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市場調查報告書
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1818007

2032 年製造業邊緣運算與雲端運算市場預測：按部署模式、組織規模、技術、應用程式、最終用戶和地區進行的全球分析

Edge & Cloud Computing in Manufacturing Market Forecasts to 2032 - Global Analysis By Deployment Model (Edge Computing, Cloud Computing and Hybrid Architecture), Organization Size, Technology, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球製造業邊緣和雲端運算市場預計在 2025 年達到 496 億美元，到 2032 年將達到 2,235.8 億美元，預測期內的複合年成長率為 24.0%。

在製造業，邊緣運算和雲端運算正透過改善數據管理和營運效率來推動數位轉型。邊緣運算在靠近生產設備的地方處理訊息，確保關鍵操作的快速響應和最小延遲。相較之下，雲端處理提供海量儲存、集中式分析和人工智慧應用，可增強設備和供應鏈的可視性。這些功能結合，創建了混合模式。這種協同作用不僅可以減少停機時間，還能使製造商能夠更快地回應市場需求。採用邊緣雲端解決方案使產業能夠獲得擴充性、彈性和創新能力，從而增強其在智慧製造領域的競爭優勢。

根據 IJFMR 發表的同行評審研究，邊緣運算將製造環境中的資料處理延遲從 150-200 毫秒縮短至僅 15 毫秒，從而實現即時品管和預測性維護。

預測性維護的需求不斷增加

預測性維護已成為製造業邊緣運算和雲端運算的關鍵驅動力。傳統的糾正性維護和定期維護通常會導致高昂的成本和停機時間。邊緣運算在設備附近處理數據，實現即時異常檢測，而雲端平台則分析大型資料集以建立預測模型並預測故障。這兩個系統可以防止意外故障，延長機器壽命並降低維護成本。這提高了資產可靠性，增強了工人安全性，並確保了不間斷的生產流程。透過最大限度地降低風險並最佳化效能，由邊緣運算和雲端整合支援的預測性維護對於追求更高效率的現代工廠至關重要。

實施成本高

在製造業中採用邊緣運算和雲端運算的最大挑戰之一是高昂的實施成本。安裝邊緣硬體、感測器、連網型設備以及整合雲端服務需要大量的資本投入。對於中小型製造商而言，這筆成本通常高得令人望而卻步，限制了大型企業的採用。此外，員工培訓、系統升級、資料保護措施和長期維護成本也帶來了財務壓力。不確定的投資報酬率使企業對接受如此重大的轉型持謹慎態度。因此，高昂的前期成本和相關費用持續限制著邊緣雲端解決方案在整個製造業的擴展。

預測分析和人工智慧的興起

預測分析和人工智慧在製造業的應用，為邊緣運算和雲端運算解決方案帶來了巨大的機會。邊緣系統處理靠近機器的即時數據並快速檢測異常，而雲端基礎的人工智慧平台則分析模式並提供準確的預測。這種方法增強了預測性維護，提高了產品質量，並簡化了供應鏈績效。製造商受益於停機時間的減少、機器壽命的延長和整體效率的提升。此外，人工智慧和邊緣雲端網路的結合，使得自適應生產系統能夠對不斷變化的條件做出即時回應。隨著工廠越來越依賴智慧自動化，人工智慧、預測分析和邊緣雲端運算的融合預計將顯著擴展市場。

技術純熟勞工短缺

製造業採用邊緣運算和雲端運算面臨的一大威脅是熟練人才的短缺。實施和維護這些技術需要資料分析、網路安全、物聯網設備和雲端整合方面的高階知識。然而，製造商往往難以找到具備這些專業知識的專業人員。缺乏熟練的員工，系統就無法充分最佳化，容易出現故障和安全問題。這種人才缺口加劇了對成本高昂的外部供應商的依賴，而中小企業可能無法負擔這些供應商的費用。人才短缺阻礙了智慧製造舉措的擴展，阻礙了邊緣雲端技術的廣泛應用，並減緩了其全球市場的發展。

