工业4.0与智慧製造：2026-2030年

全球製造业正经历一场由工业4.0技术驱动的转型，自动化、互联互通和人工智慧正日益普及到整个生产环境中。这场转型促使人们对智慧製造技术的投资不断增加，并重塑工业营运的设计、执行和优化方式。

本报告对全球工业4.0和智慧製造生态系统进行了系统分析，重点关注整个技术堆迭及其底层技术。其主要目标是定义、估算规模并分析关键组件，例如边缘硬体、平台/中间件、应用程式、安全性、基础技术和服务，从而帮助了解当前的行业格局。

报告摘要

• 一份 406 页的报告：对全球智慧製造市场进行全面分析，涵盖技术、趋势、供应商格局和采用趋势。
• 25 个技术类别：对整个工业 4.0 技术堆迭的核心和支援技术进行详细分析，包括边缘、平台、应用和安全。
• 超过 50 个趋势和挑战：检验IT/OT 融合、工业人工智慧和软体定义製造等综合趋势，以及采用的主要障碍。
• 供应商格局（超过 240 家公司）：关键细分市场的竞争分析（包括主要工业和技术供应商的简介）
• 市场规模及预测：全球智慧製造市场按细分市场、技术、地区和产业分類的分析与预测（至2030年）

上市公司

本报告中提及的部分公司：

• ABBAccentureAdvantechBeckhoff AutomationCapgeminiDeloitteEmersonEndress+HauserFanucHoneywellIBMKeyenceKUKAMicrosoftMitsubishi ElectricOmronRockwell AutomationSAPSchneider ElectricSiemensYaskawaYokogawa

目录

第一章执行摘要

第二章：引言

• 本章概要及要点
• 历史背景
• 智慧製造的定义与应用
• 对智慧製造和工业4.0的兴趣
• 智慧製造与智慧互联产品
• 主要组织的定义
• 透过物联网分析定义智慧製造
• 定义中的通用
• 调查范围
• 智慧製造技术成熟度模型
• 工业4.0标竿管理与生产力提升
• 製造业就业与机器人密度
• 工业4.0成熟度现状
• 技术优先事项
• 未来几年的展望
• 产业研究
• 实施的典型益处
• 例如：WEF灯塔工厂

第三章 市场概览与竞争格局

• 市场规模及展望概述
• 全球智慧製造市场
• 常见的促进因素和阻碍因素
• 数据的全面概述
• 全球智慧製造市场：按细分市场划分
• 全球智慧製造市场：依技术划分
• 全球智慧製造市场技术份额的变化
• 工业4.0技术：成长与成熟
• 综合前 20 名的智慧製造供应商
• 主要企业简介：ABB
• 主要企业简介：西门子
• 主要企业简介：艾默生
• 主要企业简介：施耐德电气
• 主要企业简介：微软

第四章：总体趋势与挑战

• 章节概要
• 趋势
• 整体挑战概述
• 任务

第五章：核心技术栈

• 本章概要及要点
• 智慧製造技术栈的组成部分
• 全球智慧製造核心技术堆迭市场：按细分市场划分
• 优势和市场规模的定义
• 边缘硬体：竞争格局
• 全球智慧製造边缘市场：按地区和产业划分
• 边缘运算市场细分详情
• 边缘：现场测量仪器
• 边缘：远端 I/O
• Edge：PLC
• Edge：DCS
• 边缘：人机介面
• 边缘：网关
• 边缘：IPC
• 前沿趋势：概述
• 边缘趋势
• 平台/中介软体定义及市场规模
• 平台/中介软体：竞争格局
• 全球智慧製造平台/中介软体市场：按地区和产业划分
• 平台/中介软体市场的详细细分
• 平台/中介软体：讯息仲介
• 平台/中介软体：设备管理
• 平台/中间件：应用程式管理
• 平台/中介软体：资料管理
• 平台/中介软体：工业数据运营
• 平台/中介软体：人工智慧平台
• 平台/中介软体：通讯协定转换工具
• 平台/中介软体趋势：概述
• 平台/中介软体趋势
• 智慧製造软体应用：定义与市场规模
• 应用领域：竞争格局
• 全球智慧製造应用市场：按地区和产业划分
• 详细应用市场细分
• 应用领域：工业自动化软体
• 应用：MOM/MES
• 应用领域：资产绩效与管理
• 应用领域：工厂物流
• 应用趋势：概述
• 应用趋势
• 安全定义
• 安全性：关键软体元件
• 安防市场规模及竞争格局
• 全球智慧製造安全市场：按地区和产业划分
• 安全市场的详细细分领域
• 安全趋势：概述
• 安全趋势

