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1444849

產業分析：市場佔有率分析、產業趨勢與統計、成長預測（2024-2029）

Industrial Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2024 - 2029)
出版日期: | 出版商: Mordor Intelligence | 英文 120 Pages | 商品交期: 2-3個工作天內

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簡介目錄

產業分析市場規模預計到 2024 年為 326 億美元，預計到 2029 年將達到 712.3 億美元，在預測期內（2024-2029 年）年複合成長率為 16.92%。

產業分析-市場

工業4.0的興起將在預測期內推動市場。物聯網和工業物聯網部署數量的不斷增加已成為全球市場工業分析的主要推動力。隨著生產線中多個來源（包括感測器、機器視覺系統和 PLC）提供更多資料，該產業正在從資料指標模型轉向資料分析模型。

主要亮點

  • 工業分析涉及工業運作產生的資料的收集、分析和使用。涵蓋從設備和來源擷取的各種資料，無論是資產還是生產流程。任何帶有感測器的東西都會產生資料，工業分析會檢查所有這些資料。
  • 工業分析與巨量資料分析系統的不同之處在於，它們旨在滿足嚴格的行業標準。這涉及處理來自眾多來源的大量時間序列資料並將其轉化為可行的見解。行業分析與任何製造和銷售實體產品的公司相關。
  • 工業分析的典型和傳統方法涉及資料科學家建立分析模型。資料科學家需要了解使用案例場景，並收集、轉換、最佳化資料並將其載入到開發的資料模型中，這需要檢驗、最佳化和培訓。完成的資料模型回答了第一個問題。
  • 然而，這種方法使組織對資料科學家的依賴，導致主題專家 (SME)（工程師和操作員）必須充分理解解決方案。此外，在過去幾年中，市場出現了自助服務服務應用日益成長的趨勢。這款新一代軟體採用先進的搜尋演算法、機器學習 (ML) 和模式識別技術，使查詢工業資料就像使用 Google 一樣簡單。
  • 工業分析解決方案著重自助服務，為工廠的日常運作帶來好處。這包括增強的根本原因分析、準確的效能預測、自動監控和知識保留。透過與使用者共用分析見解，您可以在趨勢出現時立即採取行動，直接有助於提高所有生產層級的整體工廠績效。
  • COVID-19的爆發迫使世界各地的企業調整策略以在「新常態」中生存。客戶也改變了他們的優先事項。許多人在網上購物，或發現不久前他們經常去的商店只提供送貨服務。儘管公司對某些產品的需求激增，但由於 COVID-19 停產對市場產生了負面影響，整個行業實際上停止了營運。

產業分析市場趨勢

預測期內製造業主導市場

  • 工業 4.0 使製造商能夠在全球範圍內過渡到未來的製造業，從而徹底改變製造業。隨著製造業中工業 4.0 的出現，各個工廠正在實施 IIoT、AI、ML 和機器人技術等數位技術，以增強、自動化和現代化整個流程。
  • 整合不同的技術變得越來越普及，因為它提供了巨大的好處。如前所述，利用技術開展新的業務方式是工業 4.0 中企業獲得競爭優勢並提高盈利和擴充性的關鍵要素。
  • 工業物聯網等技術預計將連接數百萬個物體，並確保整個價值鏈自動化。將分析引入製造業將能夠即時收集這些技術產生的大量資料，為製造商提供可行的見解，減少機器停機時間並提高生產率，這有望促進客製化和自動化。
  • 工業分析應用預計將逐步提高整個供應鏈生產流程的生產力和效率。例如，製造流程將能夠使用智慧機器和設備進行自我管理，這些機器和設備可以採取糾正措施以避免機器故障。各個零件會根據即時資料自動補充。
  • 製造業中的資料驅動公司已經在利用物聯網產生的資料，將其輸入到現有的分析管道中，以降低可變成本並提高營運管理和效率。
  • 物聯網 (IoT) 和高階分析相關技術的出現顯著增加了創新機會。製造商習慣在工廠中利用物聯網技術，聯網感測器可以實現更好的規劃和預測性維護。許多製造商目前正在為其本地邊緣雲端投資基於 5G 的行動專用網路。此策略的顯著優勢包括速度、低延遲、可靠性、容量和強大的安全性。在公開通報的 150 多個基於 4G/5G 的專用網路中，四分之一已採用 5G。製造商使用了其中約 40%。物聯網和基於 5G 的工業應用可以從這些基於 5G 的雲端中受益匪淺。對這些因素進行分析，以提高預測期內市場的成長率。

