市場調查報告書
商品編碼
1466476
數位雙胞胎市場:按類型、部署模式、公司規模、應用、產業分類 - 2024-2030 年全球預測Digital Twin Market by Type (Process Digital Twin, Product Digital Twin, System Digital Twin), Deployment Mode (On Premices, On-Cloud), Enterprise Size, Application, Industry - Global Forecast 2024-2030 |
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預計2023年數位雙胞胎市場規模為141.6億美元,2024年將達168.2億美元,預計2030年將達535.1億美元,複合年成長率為20.90%。
數位雙胞胎是一種創新技術,可創建實體物件、設備、流程、環境等的虛擬模型或數位表示,其行為、類比和外觀與現實世界中的對應對象相似。數位雙胞胎在許多領域都有應用,包括製造、汽車、醫療保健、能源和基礎設施。這些產業促進產品設計、流程最佳化、預測性維護和決策。物聯網、機器學習和巨量資料分析的持續改進對於數位雙胞胎的發展至關重要,從而實現更複雜、更準確的模型。此外,由工業 4.0舉措推動的產業數位轉型將顯著加速數位雙胞胎的採用。然而,數位雙胞胎技術的複雜性需要熟練的勞動力,而當前的技能差距對快速採用構成了挑戰。此外,確保與數位雙胞胎相關的資料的隱私和安全的需求也可能阻礙市場成長。然而,主要企業不斷尋求資料加密和身分驗證技術的進步,以防止資料外洩和資料隱私的喪失。將數位雙胞胎與擴增實境、虛擬實境和區塊鏈相結合,為該行業開闢了新的成長途徑。此外,數位雙胞胎在城市規劃和智慧基礎設施開發的應用具有巨大的市場拓展潛力。
主要市場統計 | |
---|---|
基準年[2023] | 141.6億美元 |
預測年份 [2024] | 168.2億美元 |
預測年份 [2030] | 535.1億美元 |
複合年成長率(%) | 20.90% |
汽車產業的全球擴張需要引入類型產品數位雙胞胎
流程數位雙胞胎是一種先進的數位表示形式,可模擬複雜的生產流程,使製造商和公司能夠理解、分析和最佳化流程操作。此數位雙胞胎主要用於流程監控和故障排除、流程設計和營運改進以及預測性維護。產品數位雙胞胎可實現設計最佳化、效能追蹤、生命週期管理,並專注於單一產品的細節。汽車、航太和電子等產品複雜的產業通常會利用產品數位雙胞胎。系統數位雙胞胎是一種複合數位組件,它集中了各種產品和流程的孿生來代表整個系統或設施。這種配置對於多個流程和產品相互作用的複雜系統特別有用,例如智慧城市、綜合能源系統和大型製造工廠。
部署方式:新興企業首選的雲端部署方式
本地部署是指使用私有伺服器在組織的實體設施中實施數位雙胞胎技術。此方法可讓您完全控制基礎設施和資料,確保高水準的安全性並符合特定產業法規。具有嚴格資料安全要求的組織可能更喜歡本地部署,以確保資料永遠不會離開受控環境。在雲端配置模型中,數位雙胞胎託管在第三方雲端服務供應商的基礎架構上。此選項通常提供擴充性、彈性、較低的初始成本以及對先進技術的存取。尋求擴展的新興企業和其他企業可以從雲端基礎的解決方案提供的彈性可擴展性中受益。
企業規模:大型企業對綜合數位雙胞胎技術的需求不斷增加
大公司通常有資金投資全面的數位雙胞胎技術,並希望將其整合到各個部門和地點。這些公司通常在全球範圍內營運,擁有複雜的供應鏈和廣泛的資產組合。這種複雜性需要具有高粒度和擴充性的強大數位雙胞胎解決方案。大型企業的需求包括先進的分析能力、廣泛的整合能力和高擴充性。對於中小型企業來說,由於資源和預算有限,數位雙胞胎的方法更加保守。這些公司正在尋找易於實施並能立即實現業務改進的經濟高效的解決方案。中小型企業通常尋求靈活的模組化解決方案來滿足其特定需求,而不是廣泛的企業範圍部署。
應用不同產業對預測性維護的需求推動了機器和設備的健康監測
