard architecture. Chen et al. [19] developed a concurrent product design evaluation system, using a blackboard architecture to classify knowledge into diverse KSs suitable for qualitative and quantitative evaluation, respectively.
In the past few years, blackboard architecture has proven to be suitable for tooling design such as fixture design [20] and in-jection moulding design [21], though this kind of application is still in its infancy stage. Roy and Liao [20] report the preliminary work that investigates the suitability of using a blackboard archi-tecture as a [K1]problem solving model for fixture design. It de- scribes the creation of various functional KSs for fixture design and their organization in a cooperative problem solving environ-ment. Kwong et al. [21] proposes a blackboard-based system for concurrent process design of injection moulding, which facili-tates the simultaneous considerations of moulding part design, tool design, machine-selection, production scheduling, and cost as early as possible in the conceptual design stage. However, we have not found in the literature any attempt to apply the blackboard architecture to stamping process planning for sheet metal parts. It has been mentioned in our earlier work [22] that a blackboard architecture is well suited for constructive prob-lem solving, like process planning of stamping operations, where the problem space is large and knowledge from many different sources must be integrated to achieve a solution. This topic is now to be extensively elaborated in the present paper.
3.Blackboard framework for stamping process planning
Cooperative decision making for knowledge-based stamping process planning involves a variety of KSs such as unfolding knowledge to produce flat pattern, nesting knowledge to produce blank layout, mapping knowledge to transform stamping features into stamping operations, and staging knowledge to sequence the stamping operations. These KSs may be expressed in different representation schemes such as procedures, rules, and objects. This justifies the use of a blackboard framework that can man- age heterogeneous KSs effectively. The KSs interact through the blackboard to develop a solution incrementally.
The proposed blackboard framework consists of three major components: the blackboard data structure, KSs, and a control module (Fig. 1), and was developed using object-oriented expert system shell CLIPS. The different components of the blackboard framework are described as follows.
3.1 Object-oriented blackboard data structure
The blackboard is a globally accessible database, which con-tains the data and partial solutions and is shared by a number of independent KSs. The KSs contribute their partial solutions to the blackboard, which lead to a final solution incrementally. The blackboard is structured as a hierarchy of solution parti-tion levels, which represent different aspects or stages of the solution process. Partial solutions are associated with each level and may be linked to information on other levels using algorith-mic procedures or heuristic rules. Each level contains planning objects that are used to represent the solution space in an object-oriented manner. This leads to the added advantage in knowledge system development because object-oriented approach supports software modularity, reusability, and scalability.
Referring to Fig. 1, the planning solution is partitioned into four different object levels: stamping part, stamping features, stamping operations, and stamping process plan, each represent-ing initial input or different partial solutions posted on the black-board by the specialist KSs. They are described as follows.
3.1.1 Input data to the blackboard
Input data to the blackboard mainly includes the part and press ob-jects. The generic declaration of a part object includes the basic attributes such as part type, part dimensions, weight, surface treat-ments, blank thickness, blank material, annual production, blank dimensions, etc., and points to its constituent stamping feature ob-jects that will be elaborated later on. The press object contains the attributes such as press type, press tonnage, bolster dimensions, bed open dimensions, shut height, number of strokes, etc.
3.1.2 Object-oriented feature modeling to stamped metal parts
Since traditional geometric modeling techniques do not capture design intent (e.g., design for manufacturing), they are in gen-eral unable to support sophisticated and intelligent reasoning capabilities, e.g., knowledge-based process planning. Recently, the concept of machining features has been introduced to cre-ate a direct link between design and manufacturing [23]. Feature modeling is a relatively new way of storing design and manu-facturing information in CAD/CAM/CAPP systems. Similarly, stamping features of a stamped metal part can enable stamping process planning tasks to be performed directly from the geo-metric model. Stamping features are information carriers that are used to model a stamped part with a set of design and manu-facturing information including geometric and non-geometric at-tributes. Each of these stamping features can be manufactured with a specific stamping operation or a combination of stamping operations.
Using the hierarchical classification structure of general de-sign features by Chen et al. [24], a stamped metal part can be modeled with four categories of stamping features:
Primary features: flat, drawing, etc.;
Positive secondary features: tab, curl, emboss, hem, bead, flange, etc.;
Negative secondary features: hole, extrusion hole, profile, de-form, slot, step, etc.; andConnective secondary features: bend, blend, etc.
