工業4.0與智慧製造：2026-2030年

全球製造業正經歷一場由工業4.0技術驅動的轉型，自動化、互聯互通和人工智慧正日益普及到整個生產環境中。這場轉型促使人們對智慧製造技術的投資不斷增加，並重塑工業營運的設計、執行和最佳化方式。

本報告對全球工業4.0和智慧製造生態系統進行了系統分析，重點關注整個技術堆疊及其底層技術。其主要目標是定義、估算規模並分析關鍵組件，例如邊緣硬體、平台/中間件、應用程式、安全性、基礎技術和服務，從而幫助了解當前的行業格局。

報告摘要

• 一份 406 頁的報告：對全球智慧製造市場進行全面分析，涵蓋技術、趨勢、供應商格局和採用趨勢。
• 25 個技術類別：對整個工業 4.0 技術堆疊的核心和支援技術進行詳細分析，包括邊緣、平台、應用和安全。
• 超過 50 個趨勢和挑戰：檢驗IT/OT 融合、工業人工智慧和軟體定義製造等綜合趨勢，以及採用的主要障礙。
• 供應商格局（超過 240 家公司）：關鍵細分市場的競爭分析（包括主要工業和技術供應商的簡介）
• 市場規模及預測：全球智慧製造市場按細分市場、技術、地區和產業分類的分析與預測（至2030年）

上市公司

本報告中提及的部分公司：

• ABBAccentureAdvantechBeckhoff AutomationCapgeminiDeloitteEmersonEndress+HauserFanucHoneywellIBMKeyenceKUKAMicrosoftMitsubishi ElectricOmronRockwell AutomationSAPSchneider ElectricSiemensYaskawaYokogawa

目錄

第1章摘要整理

第2章：引言

• 本章概要及要點
• 歷史背景
• 智慧製造的定義與應用
• 對智慧製造和工業4.0的興趣
• 智慧製造與智慧互聯產品
• 主要組織的定義
• 透過物聯網分析定義智慧製造
• 定義中的通用
• 調查範圍
• 智慧製造技術成熟度模型
• 工業4.0標竿管理與生產力提升
• 製造業就業與機器人密度
• 工業4.0成熟度現狀
• 技術優先事項
• 未來幾年的展望
• 產業研究
• 實施的典型益處
• 例如：WEF燈塔工廠

第3章 市場概覽與競爭格局

• 市場規模及展望概述
• 全球智慧製造市場
• 常見的促進因素和阻礙因素
• 數據的全面概述
• 全球智慧製造市場：按細分市場分類
• 全球智慧製造市場：依技術分類
• 全球智慧製造市場技術佔有率的變化
• 工業4.0技術：成長與成熟
• 綜合前 20 名的智慧製造供應商
• 主要企業簡介：ABB
• 主要企業簡介：西門子
• 主要企業簡介：艾默生
• 主要企業簡介：施耐德電氣
• 主要企業簡介：微軟

第4章：總體趨勢與挑戰

• 章節概要
• 趨勢
• 整體挑戰概述
• 任務

第5章：核心技術棧

• 本章概要及要點
• 智慧製造技術棧的組成部分
• 全球智慧製造核心技術堆疊市場：按細分市場分類
• 優勢和市場規模的定義
• 邊緣硬體：競爭格局
• 全球智慧製造邊緣市場：按地區和產業分類
• 邊緣運算市場細分詳情
• 邊緣：現場測量儀器
• 邊緣：遠端 I/O
• Edge：PLC
• Edge：DCS
• 邊緣：人機介面
• 邊緣：閘道器
• 邊緣：IPC
• 前沿趨勢：概述
• 邊緣趨勢
• 平台/中介軟體定義及市場規模
• 平台/中介軟體：競爭格局
• 全球智慧製造平台/中介軟體市場：按地區和產業分類
• 平台/中介軟體市場的詳細細分
• 平台/中介軟體：訊息仲介
• 平台/中介軟體：設備管理
• 平台/中間件：應用程式管理
• 平台/中介軟體：資料管理
• 平台/中介軟體：工業數據運營
• 平台/中介軟體：人工智慧平台
• 平台/中介軟體：通訊協定轉換工具
• 平台/中介軟體趨勢：概述
• 平台/中介軟體趨勢
• 智慧製造軟體應用：定義與市場規模
• 應用領域：競爭格局
• 全球智慧製造應用市場：按地區和產業分類
• 詳細應用市場細分
• 應用領域：工業自動化軟體
• 應用：MOM/MES
• 應用領域：資產績效與管理
• 應用領域：工廠物流
• 應用趨勢：概述
• 應用趨勢
• 安全定義
• 安全性：關鍵軟體元件
• 安防市場規模及競爭格局
• 全球智慧製造安全市場：按地區和產業分類
• 安全市場的詳細細分領域
• 安全趨勢：概述
• 安全趨勢

第6章 輔助技術

• 章節概要
• 智慧製造的組成：輔助技術
• 全球智慧製造支援技術市場：按細分市場和地區分類
• 技術支援：競爭格局
• 輔助科技市場詳細細分
• 積層製造：定義、應用案例、市場、趨勢
• 固定式機器人：定義、應用案例、市場及趨勢
• 自主移動機器人：定義、應用案例、市場與趨勢
• 機器視覺：定義、應用案例、市場與趨勢
• 擴增實境：定義、應用案例、市場、趨勢
• 人形機器人：供應商列表

第7章 服務

• 本章概要及要點
• 智慧製造專業服務概述
• 從採用者的觀點：是購買還是內部開發？
• 智慧製造專業服務：市場規模
• 案例研究：供應商服務交付方式
• 趨勢與挑戰概述
• 趨勢
• 最終用戶挑戰

第8章 用例

• 章節概要
• KPI最佳化和OEE
• 用例的採納和定義
• 用例

第9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：喬治亞-太平洋公司
• 案例研究4：福特
• 案例研究5：羅氏

第10章：實施情況

• 章節概要
• 終端使用者使用情況調查：概述
• 智慧工廠的現狀：擴充性和安全性
• 智慧工廠範式與技術
• 問題的嚴重性
• 網路安全漏洞範例
• 已採用智慧工廠的主要公司
• 對已採用該系統的主要公司進行分析
• 特斯拉柏林超級工廠
• 實施過程中的挑戰與障礙
• 人工智慧對應用的影響
• 人工智慧實施、要素和成本降低

第11章：調查方法與市場定義

第12章：關於物聯網分析

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