TWI806148B - Material handling method based on digital twin - Google Patents
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本案屬於物料處理的領域,尤指一種物料處理方法與物料處理系統。This case belongs to the field of material handling, especially a material handling method and material handling system.
目前工業界一直努力藉由整合輸送系統、龍門型機器手臂(Gantry robot)和旋轉式貨架(Carousel)等自動化設施來構成物料處理系統,以提高工廠物流的效率,上設這些自動化設施旨在降低在生產過程中所需使用的物料的勞動力成本和交貨時間。在當今的許多表面貼合技術 (Surface Mount Technology, SMT) 製造工藝中,也可以找到此類設施,藉由這些設施將需放置在印刷電路板上的不同類型的元器件交付到組裝產線。在表面貼合技術製造工藝中,自動導引車(Automatic Guided Vehicle,AGV)亦已被研發進行工廠貨物之搬運與整理,由於現行的自動導引車具有自動化、高效率,以及不易出錯等諸多優點,已廣泛應用於使用物料處理系統的工廠物流中。At present, the industry has been trying to form a material handling system by integrating automation facilities such as conveyor systems, gantry robots, and carousels to improve the efficiency of factory logistics. These automation facilities are designed to reduce The labor cost and lead time of the materials used in the production process. Such facilities can also be found in many of today's Surface Mount Technology (SMT) manufacturing processes, whereby different types of components to be placed on printed circuit boards are delivered to the assembly line. In the manufacturing process of surface bonding technology, automatic guided vehicles (AGV) have also been developed for the handling and arrangement of factory goods. Because the current automatic guided vehicles are automated, high-efficiency, and less prone to errors, etc. Advantages, it has been widely used in factory logistics using material handling systems.
然而,傳統物料處理系統通常根據環境的變化(如交付的專案類型及/或製造車間的佈局等)而被動對對應的自動化設施的運作方式進行更新及修改,造成成本升高,更甚者,傳統物料處理系統更存在高昂的維護成本的問題,綜上,傳統物料處理系統實難以適應瞬息萬變的市場。However, traditional material handling systems usually passively update and modify the operation mode of the corresponding automation facilities according to changes in the environment (such as the type of project delivered and/or the layout of the manufacturing workshop, etc.), resulting in increased costs, and even worse, Traditional material handling systems also have the problem of high maintenance costs. In summary, traditional material handling systems are difficult to adapt to the ever-changing market.
現在許多的製造業都與創建所謂的網路物理系統 (cyber-physical systems , CPS) 的軟體技術和算法緊密相連。 隨著最近數位孿生(Digital Twin)概念的出現,物理(工廠)和網路(軟體)互連之間的差距已顯著縮小,藉由運用數位孿生便可在數位空間中即時、雙向地描繪真實運作,達到優化運作效率的目的。Much of manufacturing is now closely tied to the software technologies and algorithms that create so-called cyber-physical systems (CPS). The gap between physical (factory) and network (software) interconnections has narrowed significantly with the recent emergence of the concept of a digital twin, which enables real-time, bi-directional representations of reality in digital space operation to achieve the purpose of optimizing operational efficiency.
因此本案即基於將數字孿生的技術應用在為表面貼合技術的材料的概念而提出,以改善前述傳統物料處理系統的缺失,更達成前述傳統物料處理無法達成的功效。Therefore, this case is proposed based on the concept of applying digital twin technology to materials for surface bonding technology, in order to improve the lack of the aforementioned traditional material handling system, and to achieve the effect that the aforementioned traditional material handling cannot achieve.
本案之目的在於提供一種物料處理方法與物料處理系統,其可達到即時且在線處理應用於表面貼合技術的物料,且能因應產品訂單表的變化動態地改變路線規劃,並能因應移動式貨架而規劃路線,並依照工廠實時數據提供預測以及最佳化。The purpose of this case is to provide a material processing method and material processing system, which can achieve real-time and online processing of materials applied to surface bonding technology, and can dynamically change route planning in response to changes in product order forms, and can respond to mobile shelves. And plan the route, and provide prediction and optimization according to the real-time data of the factory.
