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市场调查报告书
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1444849

产业分析：市场占有率分析、产业趋势与统计、成长预测（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个工作天内

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简介目录

产业分析市场规模预计到 2024 年为 326 亿美元，预计到 2029 年将达到 712.3 亿美元，在预测期内（2024-2029 年）复合年增长率为 16.92%。

产业分析-市场

工业4.0的兴起将在预测期内推动市场。物联网和工业物联网部署数量的不断增加已成为全球市场工业分析的主要推动力。随着生产线中多个来源（包括感测器、机器视觉系统和 PLC）提供更多资料，该产业正在从资料指标模型转向资料分析模型。

主要亮点

  • 工业分析涉及工业运作产生的资料的收集、分析和使用。涵盖从设备和来源撷取的各种资料，无论是资产还是生产流程。任何带有感测器的东西都会产生资料，工业分析会检查所有这些资料。
  • 工业分析与巨量资料分析系统的不同之处在于，它们旨在满足严格的行业标准。这涉及处理来自众多来源的大量时间序列资料并将其转化为可行的见解。行业分析与任何製造和销售实体产品的公司相关。
  • 工业分析的典型和传统方法涉及资料科学家建立分析模型。资料科学家需要了解使用案例场景，并收集、转换、优化资料并将其载入到开发的资料模型中，这需要检验、最佳化和培训。完成的资料模型回答了第一个问题。
  • 然而，这种方法使组织对资料科学家的依赖，导致主题专家 (SME)（工程师和操作员）必须充分理解解决方案。此外，在过去几年中，市场出现了自助服务服务应用日益增长的趋势。这款新一代软体采用先进的搜寻演算法、机器学习 (ML) 和模式识别技术，使查询工业资料就像使用 Google 一样简单。
  • 工业分析解决方案着重自助服务，为工厂的日常运作带来好处。这包括增强的根本原因分析、准确的效能预测、自动监控和知识保留。透过与使用者共用分析见解，您可以在趋势出现时立即采取行动，直接有助于提高所有生产层级的整体工厂绩效。
  • COVID-19的爆发迫使世界各地的企业调整策略以在「新常态」中生存。客户也改变了他们的优先事项。许多人在网上购物，或发现不久前他们经常去的商店只提供送货服务。儘管公司对某些产品的需求激增，但由于 COVID-19 停产对市场产生了负面影响，整个行业实际上停止了营运。

产业分析市场趋势

预测期内製造业主导市场

  • 工业 4.0 使製造商能够在全球范围内过渡到未来的製造业，从而彻底改变製造业。随着製造业中工业 4.0 的出现，各个工厂正在实施 IIoT、AI、ML 和机器人技术等数位技术，以增强、自动化和现代化整个流程。
  • 整合不同的技术变得越来越普及，因为它提供了巨大的好处。如前所述，利用技术开展新的业务方式是工业 4.0 中企业获得竞争优势并提高盈利和扩充性的关键要素。
  • 工业物联网等技术预计将连接数百万个物体，并确保整个价值链自动化。将分析引入製造业将能够即时收集这些技术产生的大量资料，为製造商提供可行的见解，减少机器停机时间并提高生产率，这有望促进客製化和自动化。
  • 工业分析应用预计将逐步提高整个供应链生产流程的生产力和效率。例如，製造流程将能够使用智慧机器和设备进行自我管理，这些机器和设备可以采取纠正措施以避免机器故障。各个零件会根据即时资料自动补充。
  • 製造业中的资料驱动公司已经在利用物联网产生的资料，将其输入到现有的分析管道中，以降低可变成本并提高营运管理和效率。
  • 物联网 (IoT) 和高阶分析相关技术的出现显着增加了创新机会。製造商习惯在工厂中利用物联网技术，联网感测器可以实现更好的规划和预测性维护。许多製造商目前正在为其本地边缘云端投资基于 5G 的行动专用网路。此策略的显着优势包括速度、低延迟、可靠性、容量和强大的安全性。在公开通报的 150 多个基于 4G/5G 的专用网路中，四分之一已采用 5G。製造商使用了其中约 40%。物联网和基于 5G 的工业应用可以从这些基于 5G 的云端中受益匪浅。对这些因素进行分析，以提高预测期内市场的成长率。