北美佔據主要市場佔有率

  • 雲端運算、人工智慧、巨量資料和分析、行動/社交媒體、網路安全和物聯網等先進技術被用來帶來創新和轉型，從而刺激北美商業生態系統的成長。這些技術已將傳統的商業方法轉變為現代方法。此外，潛在經濟體對數位化投資的增加正在使該地區成為數位轉型市場的新熱點。這些趨勢預計將推動該地區各行業採用工業分析。
  • 例如，美國預計將主導全球工業4.0市場，國內企業迅速採用智慧製造概念。工業 4.0 技術可提高營運效率、提高生產力、最佳化成本並減少停機時間。該國大多數工廠已經配備了採用最新機械和行業分析的智慧工廠技術。透過跨產業部署技術，我們將能夠收集可行的見解。
  • 此外，各行業擴大採用先進通訊技術預計將為該地區工業分析的採用創造重大機會。據 GSMA 稱，去年 5G 連線預計將佔北美所有行動連線的 14%。到 2025 年，預計將達到所有連接的 46%。該技術將促進自動化倉儲、自動化組裝、連網物流、包裝和產品處理以及自動購物車，因為快速、安全的連網型連接預計將實現敏捷營運和靈活生產。
  • 例如，根據 GSMA 的數據，2018 年北美物聯網專業服務收益和物聯網連接收益分別​​達到 250 億美元和 80 億美元，預計 2025 年將分別達到 1,010 億美元和 160 億美元。雖然新技術可以在現有系統上利用，但領先的製造商正在數位化方面投入大量資金，為該地區的行業分析創造了動力。

產業分析 產業概況

主要參與者包括英特爾、思科系統、IBM、通用電氣、亞馬遜、甲骨文公司、惠普、微軟公司、簡柏特等。由於工業 4.0 的採用以及公司在研發上花費大量資金以改善營運活動，主要參與者之間的競爭加劇，市場已變得碎片化。因此，市場集中度較低。

  • 2022 年 8 月 - 總部位於柏林的 Industrial Analytics 公司被英飛凌科技股份公司收購。英飛凌正在加強其人工智慧軟體和服務業務，以對機械和工業設備進行預測分析。英飛凌將收購所有已發行股。工業分析創建了用於監控工廠的人工智慧系統，例如根據振動的收集和評估來儘早檢測關鍵發展。 Industrial Analytics 的人工智慧解決方案分析資料並為預測性維護提出可行的提案。

其他福利

  • Excel 格式的市場預測 (ME) 表
  • 3 個月分析師支持

目錄

第1章簡介

  • 研究假設和市場定義
  • 調查範圍

第2章調查方法

第3章執行摘要

第4章市場洞察

  • 市場概況
  • 產業吸引力－波特五力分析
    • 供應商的議價能力
    • 買方議價能力
    • 新進入者的威脅
    • 替代產品的威脅
    • 競爭公司之間的敵意強度
  • 評估 COVID-19感染疾病對市場的影響

第5章市場動態

  • 市場促進因素
    • 資訊科技領域對巨量資料的需求日益成長
    • 電商領域需求不斷增加
  • 市場限制因素
    • 整個行業缺乏熟練的專業人才。

第6章市場區隔

  • 按配置
    • 本地
    • 雲
  • 按成分
    • 軟體
    • 服務
  • 按類型
    • 預測分析
    • 規定性分析
    • 說明分析
  • 按最終用戶產業
    • 建造
    • 製造業
    • 礦業
    • 運輸
    • 其他最終用戶產業
  • 按地區
    • 北美洲
    • 歐洲
    • 亞太地區
    • 拉丁美洲
    • 中東和非洲

第7章 競爭形勢

  • 公司簡介
    • Cisco Systems
    • IBM Corporation
    • General Electric Company
    • Amazon Web Services Inc.
    • Oracle Corporation
    • Hewlett-Packard Enterprise
    • Robert Bosch GmbH
    • Microsoft Corporation
    • SAP SE
    • ABB Ltd.

第8章投資分析

第9章市場的未來

簡介目錄
Product Code: 62315

The Industrial Analytics Market size is estimated at USD 32.60 billion in 2024, and is expected to reach USD 71.23 billion by 2029, growing at a CAGR of 16.92% during the forecast period (2024-2029).

Industrial Analytics - Market

The rising Industry 4.0 will drive the market in the forecast period. An increasing number of IoT and IIoT installations are the primary enablers of industrial analytics in the global market. The growing data available from multiple sources across the production line, such as sensors, machine vision systems, PLCs, etc., are moving industries from data metrics models to data analytics models.

