{"id":6901,"date":"2023-03-31T10:57:37","date_gmt":"2023-03-31T02:57:37","guid":{"rendered":"https:\/\/en.siasun.com\/?p=6901"},"modified":"2026-04-07T09:45:14","modified_gmt":"2026-04-07T01:45:14","slug":"the-application-of-collaborative-robots-based-on-welding-vision-based-teachless-technology-in-container-manufacturing","status":"publish","type":"post","link":"https:\/\/en.siasun.com\/de\/the-application-of-collaborative-robots-based-on-welding-vision-based-teachless-technology-in-container-manufacturing.html","title":{"rendered":"\u00a0Containerschwei\u00dfen"},"content":{"rendered":"
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Branchen<\/h2>\n\n\n\n

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Einf\u00fchrung<\/a><\/a><\/div>
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Einf\u00fchrung<\/strong><\/h2>\n\n\n\n

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\u00a0Containerschwei\u00dfen<\/strong><\/strong><\/strong><\/strong><\/strong><\/strong><\/h2>\n<\/div>\n<\/div>\n\n\n\n
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Der Einsatz von kollaborierenden Robotern mit schwei\u00dfbildbasierter lehrfreier Technologie in der Beh\u00e4lterfertigung nutzt die leichten, flexiblen und sicheren Eigenschaften der Roboter. In Kombination mit 2D-Lasersensoren und einem 3D-Vision-System identifizieren die Roboter automatisch Schwei\u00dfn\u00e4hte f\u00fcr das automatisierte Schwei\u00dfen in der Produktionslinie.<\/p>\n\n\n\n

Das System umfasst den Roboter, den Steuerschrank, das Bildverarbeitungssystem (3D-Kamera, Industriecomputer, Bildverarbeitungssoftware), die Schwei\u00dfmaschine, den Drahtvorschub und den Schwei\u00dfbrenner, die in die SPS-Steuerung der Produktionslinie integriert sind. Der Roboter ist auf einem Sockel oder einem beweglichen St\u00e4nder montiert, was die Zusammenarbeit zwischen Mensch und Roboter ohne Schutzz\u00e4une erm\u00f6glicht und Platz spart. Mit Hilfe von 3D-Kameras oder 2D-Lasersensoren werden Punktwolken erfasst, um Positionierungsabweichungen automatisch zu korrigieren, wodurch das manuelle Teachen entf\u00e4llt und Effizienz und Genauigkeit verbessert werden.<\/p>\n\n\n\n

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\"Intelligenter<\/div>
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H\u00f6hepunkte des Projekts<\/strong><\/strong><\/h2>\n<\/div>\n<\/div>\n\n\n\n
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1. Arbeitseinsparungen und Verbesserung der Produktionseffizienz<\/strong>: Durch die Modernisierung der Montagelinie und den Einsatz von rund 60 kollaborativen Schwei\u00dfroboter-Vision-Stationen wird der Personalbedarf an Schwei\u00dfern um etwa 60 Personen reduziert. Durch die verbesserte Schwei\u00dfqualit\u00e4t werden auch die Nachschwei\u00df- und Schleifarbeiten reduziert, wodurch etwa 10 weitere Arbeitskr\u00e4fte eingespart werden.<\/p>\n\n\n\n

2. Bek\u00e4mpfung des Arbeitskr\u00e4ftemangels<\/strong>: Diese L\u00f6sung lindert den seit langem bestehenden \u201cSchwei\u00dfermangel\u201d und die Probleme mit der \u00dcberalterung der Arbeitskr\u00e4fte im Schiffbau und befreit gleichzeitig die Arbeiter an vorderster Front von der hohen Staubbelastung und der intensiven Lichtbogenstrahlung.<\/p>\n\n\n\n

3.  F\u00f6rderung der Unternehmensumwandlung und Schaffung neuer technischer Rollen<\/strong>: Das Modell der Mensch-Roboter-Kollaboration hat neue technische Funktionen wie \u201cRoboter-Wartungsingenieure\u201d hervorgebracht und den \u00dcbergang von traditionellen \u201cmanuellen\u201d Schwei\u00dfern zu \u201ctechnischen\u201d Bedienern gef\u00f6rdert.<\/p>\n\n\n\n

