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1641909

產業分析：市場佔有率分析、產業趨勢與統計、成長預測（2025-2030 年）

Industrial Analytics - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2025 - 2030)
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

預計 2025 年工業分析市場規模將達到 381.2 億美元，預計到 2030 年將達到 832.8 億美元，預測期內（2025-2030 年）的複合年成長率為 16.92%。

工業分析-市場-IMG1

預測期內，工業 4.0 的興起將推動市場發展。物聯網 (IoT) 和工業物聯網 (IIoT) 的採用數量不斷增加是全球市場工業分析的關鍵推動因素。生產線上來自多個來源的資料（包括感測器、機器視覺系統和 PLC）的增加正在使產業從資料測量模型轉變為資料分析模型。

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。它涵蓋了從設備和來源獲取的廣泛資料，無論是資產還是生產過程。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，它們的設計旨在滿足業務在產業的嚴格標準。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操作的見解。工業分析與任何生產或銷售實體產品的企業相關。
  • 在典型的傳統工業分析方法中，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、最佳化和載入資料到開發的資料模型中。完成的資料模型提供了第一個問題的答案。
  • 然而，這種方法使得組織依賴資料科學家，並導致解決方案需要由主題專家（SMEs）（工程師和操作員）充分理解。此外，過去幾年來，市場自助服務應用的趨勢日益成長。這款新一代軟體使用先進的搜尋演算法、機器學習 (ML) 和模式識別技術，使查詢工業資料變得像使用 Google 一樣簡單。
  • 工業分析解決方案專注於自助服務並為日常工廠運作帶來益處。這包括增強的根本原因分析、準確的效能預測、自動監控、知識保留等。與使用者共用分析見解使他們能夠在趨勢出現時立即採取行動，直接有助於提高各個生產層面的整體工廠績效。
  • 新冠肺炎疫情迫使全球企業調整策略，以在「新常態」下生存。顧客的優先考慮也發生了變化。許多顧客開始在網路上購物，或發現他們曾經經常光顧的商店現在只提供送貨上門服務。儘管企業發現某些產品的需求激增，但由於新冠疫情導致的停工對市場產生了負面影響，整個行業實際上已經停工。

工業分析市場趨勢

預測期內製造業將主導市場

  • 工業 4.0 正在推動世界向未來製造業轉變，徹底改變製造業。隨著工業 4.0 在製造業的出現，工廠正在採用 IIoT、AI、ML 和機器人等數位技術來增強、自動化和現代化其整個流程。
  • 各種技術的整合因其可帶來顯著的優勢而變得越來越流行。利用上述技術進行新的商業實務是工業4.0的關鍵要素，有助於企業取得競爭優勢、提高盈利和擴充性。
  • 工業IoT等技術可望連結數百萬件事物，實現整個價值鏈的自動化。將分析技術引入製造業將能夠即時收集這些技術產生的大量資料，為製造商提供切實可行的見解，減少機器停機時間並提高生產率。
  • 工業分析應用可望逐步提高整個供應鏈的生產過程的生產力和效率。例如，製造過程將能夠自我管理，智慧機器和設備可以採取糾正措施以避免機器故障。根據即時資料自動補充各個零件。
  • 製造業的資料主導公司已經在利用物聯網產生的資料來輸入現有的分析管道，透過降低可變成本來提高業務控制和效率。
  • 物聯網 (IoT) 和高階分析相關技術的可用性為創新提供了重大機會。製造商越來越熟悉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投資基於5G的行動專用網路，用於內部邊緣雲。此策略具有顯著的優勢：速度快、延遲低、可靠性高、容量大、安全性強。在公開通報的150多個基於4G/5G的私有網路中，四分之一已經採用了5G。製造業使用了其中的約40%。物聯網和基於5G的工業應用可以從這個基於5G的雲端中受益匪淺。預計這些因素將在預測期內推動市場成長率。

北美佔據主要市場佔有率

  • 雲端運算、人工智慧、巨量資料、分析、行動/社群媒體、網路安全和物聯網等新興技術正在推動創新和轉型，刺激北美商業生態系統的成長。這些技術正在將傳統的商業方法轉變為現代方法。此外，隨著潛在經濟體對數位化的投資不斷增加，該地區正迅速成為數位轉型市場的新熱點。這些趨勢預計將推動該地區所有行業更多地採用工業分析。
  • 例如，由於美國將主導全球工業 4.0 市場。工業 4.0 技術提高了業務效率、增加了生產力、最佳化了成本並減少了停機時間。該國大多數工廠已經配備了使用工業分析的最新機械和智慧工廠技術。這將使我們能夠從每個行業的技術採用中收集可行的見解。
  • 此外，各行業日益廣泛地部署先進通訊技術預計將為該地區採用工業分析創造重大機會。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%。快速、安全的 5G 連接有望實現敏捷營運和靈活生產，從而推動自動化倉庫、自動化組裝、互聯物流、包裝和產品處理、自動推車等技術的發展。
  • 例如，根據GSMA的數據，2018年北美物聯網專業服務收益達到250億美元，物聯網連接收益達到80億美元，預計2025年將達到1,010億美元和160億美元。中小企業在將新技術融入現有系統方面變得更加靈活，而大型製造商則在數位化方面投入了大量預算，從而推動了該地區的工業分析。

工業分析行業概覽

主要企業包括英特爾、Cisco、IBM、通用電氣、亞馬遜、Oracle公司、惠普、微軟公司和 Genpact。工業4.0的採用以及為提高業務績效而投入的巨額研發費用，導致領先企業之間的競爭異常激烈，市場也變得分散。因此，預計市場集中度較低。

  • 2022 年 8 月－總部位於柏林的 Industrial Analytics 被英飛凌科技股份公司收購。英飛凌將加強其人工智慧軟體和服務業務，為機械和工業設備提供預測分析。英飛凌將收購該業務所有已發行股。基於對振動的收集和評估，Industrial Analytics 開發了用於監控工廠的人工智慧系統，例如用於提前發現關鍵進展。工業分析 AI 解決方案可以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 個月的分析師支持

目錄

第 1 章 簡介

  • 研究假設和市場定義
  • 研究範圍

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
    • 購買者/消費者的議價能力
    • 新進入者的威脅
    • 替代品的威脅
    • 競爭對手之間的競爭強度
  • COVID-19 市場影響評估

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增加
    • 電子商務領域的需求增加
  • 市場限制
    • 各行業專業工程師短缺

第6章 市場細分

  • 按部署
    • 本地
    • 雲
  • 按組件
    • 軟體
    • 按服務
  • 按類型
    • 預測分析
    • 指示性分析
    • 說明分析
  • 按最終用戶產業
    • 建設業
    • 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 競爭格局

  • 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 38.12 billion in 2025, and is expected to reach USD 83.28 billion by 2030, at a CAGR of 16.92% during the forecast period (2025-2030).

Industrial Analytics - Market - IMG1

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