首頁 > 市場調查報告書 > 通訊

IoT

市場調查報告書

商品編碼

1609880

2025-2033 年日本預測維修市場報告（按組件（解決方案、服務）、部署（本地、雲端）、最終用戶（能源和公用事業、運輸、製造、醫療保健等）和區域）

Japan Predictive Maintenance Market Report by Component (Solutions, Services), Deployment (On-premise, Cloud), End User (Energy and Utilities, Transportation, Manufacturing, Healthcare, and Others), and Region 2025-2033

出版日期: 2024年12月05日 | 出版商:

IMARC | 英文 121 Pages | 商品交期: 5-7個工作天內

價格

簡介目錄

2024 年，日本預測性維護市場規模達到 7.747IMARC Group美元。該市場受到幾個重要因素的推動，包括機器對機器（M2M）通訊的廣泛使用、為延長老化工業設備的使用壽命而加大投資，以及更多地採用遠端監控來進行高級檢查。

預測性維護是一種依賴使用狀態監測工具和系統進行即時設備效能監控的方法。這種方法結合了物聯網 (IoT)、人工智慧 (AI) 和整合系統等技術來連接各種資產並共享和分析關鍵資料。它包含預測性維護感測器、工業控制以及企業資產管理 (EAM) 和企業資源規劃 (ERP) 系統等業務軟體等元件。預測性維護的核心功能是利用狀態監控設備來評估和分析資產性能。它收集不同的資料點，包括溫度、振動和電導率，使工程師能夠預測設備或資產故障並規劃主動維修或更換。預測性維護具有降低成本、延長設備使用壽命和提高生產力等優勢。此外，由於其對安全合規性的貢獻以及採取先發制人的糾正措施的能力，其需求正在上升。

日本預測性維護市場趨勢：

在日本的技術實力和對最佳化工業營運的承諾的推動下，日本的預測維護市場正在經歷大幅成長。日本工業界迅速採用利用物聯網 (IoT)、人工智慧 (AI) 和整合系統等先進技術的預測性維護策略。這些技術用於即時監控和分析關鍵設備資料，以便及早發現潛在故障或維護需求。日本廣泛的製造業，包括汽車和電子產業，已經認知到預測性維護在減少停機時間、降低維護成本以及確保機械和生產線高效運作方面的價值。此外，預測性維護與安全合規措施的整合使其成為工業流程的重要組成部分。隨著日本繼續在其工業領域優先考慮創新和效率，預測性維護市場預計將在各個領域進一步擴展和採用。

日本預測維護市場區隔：

組件見解：

解決方案
服務

部署見解：

本地部署
雲

最終使用者見解：

能源和公用事業
運輸
製造業
衛生保健
其他

競爭格局：

市場研究報告也對競爭格局進行了全面分析。報告涵蓋了市場結構、關鍵參與者定位、最佳制勝策略、競爭儀表板和公司評估象限等競爭分析。此外，也提供了所有主要公司的詳細資料。

本報告回答的關鍵問題：

到目前為止，日本預測性維護市場的表現如何，未來幾年將如何表現？
COVID-19 對日本預測性維護市場有何影響？
日本預測性維護市場以組件分類是怎樣的？
日本預測性維護市場在部署上的細分如何？
日本預測性維護市場以最終用戶分類是怎樣的？
日本預測性維護市場價值鏈的各個階段是什麼？
日本預測性維護的關鍵促進因素和挑戰是什麼？
日本預測性維護市場的結構如何？
日本預測性維護市場的競爭程度如何？

本報告回答的關鍵問題：

到目前為止，日本預測性維護市場的表現如何，未來幾年將如何表現？
COVID-19 對日本預測性維護市場有何影響？
日本預測性維護市場以組件分類是怎樣的？
日本預測性維護市場在部署上的細分如何？
日本預測性維護市場以最終用戶分類是怎樣的？
日本預測性維護市場價值鏈的各個階段是什麼？
日本預測性維護的關鍵促進因素和挑戰是什麼？
日本預測性維護市場的結構如何？
日本預測性維護市場的競爭程度如何？

能源和公用事業
- 概述
- 歷史與當前市場趨勢（2019-2024）
- 市場預測（2025-2033）
運輸
- 概述
- 歷史與當前市場趨勢（2019-2024）
- 市場預測（2025-2033）
製造業
- 概述
- 歷史與當前市場趨勢（2019-2024）
- 市場預測（2025-2033）
衛生保健
- 概述
- 歷史與當前市場趨勢（2019-2024）
- 市場預測（2025-2033）
其他
- 歷史與當前市場趨勢（2019-2024）
- 市場預測（2025-2033）

第 9 章：日本預測維修市場 - 競爭格局

概述
市場結構
市場參與者定位
最佳制勝策略
競爭儀表板
公司評估象限

第 10 章：關鍵參與者簡介

Company A

Business Overview
Product Portfolio
Business Strategies
SWOT Analysis
Major News and Events