COVID-19的影響：

新冠疫情對製造業的邊緣運算和雲端運算市場產生了重大影響，重塑了全球的營運重點。工廠關閉、勞動力短缺和供應鏈中斷導致企業對數位化解決方案的依賴增加。邊緣運算已成為即時機器監控和流程自動化的關鍵，尤其是在人力有限的情況下；而雲端平台則透過遠端協作、集中分析和虛擬營運管理，確保了業務永續營運連續性。這些技術使製造商能夠在限制條件下維持生產，並快速回應不斷變化的需求。即使在後疫情時代，對彈性、靈活性和智慧製造的重視依然持續，這進一步強化了邊緣運算和雲端技術的融合，使其成為工業現代化的關鍵驅動力。

雲端運算領域預計將成為預測期內最大的領域

雲端運算領域預計將在預測期內佔據最大的市場佔有率，因為它為製造商提供了可擴展的資源、強大的資料管理和強大的分析工具。利用雲端平台，企業可以集中生產數據，提高供應鏈視覺性，並促進地理位置分散的工廠之間的協作。透過有效率地大規模處理訊息，雲端系統支援預測性維護、數位雙胞胎和人工智慧自動化。它們最大限度地減少了對昂貴基礎設施的依賴，從而實現了靈活性並節省了成本。憑藉與物聯網生態系統的無縫整合以及對智慧製造計劃的有力支持，雲端運算已成為推動全球產業數位轉型的關鍵領域。

預計人工智慧和機器學習領域在預測期內將以最高的複合年成長率成長。

預計人工智慧和機器學習領域將在預測期內呈現最高成長率。這些技術透過實現預測分析、智慧自動化和動態流程調整來增強製造業。在邊緣，人工智慧透過即時分析即時機器數據來加速決策，而雲端系統則應用機器學習模型來識別模式並預測結果。這種組合提高了生產效率，最大限度地減少了錯誤，並確保了主動維護。其適應性使工廠能夠持續最佳化營運、降低成本並提高產品品質。隨著全球智慧製造的加速發展，人工智慧和機器學習正成為該市場的關鍵成長引擎。

比最大的地區

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其早期的技術採用、大量的投資以及強大的工業基礎。美國在智慧製造、物聯網整合和數位轉型計劃方面的大量投資脫穎而出。汽車、航太和電子等行業正在利用邊緣和雲端解決方案來提高營運效率、實現預測性維護和即時分析。大型科技公司的存在和良好的法規環境進一步鞏固了該地區的領導地位。雖然北美目前處於領先地位，但預計未來幾年亞太地區將實現最高的成長率。

複合年成長率最高的地區：

預計亞太地區在預測期內的複合年成長率最高。這一成長得益於快速的工業發展、工業 4.0 標準的採用以及 5G 網路的建立。中國、日本和韓國等國家一直是將物聯網 (IoT) 設備、人工智慧 (AI) 和即時數據處理融入其製造業的先驅。該地區的數位轉型努力，加上政府的優惠政策和對技術基礎設施的大量投資，正在創建一個支援邊緣運算和雲端運算技術在製造業中擴展的生態系統。

免費客製化服務：

此報告的訂閱者可以使用以下免費自訂選項之一：

  • 公司簡介
    • 對最多三家其他市場公司進行全面分析
    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球製造業邊緣和雲端運算市場（按部署模式）

  • 邊緣運算
  • 雲端運算
  • 混合架構

6. 全球製造業邊緣和雲端運算市場（按組織規模）

  • 主要企業
  • 小型企業

7. 全球製造業邊緣與雲端運算市場（按技術）

  • 物聯網感測器和設備
  • 人工智慧和機器學習
  • 5G連接
  • 數位雙胞胎平台
  • 網路安全解決方案

8. 全球製造業邊緣與雲端運算市場（按應用）

  • 預測性維護
  • 生產最佳化
  • 庫存和物流管理
  • 能源效率監測
  • 品質檢驗與保證

9. 全球製造業邊緣和雲端運算市場（按最終用戶）

  • 車
  • 電子和半導體
  • 製藥
  • 飲食
  • 重型機械和工業設備

第 10 章：按地區分類的全球製造業邊緣與雲端運算市場

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第11章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第 12 章：公司概況

  • Cisco
  • Dell Technologies
  • Microsoft
  • Amazon Web Services（AWS）
  • Google Cloud Platform
  • IBM
  • Hewlett Packard Enterprise（HPE）
  • Intel
  • Oracle
  • Plex Systems, Inc.
  • Salesforce
  • VMware
  • Alibaba Cloud
  • Tencent Cloud
  • PTC Inc.
Product Code: SMRC30970