4. \u00dcberpr\u00fcfung der Durchf\u00fchrbarkeit eines gro\u00df angelegten kollaborativen Robotereinsatzes und der Zuverl\u00e4ssigkeit von Haushaltsger\u00e4ten<\/strong>: Der Einsatz von 60 Sichtschwei\u00dfrobotern in einem Cluster beweist die Machbarkeit von gro\u00df angelegten kollaborativen Roboteranwendungen in komplexen Szenarien. Sie zeigt auch die Zuverl\u00e4ssigkeit intelligenter Haushaltsger\u00e4te bei schweren und nicht standardisierten Aufgaben. Das Projekt amortisiert seine Investitionen und wird innerhalb eines Jahres rentabel, was ein quantifizierbares, reproduzierbares Modell f\u00fcr Kostensenkungen und Effizienzsteigerungen in Branchen wie der Containerherstellung darstellt.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Vorteile<\/strong><\/h2>\n<\/div>\n<\/div>\n\n\n\n

Dieses Projekt erm\u00f6glichte erhebliche Verbesserungen der Produktionseffizienz und der Qualit\u00e4t durch eine tiefgreifende Prozessanpassung und Systemoptimierung f\u00fcr die Beh\u00e4lterherstellung. Durch den Einsatz von 60 kollaborativen Schwei\u00dfroboter-Vision-Systemen wurden die Herausforderungen der Flexibilit\u00e4t herk\u00f6mmlicher Industrieroboter in kompakten Flie\u00dfbandanlagen erfolgreich bew\u00e4ltigt und gleichzeitig die Probleme der Konsistenz beim manuellen Schwei\u00dfen gel\u00f6st. Die kollaborativen Roboter arbeiten eng mit den Bedienern zusammen, ohne dass eine Sicherheitsumz\u00e4unung erforderlich ist, und passen sich perfekt an die r\u00e4umlichen Gegebenheiten der Produktionslinie von Ningbo CIMC an.<\/p>\n\n\n\n

Dar\u00fcber hinaus erm\u00f6glicht das Projekt eine schnelle Umstellung f\u00fcr die Mehrproduktserienfertigung mit modularen Prozesspaketen, die den Aufruf von Schwei\u00dfprogrammen mit einem Klick unterst\u00fctzen, wodurch die Umr\u00fcstzeit von mehreren Stunden auf nur wenige Minuten reduziert und eine wirklich flexible Automatisierung erreicht wird. Die technologische Innovation von SIASUN DUCO steigert nicht nur die Produktionseffizienz, sondern f\u00f6rdert auch die Umschulung der Mitarbeiter von \u201cmanuellen\u201d zu \u201ctechnischen\u201d Bedienern, um den Arbeitskr\u00e4ftemangel zu beheben und den Wert der Mitarbeiter zu steigern.<\/p>\n\n\n\n

Durch das Modell der \u201cCluster-Kollaboration\u201d und den Ansatz der \u201cMitgestaltung von Prozessen\u201d bietet dieses Projekt eine quantifizierbare, reproduzierbare L\u00f6sung zur Kostensenkung und Effizienzsteigerung, die den Kunden auf dem Weg zu einem effizienteren und intelligenteren Produktionsmodell unterst\u00fctzt.<\/p>\n\n\n\n