本案之目的在於提供一種物料的處理方法與物料處理系統,其係無須昂貴的安裝成本、維護成本及更新及修改的成本,且無須漫長的安裝時間和複雜的軟體系統。The purpose of this case is to provide a material processing method and material processing system, which do not require expensive installation costs, maintenance costs, update and modification costs, and do not require long installation time and complicated software systems.
為達前述之目的,本案的一較佳實施態樣提供一種物料處理方法,應用於工廠中的物料處理系統中,其中物料處理系統對應用於表面貼合技術的物料進行處理,且包含可移動機器人、控制可移動機器人之車隊管理系統及數位孿生建構單元,物料處理方法包含:執行物料處理程序,包含:(a)輸入產品訂單表至車隊管理系統;(b)車隊管理系統依據產品訂單表生成導航計畫表,並控制可移動機器人依據導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對物料進行處理;(c)數位孿生建構單元接收即時感測到的關於工廠的實時物理參數,以進行初始化運作,進而依據實時物理參數建立數位孿生模型;(d)利用數位孿生模型模擬可移動機器人執行導航計畫表的結果,以對應產生第一模擬結果;(e)將第一模擬結果提供給車隊管理系統;(f)車隊管理系統評估第一模擬結果是否符合預期條件;以及(g)當步驟(f)中車隊管理系統評估模擬結果符合預期條件時,則重新執行步驟(c),當步驟(f)中車隊管理系統評估模擬結果不符合預期條件時,車隊管理系統調整導航計畫表,並控制可移動機器人依據調整後的導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對物料進行處理。In order to achieve the above-mentioned purpose, a preferred implementation aspect of this case provides a material processing method, which is applied to the material processing system in the factory, wherein the material processing system processes the materials used in surface bonding technology, and includes movable The robot, the fleet management system controlling the mobile robot and the digital twin construction unit, the material processing method includes: executing the material processing program, including: (a) inputting the product order form to the fleet management system; (b) the fleet management system according to the product order form Generate a navigation plan, and control the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan to process materials; (c) the digital twin construction unit receives real-time sensed information about the factory Real-time physical parameters for initialization operation, and then establish a digital twin model based on the real-time physical parameters; (d) use the digital twin model to simulate the results of the mobile robot executing the navigation plan to generate the first simulation result; (e) The first simulation result is provided to the fleet management system; (f) the fleet management system evaluates whether the first simulation result meets the expected condition; and (g) when the fleet management system evaluates the simulation result in step (f) meets the expected condition, then re Execute step (c), when the fleet management system in step (f) evaluates that the simulation result does not meet the expected conditions, the fleet management system adjusts the navigation plan, and controls the mobile robot to move according to the adjusted navigation plan Move and operate according to the path and operation mode to process the material.
為達前述之目的,本案的另一較佳實施態樣提供一種物料處理系統,應用於工廠中,用以對應用於表面貼合技術的物料進行處理,且包含:至少一可移動機器人;車隊管理系統,用以根據產品訂單表生成導航計畫表,並控制可移動機器人依據導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對對物料進行處理;以及數位孿生建構單元,用以接收即時感測到的關於工廠的實時物理參數,並依據實時物理參數建立數位孿生模型;其中在可移動機器人對物料進行處理的過程中,數位孿生建構單元利用數位孿生模型模擬可移動機器人執行導航計畫表的結果,以對應產生第一模擬結果,而車隊管理系統評估第一模擬結果是否符合預期條件,並於第一模擬結果不符合預期條件實,調整導航計畫表,並控制可移動機器人依據調整後的導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對物料進行處理。In order to achieve the aforementioned purpose, another preferred embodiment of this case provides a material handling system, which is used in factories to process materials used in surface bonding technology, and includes: at least one mobile robot; The management system is used to generate a navigation plan table according to the product order form, and control the mobile robot to move and operate according to the movement path and operation mode planned by the navigation plan table, so as to process the materials; and the digital twin construction unit , to receive the real-time physical parameters of the factory sensed in real time, and establish a digital twin model based on the real-time physical parameters; where in the process of the mobile robot processing materials, the digital twin construction unit uses the digital twin model to simulate the mobile The robot executes the results of the navigation plan to generate the first simulation result correspondingly, and the fleet management system evaluates whether the first simulation result meets the expected conditions, and adjusts the navigation plan when the first simulation result does not meet the expected conditions, and Control the mobile robot to move and operate according to the movement path and operation mode planned by the adjusted navigation plan, so as to process the materials.