機械設備健康監測著重於使用數位雙胞胎來監測機械設備的健康狀況和性能。這些虛擬表示可實現預測性維護、故障偵測和效能最佳化。使用重型機械的行業受益於這項技術,因為它可以最大限度地減少停機時間並降低維修和維護成本。流程支援和服務中的數位雙胞胎可以改進各種系統的規劃、培訓和操作。這些技術通常用於工業流程中,以模擬不同的場景並最佳化流程。雖然健康監測產業嚴重依賴即時資料和預測分析,但流程支援解決方案受益於情境建模和服務改進。產品設計和開發允許在實際建造之前虛擬創建和迭代複雜的產品。這使得潛在的障礙能夠在設計階段的早期解決,從而節省大量的時間、成本和資源。
全球對製造工廠的投資激增,創造了對工業數位雙胞胎技術的需求
航太和國防工業使用數位雙胞胎技術來模擬和分析飛機和國防系統。在農業領域,數位雙胞胎用於精密農業、牲畜監測和資源管理。支援基於即時資料的決策、促進永續實踐、改進產量預測等等。汽車領域的數位雙胞胎支援車輛開發、交通管理和基礎設施建模。能源和公共事業公司使用數位雙胞胎對能源系統、電網和工廠進行建模,以提高效率和可靠性。關鍵領域包括再生能源來源的整合、電網彈性和預測性基礎設施維護。在醫療保健和生命科學產業,數位雙胞胎正在幫助病患監測、手術規劃和個人化醫療的發展。製造業中的數位雙胞胎技術對於產品設計、生產計畫和控制以及供應鏈最佳化至關重要。在石油和天然氣領域,數位雙胞胎被用於探勘、鑽機的預測性維護以及管道和精製的監控。在住宅和商業應用中,數位雙胞胎正在為智慧建築設計、能源管理和基礎設施維護做出貢獻。在零售和消費品行業,數位雙胞胎用於供應鏈可視性、虛擬庫存管理和改善客戶體驗。
區域洞察
在美洲,美國和加拿大是數位雙胞胎產業的關鍵國家,擁有堅實的技術基礎設施、主要參與者以及不斷的創新和產品發布。此外,政府透過採用數位雙胞胎等先進技術推動製造業、醫療保健、航太和汽車等行業發展的舉措正在推動採用。歐盟對數位雙胞胎的關注旨在實現成員國之間的標準化和互通性,增加對智慧製造和工業 4.0 計劃的投資。此外,歐盟為實現製造業永續性製定的多項法規、標準和舉措導致了對數位雙胞胎技術的大量投資。印度是快速發展的製造業和 IT 中心,在「數位印度」等政府舉措的推動下,正在迅速採用數位雙胞胎技術,特別是在智慧城市和基礎設施開發領域。在日本,我們專注於使用數位雙胞胎來提高汽車和電子行業的效率和品質。該地區科技新興企業的崛起為數位雙胞胎擴張帶來了新的機會。
FPNV定位矩陣
FPNV定位矩陣對於評估數位雙胞胎市場至關重要。我們檢視與業務策略和產品滿意度相關的關鍵指標,以對供應商進行全面評估。這種深入的分析使用戶能夠根據自己的要求做出明智的決策。根據評估,供應商被分為四個成功程度不同的像限:前沿(F)、探路者(P)、利基(N)和重要(V)。
市場佔有率分析
市場佔有率分析是一種綜合工具,可以對數位雙胞胎市場中供應商的現狀進行深入而深入的研究。全面比較和分析供應商在整體收益、基本客群和其他關鍵指標方面的貢獻,以便更好地了解公司的績效及其在爭奪市場佔有率時面臨的挑戰。此外,該分析還提供了對該行業競爭特徵的寶貴見解,包括在研究基準年觀察到的累積、分散主導地位和合併特徵等因素。詳細程度的提高使供應商能夠做出更明智的決策並制定有效的策略,從而在市場上獲得競爭優勢。
1. 市場滲透率:提供有關主要企業所服務的市場的全面資訊。
2. 市場開拓:我們深入研究利潤豐厚的新興市場,並分析其在成熟細分市場的滲透率。
3. 市場多元化:提供有關新產品發布、開拓地區、最新發展和投資的詳細資訊。
4. 競爭評估和情報:對主要企業的市場佔有率、策略、產品、認證、監管狀況、專利狀況和製造能力進行全面評估。
5. 產品開發與創新:提供對未來技術、研發活動和突破性產品開發的見解。
1.數位雙胞胎市場的市場規模和預測是多少?
2. 在數位雙胞胎市場預測期內,有哪些產品、細分市場、應用程式和領域需要考慮投資?
3.數位雙胞胎市場的技術趨勢和法規結構是什麼?
4.數位雙胞胎市場主要廠商的市場佔有率是多少?
5.進入數位雙胞胎市場的合適型態和策略手段是什麼?
[193 Pages Report] The Digital Twin Market size was estimated at USD 14.16 billion in 2023 and expected to reach USD 16.82 billion in 2024, at a CAGR 20.90% to reach USD 53.51 billion by 2030.