According to Stratistics MRC, the Global Edge & Cloud Computing in Manufacturing Market is accounted for $49.60 billion in 2025 and is expected to reach $223.58 billion by 2032 growing at a CAGR of 24.0% during the forecast period. In manufacturing, edge and cloud computing are driving digital transformation by improving data management and operational efficiency. Edge computing processes information near production equipment, ensuring rapid responses and minimal latency for critical operations. In contrast, cloud computing offers expansive storage, centralized analytics, and AI applications that enhance visibility across facilities and supply chains. Together, they create a hybrid model that supports predictive maintenance, automated quality checks, and optimized workflows. This synergy not only reduces downtime but also enables manufacturers to adapt quickly to market demands. By adopting edge-cloud solutions, industries gain scalability, resilience, and innovation, solidifying competitiveness in the smart manufacturing landscape.

According to a peer-reviewed study published in IJFMR, edge computing has reduced data processing latency in manufacturing environments from 150-200 milliseconds to just 15 milliseconds, enabling real-time quality control and predictive maintenance.

Market Dynamics:

Driver:

Rising demand for predictive maintenance

Predictive maintenance has emerged as a key growth driver for edge and cloud computing in manufacturing. Traditional reactive or scheduled maintenance often leads to high costs and downtime. Edge computing enables real-time anomaly detection by processing data near the equipment, while cloud platforms analyze large datasets to build predictive models and forecast failures. This dual system helps prevent unexpected breakdowns, extend machine life, and cut maintenance expenses. It ensures higher asset reliability, enhanced worker safety, and uninterrupted production flow. By minimizing risks and optimizing performance, predictive maintenance supported by edge-cloud integration is becoming indispensable for modern factories seeking efficiency gains.

Restraint:

High implementation costs

One of the biggest challenges to edge and cloud computing adoption in manufacturing is the significant cost of implementation. Setting up edge hardware, sensors, and connected devices, along with integrating cloud services, demands heavy capital spending. For small and mid-sized manufacturers, this expense often becomes prohibitive, restricting adoption to larger players. Further financial pressure arises from staff training, system upgrades, data protection measures, and long-term maintenance expenses. The uncertainty surrounding ROI makes companies cautious about embracing such large-scale transformation. As a result, high upfront costs and associated expenditures continue to limit the expansion of edge-cloud solutions across the manufacturing sector.

Opportunity:

Expansion of predictive analytics & AI

Predictive analytics and AI adoption in manufacturing are unlocking major opportunities for edge and cloud computing solutions. Edge systems process live data close to machinery, quickly detecting irregularities, while cloud-based AI platforms analyze patterns to deliver accurate forecasts. This approach enhances predictive maintenance, improves product quality, and streamlines supply chain performance. Manufacturers benefit from reduced downtime, extended machine life, and higher overall efficiency. Moreover, combining AI with edge-cloud networks allows adaptive production systems that respond instantly to changing conditions. As factories increasingly rely on intelligent automation, the convergence of AI, predictive analytics, and edge-cloud computing is set to fuel significant market expansion.

Threat:

Shortage of skilled workforce

A critical threat to the adoption of edge and cloud computing in manufacturing is the lack of skilled talent. Deploying and sustaining these technologies requires advanced knowledge of data analytics, cyber security, IoT devices, and cloud integration. Yet, manufacturers often face difficulties in finding professionals with such expertise. Without skilled staff, systems may not be fully optimized, leaving them prone to failures or security issues. This gap increases reliance on costly external vendors, which smaller firms may not afford. The workforce shortage creates barriers to scaling smart manufacturing initiatives, hindering the widespread use of edge-cloud technologies and slowing market development worldwide.

Covid-19 Impact:

The outbreak of COVID-19 significantly influenced the Edge and Cloud Computing in Manufacturing Market, reshaping operational priorities worldwide. Factory closures, workforce shortages, and supply chain disruptions increased reliance on digital solutions. Edge computing became vital for real-time machine monitoring and process automation with limited staff presence, while cloud platforms ensured business continuity through remote collaboration, centralized analytics, and virtual management of operations. These technologies allowed manufacturers to sustain production during restrictions and adapt quickly to changing demands. In the post-pandemic era, the emphasis on resilient, flexible, and smart manufacturing has persisted, reinforcing edge-cloud integration as a key driver of industrial modernization.