體現本案特徵與優點的一些典型實施例將在後段的說明中詳細敘述。應理解的是本案能夠在不同的態樣上具有各種的變化,其皆不脫離本案的範圍,且其中的說明及圖示在本質上當作說明之用,而非架構於限制本案。Some typical embodiments embodying the features and advantages of the present application will be described in detail in the description in the following paragraphs. It should be understood that this case can have various changes in different aspects, all of which do not depart from the scope of this case, and the descriptions and diagrams therein are used for illustration in nature, rather than to limit this case.
請參閱第1圖及第2圖,其中第1圖為本案較佳實施例之物料處理系統之系統架構示意圖,第2圖為第1圖所示之物料處理系統的控制架構示意圖。如第1圖及第2圖所示,本案之物料處理系統100可為但不限應用於工廠中,其中工廠中放置例如但不限於應用於表面貼合技術的物料,且物料包含各種不同尺寸及不同重量之應用於表面貼合技術的元件卷軸(reel),而物料處理系統100可輸入產品訂單表,並依據產品訂單表對工廠中的物料進行傳遞及處理。物料處理系統100包含具有複數種配置的緩衝區(buffer area)101、至少一可移動機器人、移動式貨架106、生產單元107、複數個生產線108、車隊管理系統(Fleet Management System)110及數位孿生建構單元111。產品訂單表上可為但不限於紀錄各種物料排列順序、所選擇的生產線108、物料抵達至所選擇的生產線108的截止時間及送到所選擇之生產線108的物料的形式和重量等。另外,可移動機器人可為複數個,例如第1圖所示的複數個可移動機器人分別為包含具有不同工具(或分別為不同型態)的複數個自主移動機器人(Automated Mobile Robot, AMR)102、103及相同或不同尺寸的自動導引車104、105。Please refer to Figure 1 and Figure 2, wherein Figure 1 is a schematic diagram of the system architecture of the material handling system in a preferred embodiment of this case, and Figure 2 is a schematic diagram of the control structure of the material handling system shown in Figure 1. As shown in Figure 1 and Figure 2, the
生產單元107用以提供物料。複數個生產線108則可分別對所接收到的物料進行處理、加工等作業程序,以完成最終的實體產品。移動式貨架106可在工廠車間的不同區域之間進行轉移,且移動式貨架106上可容納物料,即元件卷軸,這些元件卷軸將根據請求產品訂單表內的內容轉移到被指定的生產線108。緩衝區101位於生產單元107及生產線108之間,且緩衝區101可放置至少一移動式貨架106。The
自主移動機器人102、103及自動導引車104、105受車隊管理系統110以無線方式進行控制而自動的移動及作動,其中自動導引車104、105可附接到移動式貨架106 上或從移動式貨架106上拆卸,此外,自動導引車104及105分別基於車隊管理系統 110的安排而將緩衝區101內的移動式貨架106運輸至特定的自主移動機器人102、103的附近,或是將在自主移動機器人102、103的附近的移動式貨架106或在工廠其它位置的移動式貨架106運輸至緩衝區101。於一些實施例中, 自動導引車的數量可小於移動式貨架106的數量。車隊管理系統110可輸入產品訂單表,並依據產品訂單表內的紀錄內容生成導航計畫表,其中導航計畫表規劃了讓自主移動機器人102、103及自動導引車104及105自主移動的路徑,藉此自主移動機器人102、103及自動導引車104及105可依據導航計畫表進行對應的自主移動。The autonomous
於一些實施例中,取決於生產訂單表所預定的物料排列順序,故緩衝區101內的移動式貨架106可以先進先出(First-In-First-Out, FIFO)的基礎或任務導向的基礎進行順序排列,其中先進先出的基礎取決於車隊管理系統110依據生產訂單表所記錄的物料先後順序對移動式貨架106進行排列。任務導向的基礎則是基於車隊管理系統110接獲的任務中所規劃的特別優先處理而對移動式貨架106進行排列。In some embodiments, depending on the order in which the materials are arranged in the production order table, the