A digital twin is an innovative technology that creates a virtual or digital model or representation of a physical object, equipment, process, or environment that acts, simulates, and looks similar to its counterpart in the real world. Digital twin find applications in numerous sectors, including manufacturing, automotive, healthcare, energy, and infrastructure. In these industries, they facilitate product design, process optimization, predictive maintenance, and decision-making. Continuous improvements in IoT, machine learning, and big data analytics are pivotal to the growth of digital twin, allowing for more sophisticated and accurate models. Furthermore, the digital transformation of industries, driven by the Industry 4.0 initiatives, significantly promotes the adoption of digital twin. However, the complexity of digital twin technology requires a skilled workforce, with the current skill gap presenting a challenge to rapid adoption. Additionally, the need to ensure the privacy and security of data associated with digital twin can hinder market growth. However, major players are constantly exploring advancements in data encryption and authentication technologies to prevent data breaches and loss of data privacy. Combining digital twin with augmented reality, virtual reality, and blockchain creates new avenues of growth for the industry. Additionally, the utilization of digital twin in urban planning and smart infrastructure development offers vast potential for market expansion.
KEY MARKET STATISTICS | |
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Base Year [2023] | USD 14.16 billion |
Estimated Year [2024] | USD 16.82 billion |
Forecast Year [2030] | USD 53.51 billion |
CAGR (%) | 20.90% |
Type: Expansion of the automotive sector across the world necessitating adoption of product digital twin
The process digital twin is an advanced digital representation that simulates complex production processes, allowing manufacturers and business enterprises to understand, analyze, and optimize the operations of their processes. This digital twin variant is primarily used to monitor and troubleshoot process flows, improve process design and operations, and conduct predictive maintenance. Product digital twin focus on the granular details of a single product, allowing for design optimization, performance tracking, and lifecycle management. Industries that involve complex products, such as automotive, aerospace, and electronics, often leverage product digital twin. The system digital twin is a composite digital construct that aggregates various product and process twin to represent an entire system or facility. This configuration is especially beneficial for complex systems where multiple processes and products interact, such as smart cities, integrated energy systems, and large manufacturing plants.
Deployment Mode: Preference of startups for on-cloud deployment mode
On-premises deployment refers to the implementation of digital twin technology on the organization's physical facilities using its private servers. This method provides complete control over the infrastructure and data, ensuring high levels of security and compliance with industry-specific regulations. Organizations with stringent data security requirements may prefer on-premises deployment to ensure their data doesn't leave their controlled environment. With the on-cloud deployment model, the digital twin is hosted on the infrastructure of third-party cloud service providers. This option typically delivers scalability, flexibility, lower upfront costs, and access to advanced technologies. Businesses expecting to scale their operations, such as startups, can benefit from the elastic scalability offered by cloud-based solutions.
Enterprise Size: Growing demand for comprehensive digital twin technologies from large enterprises
Large enterprises often have the capital to invest in comprehensive digital twin technologies, seeking to integrate them across various departments and locations. These companies typically operate on a global scale, with complex supply chains and extensive asset portfolios. This complexity demands a robust digital twin solution that can offer a high level of granularity and the ability to scale. The need-based preferences for large enterprises include advanced analytics, extensive integration capabilities, and high scalability. For small and medium enterprises (SMEs), the approach to digital twin is more conservative due to limited resources and budget constraints. These companies require cost-effective solutions that can provide immediate operational improvements and are easy to implement. SMEs are often looking for flexible, modular solutions that cater to specific needs rather than an extensive enterprise-wide deployment.
Application: Need for predictive maintenance in diverse industries driving machine & equipment health monitoring
Machine & equipment health monitoring focuses on monitoring the health and performance of machines and equipment through the use of digital twin. These virtual representations enable predictive maintenance, fault detection, and performance optimization. Industries with heavy machinery benefit from this technology as it minimizes downtime and reduces costs associated with repairs and maintenance. Digital twin in process support and service enable improved planning, training, and operation of various systems. They are often used in the context of industrial processes to simulate different scenarios and optimize process flows. While the health monitoring segment relies largely on real-time data and predictive analytics, process support solutions benefit from scenario modeling and service improvements. In product design and development, digital twin assist in creating and iterating complex products virtually before they are built physically. This saves significant amounts of time, money, and resources as potential hurdles can be resolved early in the design phase.