The cloud computing segment is expected to be the largest during the forecast period

The cloud computing segment is expected to account for the largest market share during the forecast period as it offers manufacturer's scalable resources, robust data management, and powerful analytical tools. By leveraging cloud platforms, companies can centralize production data, enhance supply chain visibility, and foster collaboration across geographically dispersed plants. Cloud systems support predictive maintenance, digital twins, and AI-powered automation by processing information efficiently at scale. They minimize dependence on costly infrastructure, delivering flexibility and cost savings. With seamless integration into IoT ecosystems and strong support for smart manufacturing initiatives, cloud computing stands out as the leading segment, driving industrial digital transformation globally.

The AI and machine learning segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the AI and machine learning segment is predicted to witness the highest growth rate. These technologies enhance manufacturing by enabling predictive analytics, intelligent automation, and dynamic process adjustments. At the edge, AI accelerates decision-making by analyzing real-time machine data instantly, while cloud systems apply machine learning models to identify patterns and forecast outcomes. This combination boosts production efficiency, minimizes errors, and ensures proactive maintenance. Their adaptability allows factories to continuously optimize operations, reduce costs, and improve product quality. As smart manufacturing accelerates globally, AI and machine learning are becoming pivotal growth engines for this market.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, fueled by its early adoption of technologies, substantial investments, and a strong industrial foundation. The United States stands out with its significant investments in smart manufacturing, IoT integration, and digital transformation initiatives. Industries such as automotive, aerospace, and electronics utilize edge and cloud solutions to improve operational efficiency, predictive maintenance, and real-time analytics. The presence of major technology companies and a favorable regulatory environment further strengthen the region's leadership. While North America currently leads, the Asia-Pacific region is projected to experience the highest growth rates in the coming years.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. This growth is fueled by swift industrial advancement, the implementation of Industry 4.0 standards, and the establishment of 5G networks. Nations such as China, Japan, and South Korea are pioneering the integration of Internet of Things (IoT) devices, artificial intelligence (AI), and real-time data processing into their manufacturing sectors. The region's commitment to digital innovation, along with favorable government policies and substantial investments in technological infrastructure, is creating a supportive ecosystem for the expansion of edge and cloud computing technologies in manufacturing.

Key players in the market

Some of the key players in Edge & Cloud Computing in Manufacturing Market include Cisco, Dell Technologies, Microsoft, Amazon Web Services (AWS), Google Cloud Platform, IBM, Hewlett Packard Enterprise (HPE), Intel, Oracle, Plex Systems, Inc., Salesforce, VMware, Alibaba Cloud, Tencent Cloud and PTC Inc.

Key Developments:

In September 2025, Google Cloud has won a new contract worth £400m ($543m) to provide a sovereign cloud capability for the UK Ministry of Defence (MoD). This project will involve delivering a secure cloud platform that will facilitate innovation while offering the MoD with enhanced data control capabilities.

In August 2025, Intel Corporation announced an agreement with the Trump Administration to support the continued expansion of American technology and manufacturing leadership. Under terms of the agreement, the United States government will make an $8.9 billion investment in Intel common stock, reflecting the confidence the Administration has in Intel to advance key national priorities and the critically important role the company plays in expanding the domestic semiconductor industry.

In January 2025, Dell Technologies announced an expanded partnership with CoreWeave, a cloud infrastructure provider specialized in compute-intensive workloads like AI. CoreWeave will start using Dell's PowerEdge XE9712 server racks sporting NVIDIA's GB200 Grace Blackwell Superchip. CoreWeave is also using Dell IR7000 racks with fully-integrated liquid cooling technology.

