http://kadhoai.com.cn 2026-04-14 17:11:50 來源:ADI
摘要
本文將審視當今製造業麵臨的核心挑戰,探索正在席卷行業的變革浪潮。這場變革源於對資源敏感型製造的全新關注,而人工智能、分散式控製、混合組網及軟件定義自動化等新技術與能力協同發力,共同為未來數字化工廠的崛起築牢根基。
製造業麵臨的挑戰
zhizaoyezhengchuyuyichangzhuanxinglangchaozhizhong,xiaofeizheduigexinghuachanpinxuqiudezengchang,jiazhiyiqinghougongyinglianweijicuishengdechanyehuiliuqushideng,chengweituidongzheyibiangedezhuyaoqudongli。erzhexie,jinjinshizhongduotiaozhanzhongdebingshanyijiao。yucitongshi,quanqiugeguozhengfuyefenfenchutaixiangguanfagui,yijianshaozhizaoyedetanpaifang,congershixianwenshiqitijinglingpaifangmubiao。yingduizhexietiaozhanjiangweigongyezhizaoqiyekaipiquanxindefazhansaidao,qiyekejieciqijiyinruqianyanjishu,zaijiangditanpaifangdetongshi,tigaozhizaoyedeshengchanxiaolv、可擴展性和靈活性。
zairujinjiyoudezhizaogongchangnei,zhizaoshebeiyuzidonghuashebeilijingduonianfanfubushuyukuozhan,hucaozuoxingwentiriyituxian。shebeijianbujinnanyishunchangxietongyunzuo,xianghujiandelianjieyejiweiyouxian,daozhigongchangneibupubianquefanengguantongsuoyouzidonghuashebeidetongyiwangluo。
隨著新產品庫存單位(SKU)數shu量liang持chi續xu攀pan升sheng,生sheng產chan線xian的de設she置zhi與yu驗yan證zheng時shi間jian不bu得de不bu相xiang應ying增zeng加jia。在zai醫yi療liao器qi械xie製zhi造zao領ling域yu,驗yan證zheng流liu程cheng不bu僅jin耗hao時shi漫man長chang,成cheng本ben也ye十shi分fen高gao昂ang。此ci外wai,產chan品pinSKU的增多還會拉低設備綜合效率(OEE),原yuan因yin在zai於yu額e外wai投tou入ru的de設she置zhi和he驗yan證zheng會hui造zao成cheng生sheng產chan時shi間jian的de浪lang費fei,進jin而er導dao致zhi生sheng產chan效xiao率lv下xia滑hua。製zhi造zao業ye麵mian臨lin的de挑tiao戰zhan不bu止zhi於yu此ci,熟shu練lian工gong人ren短duan缺que問wen題ti同tong樣yang嚴yan峻jun。據ju預yu測ce,截jie至zhi2030年,製造業熟練工人缺口將高達約210萬人。1 當下,多數製造活動集中於既有工廠;zaicibeijingxia,qiyeshituzaixianyouchangfangkongjianneitishengchannengshi,laodonglibuzudewentibianchengweichannengtishengdeguanjianzhiyueyinsu。weilaishuzihuagongchangzhengshiweigongkeshangshuzhongzhongtiaozhanersheng,zhiliyutuidongzhizaoyemairuquanxindefazhanjiyuan(見圖1)。

圖1.工業製造麵臨的挑戰。
工業製造業的轉型
從cong技ji術shu角jiao度du來lai看kan,製zhi造zao業ye已yi取qu得de重zhong大da進jin步bu。例li如ru,通tong過guo在zai製zhi造zao資zi產chan和he設she備bei上shang增zeng加jia傳chuan感gan器qi部bu署shu並bing進jin行xing融rong合he,可ke生sheng成cheng豐feng富fu的de數shu據ju集ji,用yong於yu優you化hua機ji器qi並bing提ti高gao設she備bei綜zong合he效xiao率lv(OEE)。軟件定義自動化的部署提升了製造業的生產效率、靈活性和可擴展性,大幅縮短了設置與驗證時間。此外,人工智能(AI)正(zheng)逐(zhu)步(bu)向(xiang)邊(bian)緣(yuan)側(ce)發(fa)展(zhan),更(geng)加(jia)靠(kao)近(jin)傳(chuan)感(gan)器(qi)或(huo)執(zhi)行(xing)器(qi)等(deng)生(sheng)成(cheng)數(shu)據(ju)的(de)終(zhong)端(duan)。