Industry: Burgeoning investments in manufacturing plants across the world creating demand for digital twin technologies
The aerospace and defense industry leverages digital twin technology largely for the simulation and analysis of aircraft and defense systems. In agriculture, digital twins are utilized for precision farming, livestock monitoring, and resource management. They offer decision support based on real-time data, facilitate sustainable practices, and improve yield predictions. Digital twin in the automotive sector supports the development of vehicles, traffic management, and infrastructure modeling. Energy and utility companies use digital twins to model energy systems, grids, and plants for improved efficiency and reliability. Key preferences include the integration of renewable energy sources, grid resilience, and predictive maintenance of infrastructure. In the healthcare and life sciences industry, digital twins aid in patient monitoring, surgical planning, and the development of personalized medicine. Digital twin technology in manufacturing is pivotal for product design, production planning and management, and supply chain optimization. The oil and gas sector employs digital twins for exploration, predictive maintenance of rigs, and monitoring of pipelines and refineries. For residential and commercial applications, digital twins contribute to smart building design, energy management, and infrastructure maintenance. Retail and consumer goods industries utilize digital twins for supply chain visibility, virtual inventory management, and customer experience enhancement.
Regional Insights
In the Americas region, the U.S. and Canada represent crucial nations for the digital twin industry due to the presence of a robust technology infrastructure, key players, and constant technological innovations and product launches. Additionally, government initiatives to advance sectors such as manufacturing, healthcare, aerospace, and automotive through the adoption of advanced technologies such as digital twin has boosted adoption. The EU's focus on digital twin is largely geared toward achieving standards and interoperability across member states, with increased investments in smart manufacturing and Industry 4.0 initiatives. Additionally, several EU regulations, standards, and initiatives to achieve sustainability in the manufacturing sector have led to significant investments in digital twin technologies. As a burgeoning economy with an expanding manufacturing and IT hub, India is rapidly adopting digital twin technologies, particularly in areas of smart cities and infrastructure development, backed by government initiatives such as Digital India. Japan focuses on leveraging digital twin for its established automotive and electronics industries, aiming to enhance efficiency and product quality. The emergence of technology startups in the region creates new opportunities for the expansion of digital twin.
FPNV Positioning Matrix
The FPNV Positioning Matrix is pivotal in evaluating the Digital Twin Market. It offers a comprehensive assessment of vendors, examining key metrics related to Business Strategy and Product Satisfaction. This in-depth analysis empowers users to make well-informed decisions aligned with their requirements. Based on the evaluation, the vendors are then categorized into four distinct quadrants representing varying levels of success: Forefront (F), Pathfinder (P), Niche (N), or Vital (V).
Market Share Analysis
The Market Share Analysis is a comprehensive tool that provides an insightful and in-depth examination of the current state of vendors in the Digital Twin Market. By meticulously comparing and analyzing vendor contributions in terms of overall revenue, customer base, and other key metrics, we can offer companies a greater understanding of their performance and the challenges they face when competing for market share. Additionally, this analysis provides valuable insights into the competitive nature of the sector, including factors such as accumulation, fragmentation dominance, and amalgamation traits observed over the base year period studied. With this expanded level of detail, vendors can make more informed decisions and devise effective strategies to gain a competitive edge in the market.
Key Company Profiles
The report delves into recent significant developments in the Digital Twin Market, highlighting leading vendors and their innovative profiles. These include ABB Ltd., Altair Engineering Inc., Amazon Web Services, Inc., Ansys, Inc., Bentley Systems, Incorporated, Cisco Systems, Inc., Dassault Systemes SE, dSPACE GmbH, Emerson Electric Co., General Electric Company, Google LLC by Alphabet Inc., Hewlett Packard Enterprise Development LP, Honeywell International Inc., Huawei Technologies Co., Ltd., Intel Corporation, International Business Machines Corporation, Lenovo Group Limited, Matterport, Inc., Microsoft Corporation, NTT DATA Corporation, NVIDIA Corporation, Oracle Corporation, PTC Inc., QiO Technologies, Robert Bosch GmbH, Salesforce, Inc., SAP SE, Schneider Electric SE, Siemens AG, and Wipro Limited.
Market Segmentation & Coverage
1. Market Penetration: It presents comprehensive information on the market provided by key players.
2. Market Development: It delves deep into lucrative emerging markets and analyzes the penetration across mature market segments.
3. Market Diversification: It provides detailed information on new product launches, untapped geographic regions, recent developments, and investments.
4. Competitive Assessment & Intelligence: It conducts an exhaustive assessment of market shares, strategies, products, certifications, regulatory approvals, patent landscape, and manufacturing capabilities of the leading players.
5. Product Development & Innovation: It offers intelligent insights on future technologies, R&D activities, and breakthrough product developments.
1. What is the market size and forecast of the Digital Twin Market?
2. Which products, segments, applications, and areas should one consider investing in over the forecast period in the Digital Twin Market?
3. What are the technology trends and regulatory frameworks in the Digital Twin Market?
4. What is the market share of the leading vendors in the Digital Twin Market?
5. Which modes and strategic moves are suitable for entering the Digital Twin Market?
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