Key Highlights

  • Industrial analytics includes collecting, analyzing, and using data generated in industrial operations. It covers a wide range of data captured from devices and sources, whether an asset or a production process. Anything with the sensor creates data, and industrial analytics examines all this data.
  • Industrial analytics differs from Big Data analytics systems in that they are designed to meet the exacting standards of the industry in which they work. It includes processing vast quantities of time series data from numerous sources and turning it into actionable insights. Industrial analytics is relevant to any company that manufactures and sells physical products.
  • The typical and traditional approach to industrial analytics involves data scientists building an analytics model. Data scientists must understand the use case scenario and then gather, transform, optimize, and load the data in the developed data model, which needs to be validated, optimized, and trained. The completed data model delivers answers to the initial questions.
  • However, this approach leaves organizations dependent on their data scientists and results in a solution that subject matter experts (SMEs) (engineers and operators) might need to fully understand. Moreover, the market witnessed a growing trend toward self-service applications in the past few years. This next generation of software uses advanced search algorithms, machine learning (ML), and pattern recognition technologies to make querying industrial data as easy as using Google.
  • An industrial analytics solution focuses on self-service, resulting in benefits to day-to-day plant operation. It includes enhanced root cause analysis, accurate performance prediction, automated monitoring, and knowledge retention. By sharing analytics insights with users, they can take immediate action when a trend appears and directly contribute to improving overall plant performance at all production levels.
  • The COVID-19 outbreak forced companies worldwide to adjust their strategies to survive in the 'new normal.' Customers have changed their priorities, too. Many are shopping online or have found that the stores they frequented in person not so long ago only provide deliveries. Businesses witnessed surges in demand for some products, while entire industries virtually ceased operations due to COVID-19 shutdowns impacting the market adversely.

Industrial Analytics Market Trends

Manufacturing Sector to Dominate the Market Over the Forecast Period

  • Industry 4.0 is transforming the manufacturing industry by leaps and bounds by enabling them to make a global shift toward the futuristic manufacturing sector. With the advent of industry 4.0 in the manufacturing industry, various plants adopt digital technologies, such as IIoT, AI, ML, Robotics, and many more, to enhance, automate, and modernize the whole process.
  • Integrating different technologies is becoming prevalent, as it provides exceptional benefits. Leveraging the technologies, as mentioned earlier, into a new way of doing business is a crucial factor in Industry 4.0 for companies to gain a competitive edge and be more profitable and scalable.
  • Technologies like Industrial IoT are expected to connect millions of things to ensure that automation can be achieved across the entire value chain. Implementing analytics in the manufacturing industry is expected to boost customization and automation by collecting the vast amount of data generated by these technologies in real time, providing actionable insights to the manufacturers, reducing machine downtime, and enhancing productivity.
  • The industrial analytics application is expected to gradually improve production processes' productivity and efficiencies throughout the supply chain. For instance, the manufacturing processes would be capable of administering themselves, using intelligent machines and devices that can take corrective action, to avoid machine breakdowns. Individual parts would be automatically replenished based on real-time data.
  • Data-driven companies in the manufacturing sector are already using IoT-generated data by feeding them into their existing analytical pipeline and improving operational management and efficiencies by reducing variable costs.
  • Innovative opportunities are significantly increased by the technology availability related to the Internet of Things (IoT) and advanced analytics. Manufacturers are accustomed to utilizing IoT technology in their factories, where networked sensors allow for better planning and predictive maintenance. Many manufacturers currently invest in 5G-based mobile private networks for their on-premises edge cloud. Significant benefits of this strategy include speed, low latency, reliability, capacity, and strong security. A quarter of the more than 150 4G/5G-based private networks that have been publicly reported employ 5G. Manufacturers use about 40% of all of these. IoT and 5G-based industrial applications may greatly benefit from these 5G-based clouds. These factors are analyzed to boost the market growth rate during the forecast period.

