研究背景:近年來,全球製造業面臨COVID-19疫情、勞動力短缺和碳排放等挑戰,需要透過數位轉型和科技應用來提升韌性。並且氣候變化已成為全球議題,全球多國提出「2050淨零排放」,台灣也納入政策目標之一,超過規定碳排放量的製造業及電力業,將於2025開始課徵碳費,因此必須做出應對措施,並積極因應氣候變遷帶來的衝擊。研究目的:本研究的主要目的是探索如何利用AR/VR(Augmented Reality /Virtual Reality)技術來監控小五軸機台生產過程中的機台資訊和碳足跡,以協助製造業實現更高的環保和可持續生產目標。具體研究目的包括:1.本研究探討應用AR/VR給予製造業新型的人機互動介面使用體驗2.即時顯示機台的生產過程數據,從而實現遠端監控機台的目標3.更好的理解和管理機台其碳排放,使企業更能靈活應對碳減排目標。研究方法:本研究將以小五軸加工機為例,探討透過AR/VR技術監測生產過程中的機台資訊、碳足跡、歷史數據,深入瞭解相關文獻進行研究。將系統透過MQTT協定(Message Queuing Telemetry Transport)和Visual studio開發人員工具串聯小五軸機台和AR/VR,並運用Photoshop繪製AR/VR數據介面,Solidwork製作小五軸模型,最後透過Unity設計人機介面,實例運用Hololens2來呈現機台個性生產過程中數值,達到遠端監控機台之成效,證明本研究之可行性。研究發現:本研究運用AR/VR技術實現即時化之資訊呈現,透過自動化數據串接,我們將機台在生產過程中產生的電力透過感測器感測並透過公式轉換為碳足跡數值,即時能於Hololens2上展示五軸生產狀態和機台碳排放量,達到遠端監控之成效。研究結論:我們的研究旨在改善原始人機介面的種種限制,包括設計不良、系統擴充性差以及難以對接等問題。利用AR/VR技術,我們成功實現了能夠同時監控遠端的小五軸機台的系統。機台數據即時傳輸至伺服器資料庫,透過HoloLens 2介面呈現並導入了碳足跡盤查指標,使操作員能夠遠端觀測小五軸機台的即時數據,大幅提升機台生產流程的管理效率。這項技術讓操作員能夠同時監控不同地點的機台,提供即時、直觀的資訊,達到更全面、更有效率的監控目標。
In the quest for net-zero carbon emissions globally, this research leverages AR/VR (Augmented Reality/Virtual Reality) technologies to enhance the visualization of carbon footprints. These technologies allow real-world scenes to be seamlessly integrated with machine production data and carbon monitoring information, achieving a truly immersive virtual-reality experience. This study connects small, five-axis machines to automated data streams and utilizes sensor technology to instantaneously collect operational information from all equipment involved in the manufacturing process. This data is subsequently used for the compilation, calculation, and management of carbon footprints. This enables operators to better understand the origins and distribution of carbon emissions, thereby facilitating the implementation of carbon-reduction measures. The application of AR/VR technology serves to mitigate issues arising from inconsistent interface models and outdated information. It helps overcome limitations and design flaws in the original human-machine interfaces, offering operators real-time insight into machine operation. This innovation allows for the remote monitoring and control of various intelligent production information across multiple machines, while also providing a basis for tracking carbon emissions.