第六章 辅助技术

• 章节概要
• 智慧製造的组成：辅助技术
• 全球智慧製造支援技术市场：按细分市场和地区划分
• 技术支援：竞争格局
• 辅助科技市场详细细分
• 积层製造：定义、应用案例、市场、趋势
• 固定式机器人：定义、应用案例、市场及趋势
• 自主移动机器人：定义、应用案例、市场与趋势
• 机器视觉：定义、应用案例、市场与趋势
• 扩增实境：定义、应用案例、市场、趋势
• 人形机器人：供应商列表

第七章 服务

• 本章概要及要点
• 智慧製造专业服务概述
• 从采用者的观点：是购买还是内部开发？
• 智慧製造专业服务：市场规模
• 案例研究：供应商服务交付方式
• 趋势与挑战概述
• 趋势
• 最终用户挑战

第八章 用例

• 章节概要
• KPI优化和OEE
• 用例的采纳和定义
• 用例

第九章：案例研究

• 案例研究：全面洞察
• 案例研究1：Gousto
• 案例研究2：米其林
• 案例研究3：乔治亚-太平洋公司
• 案例研究4：福特
• 案例研究5：罗氏

第十章：实施情况

• 章节概要
• 终端使用者使用情况调查：概述
• 智慧工厂的现状：扩充性和安全性
• 智慧工厂范式与技术
• 问题的严重性
• 网路安全漏洞范例
• 已采用智慧工厂的主要公司
• 对已采用该系统的主要公司进行分析
• 特斯拉柏林超级工厂
• 实施过程中的挑战与障碍
• 人工智慧对应用的影响
• 人工智慧实施、要素和成本降低

第十一章：调查方法与市场定义

第十二章：关于物联网分析

A 406-page report analyzing the global smart manufacturing market, with a deep-dive into 25 key technologies, 52 individual trends, and the competitive landscape of 240+ vendors.

The global manufacturing sector is undergoing a transformation driven by Industry 4.0 technologies, with increasing adoption of automation, connectivity, and artificial intelligence across production environments. This transformation is expanding investments in smart manufacturing technologies and reshaping how industrial operations are designed, executed, and optimized.

This report provides a structured analysis of the global Industry 4.0 and smart manufacturing ecosystem, focusing on the full technology stack and its supporting technologies. Its primary objective is to help readers understand this landscape by defining, sizing, and analyzing key components, including edge hardware, platforms/middleware, applications, security, supporting technologies, and services.

The findings are based on extensive primary research, including interviews with 25+ experts from technology vendors and industrial end users, complemented by survey data and secondary research conducted across the smart manufacturing ecosystem.

Report at a glance

• 406-page report: A comprehensive analysis of the global smart manufacturing market, covering technologies, trends, vendor landscape, and adoption dynamics.
• 25 technology categories: Detailed analysis of core and supporting technologies across the Industry 4.0 stack, including edge, platforms, applications, and security.
• 50+ trends and challenges: Examination of overarching trends such as IT/OT convergence, industrial AI, and software-defined manufacturing, alongside key adoption barriers.
• Vendor landscape (240+ companies): Competitive analysis across major segments, including profiles of leading industrial and technology vendors.
• Market sizing and forecast: Global smart manufacturing market analysis by segment, technology, region, and industry, with forecasts to 2030.

Key areas of analysis

• Introduction to Industry 4.0 and smart manufacturing: Defines the scope of Industry 4.0, outlines key concepts, and positions smart manufacturing within the broader industrial transformation landscape.
• Big picture-The smart manufacturing market: Provides a global market overview, including market size, segmentation, growth drivers, and inhibitors shaping adoption.
• Industry 4.0 technology stack: Analyzes the core technology layers-edge hardware, platforms/middleware, applications, and security-including market size, competitive landscape, and trends.
• Supporting technologies deep dives: Covers key enabling technologies such as robotics, machine vision, additive manufacturing, augmented reality, and autonomous mobile robots, including market dynamics and use cases.
• Services and implementation landscape: Examines the role of professional services, system integration, and managed services in enabling smart manufacturing deployments.
• Use cases and case studies: Provides analysis of key smart manufacturing use cases and includes detailed real-world case studies demonstrating implementation and business impact.