North America to Account for Significant Market Share

  • The advanced technologies used, such as cloud computing, AI, big data and analytics, mobility/social media, cybersecurity, and IoT, have led to innovation and transformation, thereby stimulating growth in the business ecosystem of North America. These technologies have transformed the legacy approach to business into a modern approach. Also, the region is becoming a new hotspot in the digital transformation market due to rising investments in digitalization across potential economies. Such trends are expected to boost the adoption of industrial analytics across the industries in the region.
  • The United States, for instance, is expected to dominate the Industry 4.0 market globally, as the companies in the country are rapidly adopting the concept of smart manufacturing. Industry 4.0 technologies provide improved operational efficiency, enhanced productivity, optimization of costs, and reduction in downtime. Most of the factories in the country are already equipped with modern machines and smart factory technology, which uses industrial analytics. It enables them to gather actionable insights by deploying technologies across their industries.
  • Further, the growth in the advanced communication technologies deployment across industries is expected to create significant opportunities for adopting industrial analytics in the region. According to GSMA, in the previous year, 5G connections were forecast to account for 14% of all mobile connections in North America. By 2025, it is expected to reach 46% of the total connectivity. Since fast and secure 5G connectivity is expected to enable agile operations and flexible production, the technology is expected to facilitate automated warehouses, automated assembly, connected logistics, packing and product handling, and autonomous carts.
  • For example, according to GSMA, IoT professional services revenue and IoT connectivity revenue in North America amounted to USD 25 billion and USD 8 billion in 2018 and are forecasted to reach USD 101 billion and 16 billion in 2025. SMEs are becoming increasingly flexible in incorporating new technologies with their existing systems, whereas large manufacturers have heavy budgets for digitization, thus giving momentum to industrial analytics in the region.

Industrial Analytics Industry Overview

The major players include Intel, Cisco Systems, IBM, General Electric, Amazon.com, Oracle Corporation, Hewlett-Packard, Microsoft Corporation, and Genpact, amongst others. The market is fragmented since there is high competition among major players due to the adoption of industry 4.0 and the companies spending heavily on R&D for better operational activities. Therefore, the market concentration will be low.

  • August 2022-Industrial Analytics, a firm based in Berlin, was acquired by Infineon Technologies AG. Infineon is enhancing its artificial intelligence software and services business to perform predictive analysis on machinery and industrial equipment. Infineon is acquiring all outstanding shares of the business. Based on the collection and evaluation of vibrations, Industrial Analytics creates artificial intelligence systems that, for instance, monitor plants for the early detection of significant developments. Industrial Analytics' AI solutions analyze data for predictive maintenance and make actionable suggestions.

Additional Benefits:

  • The market estimate (ME) sheet in Excel format
  • 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

  • 1.1 Study Assumptions and Market Definition
  • 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

  • 4.1 Market Overview
  • 4.2 Industry Attractiveness - Porter's Five Forces Analysis
    • 4.2.1 Bargaining Power of Suppliers
    • 4.2.2 Bargaining Power of Buyers/Consumers
    • 4.2.3 Threat of New Entrants
    • 4.2.4 Threat of Substitute Products
    • 4.2.5 Intensity of Competitive Rivalry
  • 4.3 Assessment of Impact of COVID-19 on the Market

5 MARKET DYNAMICS

  • 5.1 Market Drivers
    • 5.1.1 Increasing Demand for Big-Data in Information Technology Sector
    • 5.1.2 Rising Demand from the E-commerce Sector
  • 5.2 Market Restraints
    • 5.2.1 Lack of Skilled Professional Across Industries

6 MARKET SEGMENTATION

  • 6.1 By Deployment
    • 6.1.1 On-premises
    • 6.1.2 Cloud
  • 6.2 By Component
    • 6.2.1 Software
    • 6.2.2 Services
  • 6.3 By Type
    • 6.3.1 Predictive Analytics
    • 6.3.2 Prescriptive Analytics
    • 6.3.3 Descriptive Analytics
  • 6.4 By End User Industry
    • 6.4.1 Construction
    • 6.4.2 Manufacturing
    • 6.4.3 Mining
    • 6.4.4 Transportation
    • 6.4.5 Other End User Industry
  • 6.5 By Geography
    • 6.5.1 North America
    • 6.5.2 Europe
    • 6.5.3 Asia Pacific
    • 6.5.4 Latin America
    • 6.5.5 Middle East and Africa

7 COMPETITIVE LANDSCAPE

  • 7.1 Company Profiles
    • 7.1.1 Cisco Systems
    • 7.1.2 IBM Corporation
    • 7.1.3 General Electric Company
    • 7.1.4 Amazon Web Services Inc.
    • 7.1.5 Oracle Corporation
    • 7.1.6 Hewlett-Packard Enterprise
    • 7.1.7 Robert Bosch GmbH
    • 7.1.8 Microsoft Corporation
    • 7.1.9 SAP SE
    • 7.1.10 ABB Ltd.

8 INVESTMENT ANAYSIS

9 FUTURE OF THE MARKET