邊(bian)緣(yuan)人(ren)工(gong)智(zhi)能(neng)將(jiang)借(jie)助(zhu)數(shu)據(ju)驅(qu)動(dong)的(de)決(jue)策(ce)方(fang)式(shi),把(ba)製(zhi)造(zao)數(shu)據(ju)轉(zhuan)化(hua)為(wei)切(qie)實(shi)可(ke)行(xing)的(de)見(jian)解(jie),助(zhu)力(li)自(zi)主(zhu)製(zhi)造(zao)實(shi)現(xian)製(zhi)造(zao)業(ye)生(sheng)產(chan)效(xiao)率(lv)與(yu)競(jing)爭(zheng)力(li)的(de)躍(yue)升(sheng)(見圖2)。

圖2.製造業的轉型。
資源感知型製造
下一代製造業需要更全麵地審視資源消耗的各個方麵。製造業所需的四大關鍵資源分別是資金、電力、材(cai)料(liao)和(he)人(ren)力(li)。在(zai)資(zi)源(yuan)感(gan)知(zhi)型(xing)製(zhi)造(zao)的(de)背(bei)景(jing)下(xia),未(wei)來(lai)數(shu)字(zi)化(hua)工(gong)廠(chang)亟(ji)待(dai)提(ti)升(sheng)對(dui)這(zhe)些(xie)資(zi)源(yuan)的(de)利(li)用(yong)效(xiao)率(lv)。在(zai)資(zi)金(jin)效(xiao)率(lv)方(fang)麵(mian),所(suo)有(you)製(zhi)造(zao)領(ling)域(yu)的(de)資(zi)本(ben)支(zhi)出(chu)都(dou)應(ying)注(zhu)重(zhong)實(shi)現(xian)投(tou)資(zi)回(hui)報(bao)率(lv)(ROI),周期可能為一年、三(san)年(nian)或(huo)五(wu)年(nian)不(bu)等(deng)。未(wei)來(lai)數(shu)字(zi)化(hua)工(gong)廠(chang)的(de)關(guan)鍵(jian)目(mu)標(biao)之(zhi)一(yi),便(bian)是(shi)以(yi)最(zui)少(shao)的(de)資(zi)本(ben)支(zhi)出(chu)實(shi)現(xian)利(li)潤(run)最(zui)大(da)化(hua),進(jin)而(er)獲(huo)得(de)最(zui)高(gao)的(de)投(tou)資(zi)回(hui)報(bao)率(lv)。其(qi)次(ci)是(shi)電(dian)力(li)效(xiao)率(lv),下(xia)一(yi)代(dai)製(zhi)造(zao)業(ye)必(bi)須(xu)以(yi)更(geng)低(di)的(de)能(neng)耗(hao)實(shi)現(xian)更(geng)高(gao)的(de)產(chan)出(chu),達(da)成(cheng)減(jian)少(shao)全(quan)球(qiu)碳(tan)排(pai)放(fang)的(de)目(mu)標(biao)。降(jiang)低(di)電(dian)力(li)消(xiao)耗(hao)的(de)關(guan)鍵(jian)舉(ju)措(cuo)包(bao)括(kuo):部署高效電機驅動器,將氣動驅動替換為機電驅動,運用自適應閉環控製技術提升製造效率,等等。
資(zi)源(yuan)感(gan)知(zhi)型(xing)製(zhi)造(zao)的(de)第(di)三(san)個(ge)方(fang)麵(mian)是(shi)材(cai)料(liao)效(xiao)率(lv)。在(zai)提(ti)升(sheng)製(zhi)造(zao)業(ye)可(ke)持(chi)續(xu)性(xing)方(fang)麵(mian),減(jian)少(shao)材(cai)料(liao)浪(lang)費(fei)與(yu)降(jiang)低(di)能(neng)源(yuan)消(xiao)耗(hao)同(tong)等(deng)重(zhong)要(yao),發(fa)揮(hui)著(zhe)不(bu)可(ke)或(huo)缺(que)的(de)作(zuo)用(yong)。通(tong)過(guo)最(zui)大(da)限(xian)度(du)地(di)減(jian)少(shao)原(yuan)材(cai)料(liao)的(de)使(shi)用(yong),再(zai)結(jie)合(he)加(jia)強(qiang)生(sheng)產(chan)質(zhi)量(liang)控(kong)製(zhi),能(neng)夠(gou)顯(xian)著(zhu)減(jian)少(shao)整(zheng)個(ge)製(zhi)造(zao)流(liu)程(cheng)中(zhong)的(de)材(cai)料(liao)浪(lang)費(fei),最(zui)終(zhong)朝(chao)著(zhe)零(ling)廢(fei)棄(qi)生(sheng)產(chan)的(de)目(mu)標(biao)邁(mai)進(jin)。最(zui)後(hou)一(yi)個(ge)方(fang)麵(mian)是(shi)人(ren)力(li)效(xiao)率(lv),亦(yi)是(shi)重(zhong)中(zhong)之(zhi)重(zhong)。當(dang)前(qian),製(zhi)造(zao)業(ye)在(zai)招(zhao)聘(pin)熟(shu)練(lian)工(gong)人(ren)方(fang)麵(mian)存(cun)在(zai)諸(zhu)多(duo)挑(tiao)戰(zhan)。製(zhi)造(zao)業(ye)必(bi)須(xu)盡(jin)可(ke)能(neng)地(di)減(jian)少(shao)人(ren)為(wei)介(jie)入(ru),可(ke)采(cai)取(qu)的(de)方(fang)式(shi)包(bao)括(kuo):推廣自主製造模式,應用先進機器人技術,部署具備實時感知能力、能快速響應操作環境與製造需求變化的自動化解決方案(見圖3)。