A data-driven foundation for key business functions

• Strategy and corporate development: Inform strategic planning with market sizing, long-term forecasts, and analysis of macro trends such as AI adoption, IT/OT convergence, and reshoring.
• Product management and marketing: Guide product roadmaps using insights into technology evolution, competitive dynamics, and emerging Industry 4.0 use cases.
• R&D and engineering leadership: Prioritize technical investments based on detailed analysis of core technologies, software architectures, and integration trends across the stack.
• Market intelligence and competitive analysis: Benchmark positioning within the smart manufacturing ecosystem using vendor landscape analysis and technology-level insights.

Key concepts defined

• Industry 4.0: The current phase of industrial transformation is characterized by the integration of digital technologies-including IoT, AI, cloud computing, and automation-into industrial processes.
• Smart manufacturing: The application of Industry 4.0 technologies within production environments to improve operational efficiency, flexibility, and decision-making across the manufacturing value chain.
• Smart manufacturing technology stack: A structured framework consisting of edge hardware, platforms/middleware, applications, and security, supported by enabling technologies such as robotics and machine vision.
• Industrial AI: The use of artificial intelligence and machine learning within industrial environments to optimize processes, enable predictive capabilities, and automate decision-making.
• IT/OT convergence: The integration of information technology systems with operational technology on the shop floor, enabling seamless data flow and unified system architectures.

Questions answered

• How are smart manufacturing and Industry 4.0 defined?
• What are the 25 key technologies and components that make up smart manufacturing?
• How large is the smart manufacturing market, and how is it expected to grow (by region, by industry, by technology)?
• Who are the leading vendors and how are they positioned in the market?
• Who are the market leaders in each of the 25 individual technology categories across 240+ vendors?
• What is the role and size of the services market?
• Which use cases are driving adoption across industries?
• What are some of the standout case studies of smart manufacturing adoption?
• What are the main trends and challenges shaping smart manufacturing?

Companies mentioned

A selection of companies mentioned in the report.

• ABB
• Accenture
• Advantech
• Beckhoff Automation
• Capgemini
• Deloitte
• Emerson
• Endress+Hauser
• Fanuc
• Honeywell
• IBM
• Keyence
• KUKA
• Microsoft
• Mitsubishi Electric
• Omron
• Rockwell Automation
• SAP
• Schneider Electric
• Siemens
• Yaskawa
• Yokogawa

Table of Contents

1. Executive summary

• Executive summary (5 parts)
• 3 key action items from this report for...

2. Introduction

• Introduction-Chapter overview and key takeaways
• Historical context
• Smart manufacturing definition and application
• Interest in smart manufacturing and Industry 4.0
• Smart manufacturing vs. smart connected products
• Definitions by key organizations
• IoT Analytics' definition of smart manufacturing
• Commonalities in definitions
• Vertical scope of the report
• Smart manufacturing technology maturity models (2 parts)
• Industry 4.0 benchmarks and productivity gains
• Manufacturing jobs and robot density
• Current state of Industry 4.0 maturity
• Technology priorities
• Vision for the coming years
• Industry survey (2 parts)
• Typical benefits of implementation
• Example-WEF Lighthouse factory (2 parts)

3. Market overview & competitive landscape

• Market size & outlook overview
• Global smart manufacturing market-Overall
• General drivers and inhibitors
• Data in perspective
• Global smart manufacturing market-By segments
• Global smart manufacturing market-By technology
• Global smart manufacturing market-Technology share shifts
• Industry 4.0 technologies-Growth vs. Maturity
• Overall-Top 20 smart manufacturing vendors
• Key company profile-ABB (2 parts)
• Key company profile-Siemens (6 parts)
• Key company profile-Emerson (2 parts)
• Key company profile-Schneider Electric (2 parts)
• Key company profile-Microsoft (2 parts)

4. Overarching trends and challenges

• Overarching trends and challenges-Chapter overview
• Trend 1 (2 parts)
• Trend 2 (4 parts)
• Trend 3
• Trend 4
• Trend 5 (2 parts)
• Trend 6
• Overarching challenges-Overview
• Challenge 1
• Challenge 2
• Challenge 3
• Challenge 4
• Challenge 5