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It uses vision-based teachless technology to automatically identify weld seams and correct positioning deviations, eliminating manual teaching.\n\n**Project Highlights:**\n1. **Labor Savings & Efficiency:** Deployment of 60 collaborative robot welding vision stations reduced the need for welders by approximately 60 and saved an additional 10 workers in post-welding grinding.\n2. **Addressing Labor Shortages:** The solution alleviates the 'welder shortage' and aging workforce issues in shipbuilding while improving working conditions.\n3. **Role Transformation:** The human-robot collaboration creates new technical roles like 'robot maintenance engineers,' transitioning workers from manual to technical operators.\n4. **Feasibility & Reliability:** The cluster deployment of 60 robots proves the feasibility of large-scale collaborative robot use in complex scenarios and the reliability of domestic equipment. The project recoups its investment within a year.\n\n**Benefits:** The system enables rapid switching for multi-product batch production with modular process packages, reducing changeover time from hours to minutes. It enhances production efficiency, promotes employee skill transformation, and provides a quantifiable, replicable model for cost reduction and efficiency improvement."],"_geo_faqs":["[{\"question\":\"How does vision-based teachless technology work for container welding?\",\"answer\":\"The system uses 2D laser sensors or 3D cameras to capture point clouds of the workpiece. 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Scalable, cost-effective solution for flexible production."],"_geo_ai_search_text":["\u00a0container welding\nThis article details the application of collaborative robots with vision-based teachless technology in container welding, highlighting labor savings, efficiency improvements, and a successful large-scale deployment at CIMC.\n**Industry & Application:** The article focuses on container manufacturing, where collaborative robots equipped with 2D laser sensors and 3D vision systems are used for automated welding.\n\n**Technology & System:** The system integrates a robot, control cabinet, vision system (3D camera, industrial computer, vision software), welding machine, wire feeder, and welding torch. It uses vision-based teachless technology to automatically identify weld seams and correct positioning deviations, eliminating manual teaching.\n\n**Project Highlights:**\n1. **Labor Savings & Efficiency:** Deployment of 60 collaborative robot welding vision stations reduced the need for welders by approximately 60 and saved an additional 10 workers in post-welding grinding.\n2. **Addressing Labor Shortages:** The solution alleviates the 'welder shortage' and aging workforce issues in shipbuilding while improving working conditions.\n3. **Role Transformation:** The human-robot collaboration creates new technical roles like 'robot maintenance engineers,' transitioning workers from manual to technical operators.\n4. **Feasibility & Reliability:** The cluster deployment of 60 robots proves the feasibility of large-scale collaborative robot use in complex scenarios and the reliability of domestic equipment. The project recoups its investment within a year.\n\n**Benefits:** The system enables rapid switching for multi-product batch production with modular process packages, reducing changeover time from hours to minutes. It enhances production efficiency, promotes employee skill transformation, and provides a quantifiable, replicable model for cost reduction and efficiency improvement.\nCollaborative robots with vision-based teachless technology automate container welding by automatically identifying weld seams. A deployment of 60 collaborative robot welding stations reduced the workforce by 60 welders and 10 grinding workers. The system alleviates the 'welder shortage' and transforms workers from manual welders to technical operators. The project proves the feasibility and reliability of large-scale collaborative robot deployment in complex industrial scenarios. Modular process packages enable rapid product changeovers, reducing setup time from hours to minutes. The investment in the project is recovered within one year, providing a replicable model for cost reduction.\nHow does vision-based teachless technology work for container welding?\nThe system uses 2D laser sensors or 3D cameras to capture point clouds of the workpiece. This vision system automatically identifies weld seams and corrects any positioning deviations, eliminating the need for manual teaching or programming of the robot path.\nWhat are the main benefits of using collaborative robots for container welding?\nKey benefits include significant labor savings (reducing the need for 60 welders and 10 grinding workers), improved welding quality, alleviation of the skilled welder shortage, and the creation of new technical roles. The system also enables rapid product changeovers, reducing downtime from hours to minutes.\nCan collaborative robots be deployed on a large scale in container manufacturing?\nYes, the article highlights a successful case where 60 collaborative robot welding stations were deployed in a cluster. This proves the feasibility of large-scale deployment in complex, heavy-duty environments and demonstrates the reliability of domestic intelligent equipment.\nHow does this solution address the labor shortage in welding?\nBy automating the welding process, the solution reduces the reliance on human welders, directly addressing the chronic 'welder shortage' and the aging workforce. It also improves working conditions by removing workers from high dust and intense arc radiation environments.\nWhat is the return on investment for implementing collaborative robot welding in a container factory?\nThe article states that the project recovers its investment and becomes profitable within one year, providing a quantifiable and replicable model for cost reduction and efficiency improvement in the container manufacturing industry.\nManufacturing engineers, factory managers, and decision-makers in the container manufacturing and shipbuilding industries who are seeking automation solutions to address labor shortages, improve welding quality, and increase production efficiency."]},"medium_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/03\/\u9996\u56fe-300x180.jpg","thumbnail_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/03\/\u9996\u56fe-150x150.jpg","full_url":"https:\/\/en.siasun.com\/wp-content\/uploads\/2026\/03\/\u9996\u56fe.jpg","_links":{"self":[{"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/posts\/6901","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/comments?post=6901"}],"version-history":[{"count":3,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/posts\/6901\/revisions"}],"predecessor-version":[{"id":6959,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/posts\/6901\/revisions\/6959"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/media\/6904"}],"wp:attachment":[{"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/media?parent=6901"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/categories?post=6901"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/en.siasun.com\/de\/wp-json\/wp\/v2\/tags?post=6901"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}