自主移動機器人102、103基於車隊管理系統110的控制而各自將物料移入/移出緩衝區101內的移動式貨架106,例如,自主移動機器人102可將生產單元107提供之物料移入緩衝區101內的移動式貨架106上,自主移動機器人103可將緩衝區101內的移動式貨架106上的物料移出並傳送至任一生產線108上。此外,每個自主移動機器人102、103實際上由附接移動驅動單元(未圖示)之機械手臂(robot manipulator)所構成。更甚者,自主移動機器人102、103可根據元件卷軸的類型和生產訂單表關於元件卷軸的順序安排而對元件卷軸進行分類。當自主移動機器人102、103 完成元件卷軸的轉移時,鄰近於自主移動機器人102、103附近的移動式貨架106可藉由自動導引車104、105移回緩衝區 101。The autonomous
於一些實施例中,如第2圖所示,物料處理系統100可包含集中式通信中介軟體(centralized communication middleware)109。此外,本案的物料處理系統100依據控制架構可大致區分為三部分,最低階的部分為受控體,即包含自主移動機器人102、103及自動導引車104及105等,中階的部分為信號管理及傳輸,其由集中式通信中介軟體109實現,最高階的部分則為控制體,即包含車隊管理系統110及數位孿生建構單元111。集中式通信中介軟體109傳送及轉換車隊管理系統110所輸出的資料封包及/或控制訊號至自主移動機器人102、103及自動導引車104及105,使得車隊管理系統110可控制自主移動機器人102、103及自動導引車104及105進行對應的操作,此外,集中式通信中介軟體109更將自主移動機器人102、103及自動導引車104及105藉由自身或外加的感測器(未圖示)所感測到的運作參數轉換及傳送至車隊管理系統110及/或數位孿生建構單元111,因此集中式通信中介軟體109實際上管理由車隊管理系統110及數位孿生建構單元111所分別輸出及分別接收的關鍵資訊。數位孿生建構單元111乃是依據所工廠內之各感測器(未圖示)所感測到的實時物理參數(實時物理參數包含工廠內的環境及各個設施等的結構參數及/或運作參數)建立數位孿生模型,且工廠中的實時物理參數與數位孿生建構單元111所建立的數位孿生模型之間存在虛實映射關係,此外數位孿生建構單元111依據實時物理數據進行處理、預測和優化,並根據車隊管理系統110的預設控制立即採取最佳任務安排,並將安排結果通知車隊管理系統110,使車隊管理系統110進行對應的控制與調整。於上述實施例中,數位孿生模型可為但不限於包含自動導引車104、105的數位孿生模型、自主移動機器人102、103的數位孿生及工廠內其它設施的數位孿生模型。In some embodiments, as shown in FIG. 2 , the
請參閱第3圖,並配合第1圖及第2圖,其中第3圖為應用於第1圖所示之物料處理系統中的物料處理方法在執行物料處理程序時的步驟流程圖。如第1圖至第3圖所示,本案之物料處理方法會執行一物料處理程序,該物料處理程序包含步驟如下。Please refer to Figure 3, and cooperate with Figure 1 and Figure 2, wherein Figure 3 is a flow chart of the steps of the material handling method applied in the material handling system shown in Figure 1 when executing the material handling procedure. As shown in Figures 1 to 3, the material handling method in this case will implement a material handling procedure, which includes the following steps.
步驟S200:輸入產品訂單表至車隊管理系統110。Step S200: Input the product order form to the
步驟S201:車隊管理系統110依據產品訂單表生成導航計畫表,並控制可移動機器人(包含自主移動機器人102、103及自動導引車104及105)依據導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對物料進行處理。Step S201: The
步驟202:數位孿生建構單元111接收即時感測到的關於工廠的實時物理參數,以進行初始化運作,進而依據實時物理參數建立數位孿生模型。Step 202: The digital
步驟S203:利用數位孿生模型模擬可移動機器人執行導航計畫表的結果,以對應產生第一模擬結果。Step S203: using the digital twin model to simulate the result of the mobile robot executing the navigation plan, so as to generate a first simulation result correspondingly.