5. Core tech stack

• Industry 4.0 tech stack-Chapter overview and key takeaways
• Smart manufacturing tech stack elements (2 parts)
• Global Smart manufacturing core tech stack market-By segments
• Edge-Definition and Market size
• Edge hardware-Competitive landscape
• Global smart manufacturing edge market-By region and industry
• Detailed edge market segments (3 parts)
• Edge-Field instruments (2 parts)
• Edge-Remote I/O (2 parts)
• Edge-PLC (2 parts)
• Edge-DCS (2 parts)
• Edge-HMI (2 parts)
• Edge-Gateways (2 parts)
• Edge-IPCs (2 parts)
• Edge-Trends: Overview
• Edge-Trend 1 (2 parts)
• Edge-Trend 2
• Edge-Trend 3
• Edge-Trend 4 (3 parts)
• Edge-Trend 5
• Edge-Trend 6
• Platforms/middleware-Definition and Market size
• Platforms/middleware-Competitive landscape
• Global smart manufacturing platforms/middleware market-By region and industry
• Detailed platforms/middleware market segments (3 parts)
• Platforms/middleware-Message brokers (3 parts)
• Platforms/middleware-Device management (2 parts)
• Platforms/middleware-Application management (2 parts)
• Platforms/middleware-Data management (4 parts)
• Platforms/middleware-Industrial DataOps (2 parts)
• Platforms/middleware-AI platforms (2 parts)
• Platforms/middleware-Protocol converters (2 parts)
• Platforms/middleware-Trends: Summary
• Platforms/middleware-Trend 1 (3 parts)
• Platforms/middleware-Trend 2 (2 parts)
• Platforms/middleware-Trend 3 (2 parts)
• Platforms/middleware-Trend 4
• Platforms/middleware-Trend 5
• Platforms/middleware-Trend 6
• Platforms/middleware-Trend 7 (3 parts)
• Platforms/middleware-Trend 8
• Smart manufacturing software applications-Definition and Market size
• Applications-Competitive landscape
• Global smart manufacturing applications market-By region and industry
• Detailed applications market segments (3 parts)
• Applications: Industrial automation software (2 parts)
• Applications: MOM/MES (2 parts)
• Applications: Asset performance and management (2 parts)
• Applications: Factory logistics (2 parts)
• Applications: Trends: Summary
• Applications-Trend 1 (2 parts)
• Applications-Trend 2
• Applications-Trend 3
• Applications-Trend 4
• Applications-Trend 5
• Applications-Trend 6
• Applications-Trend 7
• Applications-Trend 8 (2 parts)
• Applications-Trend 9 (2 parts)
• Security-Definition
• Security: Key software components (7 parts)
• Security-Market size & competitive landscape
• Global smart manufacturing security market-By region and industry
• Detailed security market segments (3 parts)
• Security: Trends: Summary
• Security-Trend 1
• Security-Trend 2 (2 parts)
• Security-Trend 3
• Security-Trend 4
• Security-Trend 5

6. Supporting technologies

• Smart manufacturing supporting technologies-Chapter overview
• Elements of smart manufacturing-Supporting technologies
• Global smart manufacturing supporting technologies market-By segments and region
• Supporting Tech-Competitive landscape
• Detailed supporting technologies market segments (3 parts)
• Additive manufacturing-Definition, use cases, market, and trends (6 parts)
• Stationary robots-Definition, use cases, market, and trends (11 parts)
• Autonomous mobile robots-Definition, use cases, market, and trends (7 parts)
• Machine vision-Definition, use cases, market, and trends (11 parts)
• Augmented reality-Definition, use cases, market, and trends (4 parts)
• Humanoid robots-Select vendors

7. Services

• Services-Chapter overview and key takeaways
• Professional services for smart manufacturing-Overview (3 parts)
• Adopter perspective-Buy or build? (2 parts)
• Professional services for smart manufacturing-Market size
• Example-How vendors provide smart manufacturing services
• Trends & challenges overview
• Trend 1 (3 parts)
• Trend 2
• Trend 3 (2 parts)
• End-user challenge 1 (4 parts)
• End-user challenge 2
• End-user challenge 3

8. Use cases

• Use case analysis-Chapter overview
• KPI optimization and OEE
• Use case adoption and definitions (2 parts)
• Use cases 1 through 14

9. Case studies

• Case studies-Overarching insights
• Case study 1: Gousto (10 parts)
• Case study 2: Michelin (10 parts)
• Case study 3: Georgia-Pacific (9 parts)
• Case study 4: Ford (16 parts)
• Case study 5: Roche (12 parts)

10. Adoption landscape

• Adoption landscape-Chapter overview
• End user adoption-Survey overviews (2 parts)
• State of smart factories-Scalability and security
• Smart factory paradigms and technologies
• Severity of challenges
• Cybersecurity breaches examples
• Leading smart factory adopters
• Analysis of leading adopters (3 parts)
• Tesla Giga Berlin example
• Challenges and adoption barriers
• Impact of AI on applications
• AI adoption, elements, and cost savings

11. Methodology & market definitions

• Research Methodology

12. About IoT Analytics

• About IoT Analytics and other publications
• Information and contact