Deployment Models Covered:

  • Edge Computing
  • Cloud Computing
  • Hybrid Architecture

Organization Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises (SMEs)

Technologies Covered:

  • IoT Sensors & Devices
  • AI & Machine Learning
  • 5G Connectivity
  • Digital Twin Platforms
  • Cybersecurity Solutions

Applications Covered:

  • Predictive Maintenance
  • Production Optimization
  • Inventory & Logistics Management
  • Energy Efficiency Monitoring
  • Quality Inspection & Assurance

End Users Covered:

  • Automotive
  • Electronics & Semiconductors
  • Pharmaceuticals
  • Food & Beverage
  • Heavy Machinery & Industrial Equipment

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Edge & Cloud Computing in Manufacturing Market, By Deployment Model

  • 5.1 Introduction
  • 5.2 Edge Computing
  • 5.3 Cloud Computing
  • 5.4 Hybrid Architecture

6 Global Edge & Cloud Computing in Manufacturing Market, By Organization Size

  • 6.1 Introduction
  • 6.2 Large Enterprises
  • 6.3 Small & Medium Enterprises (SMEs)

7 Global Edge & Cloud Computing in Manufacturing Market, By Technology

  • 7.1 Introduction
  • 7.2 IoT Sensors & Devices
  • 7.3 AI & Machine Learning
  • 7.4 5G Connectivity
  • 7.5 Digital Twin Platforms
  • 7.6 Cybersecurity Solutions

8 Global Edge & Cloud Computing in Manufacturing Market, By Application

  • 8.1 Introduction
  • 8.2 Predictive Maintenance
  • 8.3 Production Optimization
  • 8.4 Inventory & Logistics Management
  • 8.5 Energy Efficiency Monitoring
  • 8.6 Quality Inspection & Assurance

9 Global Edge & Cloud Computing in Manufacturing Market, By End User

  • 9.1 Introduction
  • 9.2 Automotive
  • 9.3 Electronics & Semiconductors
  • 9.4 Pharmaceuticals
  • 9.5 Food & Beverage
  • 9.6 Heavy Machinery & Industrial Equipment

10 Global Edge & Cloud Computing in Manufacturing Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 Cisco
  • 12.2 Dell Technologies
  • 12.3 Microsoft
  • 12.4 Amazon Web Services (AWS)
  • 12.5 Google Cloud Platform
  • 12.6 IBM
  • 12.7 Hewlett Packard Enterprise (HPE)
  • 12.8 Intel
  • 12.9 Oracle
  • 12.10 Plex Systems, Inc.
  • 12.11 Salesforce
  • 12.12 VMware
  • 12.13 Alibaba Cloud
  • 12.14 Tencent Cloud
  • 12.15 PTC Inc.

List of Tables

  • Table 1 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 3 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Edge Computing (2024-2032) ($MN)
  • Table 4 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Cloud Computing (2024-2032) ($MN)
  • Table 5 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Hybrid Architecture (2024-2032) ($MN)
  • Table 6 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 7 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 8 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 9 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Technology (2024-2032) ($MN)
  • Table 10 Global Edge & Cloud Computing in Manufacturing Market Outlook, By IoT Sensors & Devices (2024-2032) ($MN)
  • Table 11 Global Edge & Cloud Computing in Manufacturing Market Outlook, By AI & Machine Learning (2024-2032) ($MN)
  • Table 12 Global Edge & Cloud Computing in Manufacturing Market Outlook, By 5G Connectivity (2024-2032) ($MN)
  • Table 13 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Digital Twin Platforms (2024-2032) ($MN)
  • Table 14 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Cybersecurity Solutions (2024-2032) ($MN)
  • Table 15 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Application (2024-2032) ($MN)
  • Table 16 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Predictive Maintenance (2024-2032) ($MN)
  • Table 17 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Production Optimization (2024-2032) ($MN)
  • Table 18 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Inventory & Logistics Management (2024-2032) ($MN)
  • Table 19 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Energy Efficiency Monitoring (2024-2032) ($MN)
  • Table 20 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Quality Inspection & Assurance (2024-2032) ($MN)
  • Table 21 Global Edge & Cloud Computing in Manufacturing Market Outlook, By End User (2024-2032) ($MN)
  • Table 22 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 23 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Electronics & Semiconductors (2024-2032) ($MN)
  • Table 24 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Pharmaceuticals (2024-2032) ($MN)
  • Table 25 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Food & Beverage (2024-2032) ($MN)
  • Table 26 Global Edge & Cloud Computing in Manufacturing Market Outlook, By Heavy Machinery & Industrial Equipment (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.