步驟S204:將第一模擬結果提供給車隊管理系統110。Step S204: Provide the first simulation result to the
步驟S205:車隊管理系統110評估第一模擬結果是否符合一預期條件(該預期條件為預設,且預期條件可例如模擬結果滿足產品訂單表所記錄的物料抵達至所選擇的生產線108的截止時間等)。Step S205: The
當於步驟S205中車隊管理系統110評估模擬結果符合預期條件時,則重新執行步驟S202。於一些實施例中,在步驟S205執行完後,會於一設定時間過後才重新執行步驟S202。When the
步驟S206:當於步驟S205中車隊管理系統110評估模擬結果不符合預期條件時,車隊管理系統110調整導航計畫表,並控制可移動機器人依據調整後的導航計畫表所規劃的移動路徑及操作方式進行移動與操作,以對物料進行處理。當步驟S206執行完後,則重新執行步驟S202。於一些實施例中,在步驟S206執行完後,會於設定時間過後才重新執行步驟S202。Step S206: When the
由上可知,本案之物料處理方法跟物料處理系統100可在可移動機器人移動跟操作而對物料進行處理的過程中,同步利用數位孿生建構單元111依據實時物理參數所建立的數位孿生模型來模擬可移動機器人執行導航計畫表的結果,以預測可移動機器人的移動跟操作結果可否符合達成產品訂單表所記錄的內容,並在模擬結果不符合預期條件時,隨時調整導航計畫表而對可移動機器人的移動跟操作進行優化,因此本案之物料處理方法跟物料處理系統可因應各種環境或參數變化,例如產品訂單表的變化及移動式貨架的位置變化等,而動態地對導航計畫表中的路線規劃進行調整,使物料處理系統100可完成產品訂單表所紀錄的內容。另外,藉由數位孿生建構單元111依據實時物理參數所建立的數位孿生模型來進行工廠內的各種行為或參數模擬,本案之物料處理系統100可根據環境的變化而對各設施的運作主動進行調整,故可降低物料處理系統100的維護成本、更新及修改的成本,且無須漫長的安裝時間和複雜的軟體系統。It can be seen from the above that the material processing method and the
請參閱第4圖,並配合第1圖至第4圖,其中第4圖為本案之物料處理方法在執行充電預測程序時的步驟流程圖。如第1圖至第4圖所示,於一些實施例中,本案之物料處理方法更執行充電預測程序,該充電預測程序包含步驟如下。Please refer to Figure 4, and cooperate with Figures 1 to 4, wherein Figure 4 is a flow chart of the steps of the material handling method in this case when performing the charge prediction program. As shown in FIG. 1 to FIG. 4 , in some embodiments, the material processing method of the present application further implements a charge prediction procedure, and the charge prediction procedure includes the following steps.
步驟S300:於實時物理參數反映出任一可移動機器人的當前電量等於或小於一第一預設電量門檻值而處於一低電量狀態時,利用數位孿生模型依據實時物理參數模擬處於低電量狀態的可移動機器人移動至導航計畫表所規劃的移動路徑的終點。Step S300: When the real-time physical parameters reflect that the current power of any mobile robot is equal to or less than a first preset power threshold and is in a low power state, use the digital twin model to simulate the mobile robot in the low power state according to the real-time physical parameters The mobile robot moves to the end point of the movement path planned by the navigation plan table.
步驟S301:利用數位孿生模型模擬處於低電量狀態的可移動機器人從移動路徑的終點朝充電站移動,並產生第二模擬結果。Step S301: using the digital twin model to simulate the movement of the mobile robot in a low battery state from the end of the movement path towards the charging station, and generating a second simulation result.