圖3.資源感知型製造。
未來數字化工廠
ADI公司對未來數字化工廠的願景,聚焦於連接、控製和解讀這三大核心支柱。連接戰略旨在通過提升製造業生產效率、可ke擴kuo展zhan性xing和he靈ling活huo性xing,同tong時shi降jiang低di碳tan排pai放fang,來lai達da成cheng未wei來lai工gong廠chang的de發fa展zhan藍lan圖tu。確que保bao所suo有you製zhi造zao資zi產chan和he機ji器qi連lian接jie到dao統tong一yi網wang絡luo,實shi現xian製zhi造zao數shu據ju的de透tou明ming訪fang問wen,並bing利li用yong這zhe些xie數shu據ju推tui動dong整zheng個ge製zhi造zao場chang所suo的de工gong藝yi持chi續xu改gai進jin。製zhi造zao環huan境jing須xu借jie助zhu有you線xian和he無wu線xian混hun合he網wang絡luo,實shi現xian從cong邊bian緣yuan到dao雲yun端duan的de實shi時shi無wu縫feng連lian接jie。對dui於yu有you線xian控kong製zhi連lian接jie,千qian兆zhao位wei工gong業ye以yi太tai網wang正zheng被bei部bu署shu用yong於yu工gong廠chang網wang絡luo以yi提ti供gong更geng高gao的de帶dai寬kuan,同tong時shi搭da配pei時shi間jian敏min感gan型xing網wang絡luo(TSN)來確保實時流量控製的確定性。對於諸如自主移動機器人(AMR)等移動應用,靈活的專用5G網絡起到補充作用,並且專用5G網絡還可連接難以輕鬆接入有線工業以太網的遠程傳感器和執行器。
第(di)二(er)項(xiang)關(guan)鍵(jian)戰(zhan)略(lve)聚(ju)焦(jiao)於(yu)控(kong)製(zhi)領(ling)域(yu)。分(fen)散(san)式(shi)自(zi)主(zhu)控(kong)製(zhi)依(yi)托(tuo)全(quan)新(xin)的(de)模(mo)塊(kuai)化(hua)自(zi)動(dong)化(hua)解(jie)決(jue)方(fang)案(an),帶(dai)來(lai)更(geng)高(gao)的(de)靈(ling)活(huo)性(xing),既(ji)能(neng)縮(suo)短(duan)設(she)置(zhi)和(he)驗(yan)證(zheng)時(shi)間(jian),又(you)能(neng)支(zhi)持(chi)日(ri)益(yi)增(zeng)長(chang)的(de)新(xin)產(chan)品(pin)庫(ku)存(cun)單(dan)位(wei)(SKU)。從傳統生產線的集中式可編程邏輯控製器(PLC)轉向分散式PLC控(kong)製(zhi),先(xian)進(jin)的(de)邊(bian)緣(yuan)計(ji)算(suan)將(jiang)被(bei)直(zhi)接(jie)集(ji)成(cheng)到(dao)機(ji)器(qi)之(zhi)中(zhong)。基(ji)於(yu)邊(bian)緣(yuan)的(de)自(zi)主(zhu)控(kong)製(zhi)讓(rang)生(sheng)產(chan)線(xian)更(geng)具(ju)可(ke)重(zhong)構(gou)性(xing),顯(xian)著(zhu)提(ti)升(sheng)製(zhi)造(zao)靈(ling)活(huo)性(xing)。每(mei)一(yi)台(tai)機(ji)器(qi)都(dou)成(cheng)為(wei)一(yi)個(ge)完(wan)整(zheng)獨(du)立(li)的(de)模(mo)塊(kuai)化(hua)製(zhi)造(zao)單(dan)元(yuan),可(ke)在(zai)極(ji)少(shao)人(ren)為(wei)介(jie)入(ru)的(de)情(qing)況(kuang)下(xia),輕(qing)鬆(song)完(wan)成(cheng)配(pei)置(zhi)與(yu)重(zhong)新(xin)部(bu)署(shu)。通(tong)過(guo)部(bu)署(shu)更(geng)多(duo)靈(ling)活(huo)、模塊化的製造解決方案,並由分散式自主控製予以支持,我們能夠更好地實現未來數字化工廠的目標。