北美占据主要市场占有率

  • 云端运算、人工智慧、巨量资料和分析、行动/社交媒体、网路安全和物联网等先进技术被用来带来创新和转型，从而刺激北美商业生态系统的成长。这些技术已将传统的商业方法转变为现代方法。此外，潜在经济体对数位化投资的增加正在使该地区成为数位转型市场的新热点。这些趋势预计将推动该地区各行业采用工业分析。
  • 例如，美国预计将主导全球工业4.0市场，国内企业迅速采用智慧製造概念。工业 4.0 技术可提高营运效率、提高生产力、优化成本并减少停机时间。该国大多数工厂已经配备了采用最新机械和行业分析的智慧工厂技术。透过跨产业部署技术，我们将能够收集可行的见解。
  • 此外，各行业越来越多地采用先进通讯技术预计将为该地区工业分析的采用创造重大机会。据 GSMA 称，去年 5G 连线预计将占北美所有行动连线的 14%。到 2025 年，预计将达到所有连接的 46%。该技术将促进自动化仓储、自动化组装、连网物流、包装和产品处理以及自动购物车，因为快速、安全的连网型连接预计将实现敏捷营运和灵活生产。
  • 例如，根据 GSMA 的数据，2018 年北美物联网专业服务收益和物联网连接收益分别​​达到 250 亿美元和 80 亿美元，预计 2025 年将分别达到 1,010 亿美元和 160 亿美元。虽然新技术可以在现有系统上利用，但领先的製造商正在数位化方面投入大量资金，为该地区的行业分析创造了动力。

产业分析 产业概况

主要参与者包括英特尔、思科系统、IBM、通用电气、亚马逊、甲骨文公司、惠普、微软公司、简柏特等。由于工业 4.0 的采用以及公司在研发上花费大量资金以改善营运活动，主要参与者之间的竞争加剧，市场已变得碎片化。因此，市场集中度较低。

  • 2022 年 8 月 - 总部位于柏林的 Industrial Analytics 公司被英飞凌科技股份公司收购。英飞凌正在加强其人工智慧软体和服务业务，以对机械和工业设备进行预测分析。英飞凌将收购所有已发行股。工业分析创建了用于监控工厂的人工智慧系统，例如根据振动的收集和评估来儘早检测关键发展。 Industrial Analytics 的人工智慧解决方案分析资料并为预测性维护提出可行的提案。

其他福利

  • Excel 格式的市场预测 (ME) 表
  • 3 个月分析师支持

目录

第一章简介

  • 研究假设和市场定义
  • 调查范围

第二章调查方法

第三章执行摘要

第四章市场洞察

  • 市场概况
  • 产业吸引力－波特五力分析
    • 供应商的议价能力
    • 买方议价能力
    • 新进入者的威胁
    • 替代产品的威胁
    • 竞争公司之间的敌意强度
  • 评估 COVID-19感染疾病对市场的影响

第五章市场动态

  • 市场驱动因素
    • 资讯科技领域对巨量资料的需求日益增长
    • 电商领域需求不断增加
  • 市场限制因素
    • 整个行业缺乏熟练的专业人才。

第六章市场区隔

  • 按配置
    • 本地
    • 云
  • 按成分
    • 软体
    • 服务
  • 按类型
    • 预测分析
    • 规定性分析
    • 说明分析
  • 按最终用户产业
    • 建造
    • 製造业
    • 矿业
    • 运输
    • 其他最终用户产业
  • 按地区
    • 北美洲
    • 欧洲
    • 亚太地区
    • 拉丁美洲
    • 中东和非洲

第七章 竞争形势

  • 公司简介
    • 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.

第八章投资分析

第9章市场的未来

简介目录
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