步驟S302:將第二模擬結果提供給車隊管理系統110,使車隊管理系統110依據第二模擬結果評估低電量狀態的可移動機器人依據剩餘電量是否可從移動路徑的終點移動至充電站。Step S302: Provide the second simulation result to the
步驟S303:當於步驟S302中車隊管理系統110評估低電量狀態的可移動機器人依據剩餘電量可從移動路徑的終點移動至充電站時,車隊管理系統110控制可移動機器人依據導航計畫表進行移動。當步驟S303執行完後,重新執行步驟S300。Step S303: When the
步驟S304:當於步驟S302中車隊管理系統110評估低電量狀態的可移動機器人依據剩餘電量無法從移動路徑的終點移動至充電站時,車隊管理系統110控制低電量狀態的可移動機器人回到充電站充滿至第二預設電量門檻值。當步驟S304執行完後,則重新執行步驟S303。在本實施例中,第二預設電量門檻值大於第一預設電量門檻值。Step S304: When the
於一些實施例中,在物料處理方法執行物料處理程序,使得可移動機器人對物料進行處理而數位孿生模型已建立的情況下,物料處理方法可同步執行充電預測程序,但不以此為限,於其它實施例中,充電預測程序先於物料處理程序執行。In some embodiments, when the material processing method executes the material processing program so that the mobile robot processes the material and the digital twin model has been established, the material processing method can simultaneously execute the charging prediction program, but not limited thereto, In other embodiments, the charge prediction procedure is executed prior to the material handling procedure.
藉由前述物料處理方法所執行的充電預測程序,可使本案之物料處理系統100中無須在可移動機器人的當前電量等於或低於第一預設電量門檻值而處於低電量狀態時即控制可移動機器人進行充電,而是在判斷出可移動機器人無法順利完成至導航計畫表並回到充電站充電時才控制可移動機器人進行充電,故可減少可移動機器人的充電次數而提升使用效率。With the charge prediction program executed by the aforementioned material handling method, the
請參閱第5圖,並配合第1圖至第3圖,其中第5圖係顯示了第1圖所示之數位孿生建構單元所建立的數位孿生模型由複數個子模型組成時的示意圖。如第5圖所示,於一些實施例中,數位孿生建構單元111所建立的數位孿生模型400可由至少一子模型組成,而如第5圖所示,數位孿生建構單元111所建立的數位孿生模型400由複數個相互連接的子模型組成,且複數個子模型是由全球非同步局部同步(Globally Asynchronous and Formally Synchronous, GALS)方式組成及模擬。 數位孿生模型400由一個或複數個稱為時脈域(clock-domains)的頂層異步行為(又名進程)組成,例如時脈域401、時脈域407和408。在每個時脈域內,有一個或複數個同步行為(又名線程),例如在時脈域401內的同步行為402、403,406,在時脈域407內的同步行為 407a,在時脈域408內的同步行為 404、405,這些時脈域內的同步行為分別根據其對應的時脈域的邏輯刻度而以鎖定步驟的方式執行,而自主移動機器人102、103及自動導引車104及105分別對應的子模型以及移動式貨架106的內部狀態和物料處理系統100的操作皆以此類形式進行描述。另外,密切相關的行為被歸入同一時脈域,而根據全球非同步局部同步所定義的同步部分,即為在同一時脈域內的所有行為都以確定性的方式進行模擬,例如,自主移動機器人102 和生產單元 107 的子模型大多在近距離協同工作,而在這種情況下,自主移動機器人102和生產單元 107 的模擬便為同步的,因此這兩個模型之間的任何通信都決定其模擬是在本地還是分散式計算環境中進行。藉由數位孿生建構單元111所建立的數位孿生模型400由複數個相互連接的子模型組成,且複數個子模型是由全球非同步局部同步方式組成及模擬,因此本案更可達到如下述優點,即通過對單時脈域的決定性模擬改進可移動機器人依據導航規劃所能達成的截止時間和可移動機器人的電池消耗的預測的能力,此外,為在不影響決定論的情況下執行分散式模擬的能力,由於不同時脈域的異步關係,在兩個不同時脈域中模擬的模型通過先進先出序列(例如第5圖所示之序列409、410、411、412)進行通信,而這種組合通過消除時脈域之間的同步限制來實現可擴展性,故允許以全球非同步局部同步方式組合的數位孿生模型可適用於更大規模的應用於表面貼合技術的物料處理系統。Please refer to Figure 5, and cooperate with Figures 1 to 3, wherein Figure 5 shows a schematic diagram when the digital twin model established by the digital twin building unit shown in Figure 1 is composed of multiple sub-models. As shown in FIG. 5, in some embodiments, the digital
綜上所述,本案提供一種物料處理方法跟物料處理系統,物料處理方法跟物料處理系統可在可移動機器人移動跟操作而對物料進行處理的過程中,利用數位孿生模型來實時模擬可移動機器人執行導航計畫表的結果,進而隨時對可移動機器人的移動跟操作進行預測與優化,以達到提升物料處理系統整體效率與成本之功效。To sum up, this case provides a material processing method and a material processing system, which can use the digital twin model to simulate the mobile robot in real time during the process of the mobile robot moving and operating to process the material Execute the results of the navigation plan, and then predict and optimize the movement and operation of the mobile robot at any time, so as to achieve the effect of improving the overall efficiency and cost of the material handling system.