zuihouyixiangzhanlvejujiaoyujiedu。jieduzhanlvezhizaijiangshengchanshujuzhuanhuaweikefuzhushijiandedongchaxinxi,congerzhulishixianweilaigongchangdegexiangmubiao。jugusuan,zhizaoyemeinianchanshengdeshujuliangyueda1812 PB(拍字節)。2 解(jie)讀(du)戰(zhan)略(lve)將(jiang)運(yun)用(yong)人(ren)工(gong)智(zhi)能(neng)技(ji)術(shu)來(lai)處(chu)理(li)這(zhe)些(xie)海(hai)量(liang)製(zhi)造(zao)數(shu)據(ju),以(yi)提(ti)升(sheng)生(sheng)產(chan)效(xiao)率(lv)。解(jie)讀(du)戰(zhan)略(lve)的(de)關(guan)鍵(jian)在(zai)於(yu)在(zai)數(shu)據(ju)產(chan)生(sheng)的(de)邊(bian)緣(yuan)側(ce)部(bu)署(shu)人(ren)工(gong)智(zhi)能(neng)。邊(bian)緣(yuan)人(ren)工(gong)智(zhi)能(neng)將(jiang)通(tong)過(guo)主(zhu)動(dong)決(jue)策(ce),結(jie)合(he)傳(chuan)感(gan)器(qi)融(rong)合(he)(包含工業視覺、溫度、壓力/力、測斜儀、位置、振動、濕度等測量方式),實shi現xian製zhi造zao業ye的de自zi主zhu優you化hua。邊bian緣yuan人ren工gong智zhi能neng將jiang通tong過guo自zi動dong執zhi行xing常chang規gui任ren務wu,減jian少shao對dui熟shu練lian勞lao動dong力li的de依yi賴lai,並bing以yi盡jin可ke能neng高gao的de良liang品pin率lv實shi現xian更geng具ju個ge性xing化hua和he複fu雜za性xing的de製zhi造zao。關guan鍵jian應ying用yong包bao括kuo引yin導dao驅qu動dong(移動機器人)、缺陷或異常檢測(機器健康狀況)、持續的工藝改進、模式識別(質量控製),最終還將融入自動化控製循環,成為其中重要一環。

圖4.實現未來數字化工廠的幾點關鍵要求。
結論
製造業正在經曆一場變革,朝著更智能、更互聯、以(yi)軟(ruan)件(jian)定(ding)義(yi)為(wei)主(zhu)的(de)方(fang)向(xiang)發(fa)展(zhan)。實(shi)時(shi)無(wu)縫(feng)的(de)邊(bian)緣(yuan)到(dao)雲(yun)端(duan)連(lian)接(jie),將(jiang)實(shi)現(xian)對(dui)新(xin)型(xing)製(zhi)造(zao)數(shu)據(ju)集(ji)的(de)透(tou)明(ming)化(hua)訪(fang)問(wen)。分(fen)散(san)式(shi)控(kong)製(zhi)借(jie)助(zhu)邊(bian)緣(yuan)計(ji)算(suan),將(jiang)控(kong)製(zhi)功(gong)能(neng)從(cong)可(ke)編(bian)程(cheng)邏(luo)輯(ji)控(kong)製(zhi)器(qi)(PLC)遷移至機器本身。傳感器融合技術的應用提升了機器的設備綜合效率(OEE),bingchanshengfengfudeshujuji,weirengongzhinengmoxingdexunlianyubushutigongzhicheng。bianyuanrengongzhinengjiangshizidonghuajiqiwanquanshixianzizhuhua。zhexiexinjishuderongheshibijiangchedigaibianweilaideshuzihuagongchang,zaixianzhujiangdinengyuanxiaohaohecailiaolangfeidetongshi,tigaozhizaoyedeshengchanxiaolv、linghuoxinghekekuozhanxing。duiyuzhizaoshangeryan,chenggongdeguanjianzaiyuruheyushengtaixitongneideqitagongsizhankaihezuo,yinweifengfuduoyangdejingyanhenengliduiyujiasushixianweilaishuzihuagongchangdeyuanjingzhiguanzhongyao。ruxujinyibulejieADI針對未來數字化工廠的可持續自動化解決方案,請訪問
analog.com/industrialautomation。
參考文獻
1 Victor Reyes、Heather Ashton和Chad Moutray,“Creating Pathways for Tomorrow’s Workforce Today:Beyond Reskilling in Manufacturing”,Deloitte Insights,美國製造業研究所,2021年5月。
2 “Deloitte Survey on AI Adoption in Manufacturing”,Deloitte,2020年。