In this work, the object-oriented feature representation is em-ployed to encapsulate design and manufacturing information in a stamping feature object. For example, a hole feature object contains the basic attributes such as feature type, feature ID, pri-mary feature ID, position, orientation, depth, diameter, precision, roughness, etc., and methods to calculate perimeter.
Besides representation of individual stamping features, a comprehensive representation of feature relations guarantees that all the stamping features associated with stamping process planning are considered. In addition, the data on feature relations are useful for determining the sequence of stamping operations and sometimes the stamping operations themselves. Four criti-cal types of relations among stamping features – “is-in”, “is-on”, “adjacent-to” and “precision-associated” are identified, which have been elaborated in our previous work [25] and won’t be repeated in this paper for conciseness. For example, a precision-associated relation represents design constraints that arise when a stamping feature does not directly connect to, but is associ-ated with, another stamping feature by a toleranced dimension. The feature relation data is also included in the feature object for more complete feature modeling.
3.1.3 Stamping operation objects mapped from stamping feature objects
On the blackboard, the stamping operation objects are in a lower level than the stamping feature objects, and are used to define the manufacturing process from metal strip to the formed metal part. Stamping features constitute a stamped part, while stamp-ing operations are selected as elements of a stamping process plan. Essentially, the stamping process planning task is to trans-form a set of stamping features into a set of stamping opera-tions, and to describe the relations between these. The generic declaration of a stamping operation object includes stamping op-eration type, geometric shapes, geometric constraints, precision, roughness, relationships with stamping features, control param-eters, etc. Typical stamping operation objects include piercing, notching, cut-off, blanking, lancing, shaving, drawing, emboss-ing, coining, trimming, and other miscellaneous forming opera-tions. A stamping feature may be manufactured with a specific stamping operation (one-to-one mapping) or a combination of stamping operations (one-to-many mapping). Several stamping features may also be manufactured with a single stamping oper-ation (many-to-one mapping).
3.1.4 Graph-based stamping process plan
After the mapping from stamping features to a set of stamping operations, the remaining process planning task is to assign each stamping operation to the relevant die station according to an op-timal sequence of stamping operations. Stamping operations are sequenced in a progressive manner by creating stamping opera-tion relations and using them to form a stamping process plan. This formal description of operation relations forms the founda-tion of automatic strip layout design.
A graph-based approach is used to arrange the stamping op-eration objects in a stamping process plan. The graph consists of a set of nodes that store information about the stamping opera-tions, and a set of arcs that store information about the operation relations. Stamping operations are related to one another through two kinds of relationship, “cluster” or “precedence” relations. Cluster stamping operations are executed simultaneously and can be staged at the same die station. Stamping operations in prece-dence must be performed in sequence and so they are staged in adjacent die stations. Cluster relation, and precedence rela-tion are represented by dashed ellipses and directed solid line, respectively, as shown in Fig. 2. Note that stamping operations B and C work simultaneously, and are staged at the same die station, while stamping operation A precedes operation B, and is staged in a die station immediately prior to the one for the operation B.
The strip layout can be generated by a computer automat-ically using the graph-based stamping process plan, which is suited for computer implementation and leads to efficient formu-lation and solution procedures.
以沖壓工藝規(guī)劃知識進行的級進模設計
摘 要
人們普遍認為沖壓工藝規(guī)劃的布局是級進模設計中的關鍵任務。有史以來，沖壓工藝規(guī)劃是一門藝術，而不是一門科學。雖然人工智能在將內置的智能和應用多樣化的知識窗臺解決這類問題已經取得了很多最新進展。而現(xiàn)在主要的困難是，現(xiàn)有的基于知識的專家系統(tǒng)—沖壓工藝規(guī)劃缺乏適當?shù)募軜嫿M織異構知識源（KSS）的合作決策EN-vironment。本文提出了沖壓工藝規(guī)劃知識型面板框架。建議AP-proach通過自動售貨機 - 荷蘭國際集團的帶狀布局設計，加快了級進模設計過程。
關鍵詞：基于知識 面向對象 級進模具設計 沖壓工藝規(guī)劃
1.引言
級進模在大眾中生產鈑金件已被廣泛應用于各種行業(yè)，如航空航天，電子，機床，汽車。這些模具可在一次裝夾完成穿孔，開槽，切斷，落料，彎曲，刮，拉絲，浮雕，修剪，和