100:物料處理系統
101:緩衝區
102、103:自主移動機器人
104、105:自動導引車
106:移動式貨架
107:生產單元
108:生產線
109:集中式通信中介軟體
110:車隊管理系統
111:數位孿生建構單元
400:數位孿生模型
401、407、408:時脈域
402、403、404、405、406、407a:同步行為
409、410、411、412:序列
S200~S206:物料處理方法執行物料處理程序的步驟
S300~S304:物料處理方法執行充電預測程序的步驟
100:Material Handling System
101:
第1圖為本案較佳實施例之物料處理系統之系統架構示意圖; 第2圖為第1圖所示之物料處理系統的控制架構示意圖; 第3圖為應用於第1圖所示之物料處理系統中的物料處理方法在執行物料處理程序時的步驟流程圖; 第4圖本案之物料處理方法在執行充電預測程序時的步驟流程圖; 第5圖係顯示了第1圖所示之數位孿生建構單元所建立的數位孿生模型由複數個子模型組成時的示意圖。 Figure 1 is a schematic diagram of the system architecture of the material handling system of the preferred embodiment of this case; Figure 2 is a schematic diagram of the control structure of the material handling system shown in Figure 1; Figure 3 is a flow chart of the steps of the material handling method applied to the material handling system shown in Figure 1 when executing the material handling procedure; Figure 4 is a flow chart of the steps of the material handling method in this case when executing the charge prediction program; FIG. 5 is a schematic diagram showing a digital twin model established by the digital twin building unit shown in FIG. 1 consisting of multiple sub-models.
S200~S206:物料處理方法執行物料處理程序的步驟 S200~S206: the steps of executing the material handling procedure in the material handling method
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Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016077243A1 (en) * | 2014-11-11 | 2016-05-19 | Google Inc. | Position-controlled robotic fleet with visual handshakes |
CN111580478A (en) * | 2020-05-13 | 2020-08-25 | 中国电子科技集团公司第十四研究所 | Complex electronic equipment final assembly digital twin workshop |
-
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Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2016077243A1 (en) * | 2014-11-11 | 2016-05-19 | Google Inc. | Position-controlled robotic fleet with visual handshakes |
CN111580478A (en) * | 2020-05-13 | 2020-08-25 | 中国电子科技集团公司第十四研究所 | Complex electronic equipment final assembly digital twin workshop |
Non-Patent Citations (2)
Title |
---|
Jay Lee等人," Integration of digital twin and deep learning in cyber-physical systems: towards smart manufacturing",First published: 09 March 2020.^&rn^ (網址:https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cim.2020.0009 ) |
Mohammad Azangoo等人,"Digital Twin-Assisted Controlling of AGVs in Flexible Manufacturing Environments",Published in: 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE),Date of Conference: 20-23 June 2021^&rn^(網址:https://arxiv.org/ftp/arxiv/papers/2112/2112.01367.pdf )^&rn^;Jay Lee等人," Integration of digital twin and deep learning in cyber-physical systems: towards smart manufacturing",First published: 09 March 2020.^&rn^ (網址:https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cim.2020.0009 ) * |
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