Company B

Business Overview
Product Portfolio
Business Strategies
SWOT Analysis
Major News and Events

Company C

Business Overview
Product Portfolio
Business Strategies
SWOT Analysis
Major News and Events

Company D

Business Overview
Product Portfolio
Business Strategies
SWOT Analysis
Major News and Events

Company E

Business Overview
Product Portfolio
Business Strategies
SWOT Analysis
Major News and Events

第 11 章：日本預測維護市場 - 產業分析

促進因素、限制因素和機會
- 概述
- 促進要素
- 限制
- 機會
波特五力分析
- 概述
- 買家的議價能力
- 供應商的議價能力
- 競爭程度
- 新進入者的威脅
- 替代品的威脅
價值鏈分析

第 12 章：附錄

簡介目錄

Product Code: SR112024A18661

Japan predictive maintenance market size reached USD 774.7 Million in 2024. Looking forward, IMARC Group expects the market to reach USD 7,400.7 Million by 2033, exhibiting a growth rate (CAGR) of 28.5% during 2025-2033. The market is being propelled by several significant factors, including the expanding use of machine-to-machine (M2M) communication, greater investments in prolonging the operational lifespan of aging industrial equipment, and the increased incorporation of remote monitoring for conducting advanced inspections.

Predictive maintenance is a methodology that relies on the use of condition-monitoring tools and systems for real-time equipment performance monitoring. This approach incorporates technologies like the Internet of Things (IoT), artificial intelligence (AI), and integrated systems to connect various assets and share and analyze critical data. It encompasses components such as predictive maintenance sensors, industrial controls, and business software like Enterprise Asset Management (EAM) and Enterprise Resource Planning (ERP) systems. The core function of predictive maintenance is to employ condition monitoring equipment to assess and analyze asset performance. It gathers diverse data points, including temperature, vibrations, and conductivity, enabling engineers to anticipate equipment or asset failures and plan for proactive repairs or replacements. Predictive maintenance offers advantages such as cost reduction, extended equipment lifespan, and enhanced productivity. Furthermore, its demand is on the rise due to its contribution to safety compliance and the ability to take preemptive corrective actions.

Japan Predictive Maintenance Market Trends:

The predictive maintenance market in Japan is experiencing substantial growth, driven by the country's technological prowess and its commitment to optimizing industrial operations. Japanese industries have been quick to adopt predictive maintenance strategies that leverage advanced technologies such as the Internet of Things (IoT), artificial intelligence (AI), and integrated systems. These technologies are used to monitor and analyze critical equipment data in real-time, allowing for the early detection of potential failures or maintenance needs. Japan's extensive manufacturing sector, including automotive and electronics industries, has recognized the value of predictive maintenance in reducing downtime, lowering maintenance costs, and ensuring the efficient operation of machinery and production lines. Additionally, the integration of predictive maintenance with safety compliance measures has made it a crucial component of industrial processes. As Japan continues to prioritize innovation and efficiency in its industrial landscape, the predictive maintenance market is expected to witness further expansion and adoption across various sectors.

Japan Predictive Maintenance Market Segmentation:

Component Insights:

Solutions
Services

Deployment Insights:

On-premise
Cloud

End User Insights:

Energy and Utilities
Transportation
Manufacturing
Healthcare
Others

Competitive Landscape:

The market research report has also provided a comprehensive analysis of the competitive landscape. Competitive analysis such as market structure, key player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided.

Key Questions Answered in This Report:

How has the Japan predictive maintenance market performed so far and how will it perform in the coming years?
What has been the impact of COVID-19 on the Japan predictive maintenance market?
What is the breakup of the Japan predictive maintenance market on the basis of component?
What is the breakup of the Japan predictive maintenance market on the basis of deployment?
What is the breakup of the Japan predictive maintenance market on the basis of end user?
What are the various stages in the value chain of the Japan predictive maintenance market?
What are the key driving factors and challenges in the Japan predictive maintenance?
What is the structure of the Japan predictive maintenance market and who are the key players?
What is the degree of competition in the Japan predictive maintenance market?

1 Preface

2 Scope and Methodology

2.1 Objectives of the Study
2.2 Stakeholders
2.3 Data Sources
- 2.3.1 Primary Sources
- 2.3.2 Secondary Sources
2.4 Market Estimation
- 2.4.1 Bottom-Up Approach
- 2.4.2 Top-Down Approach
2.5 Forecasting Methodology

3 Executive Summary

4 Japan Predictive Maintenance Market - Introduction

4.1 Overview
4.2 Market Dynamics
4.3 Industry Trends
4.4 Competitive Intelligence

5 Japan Predictive Maintenance Market Landscape

5.1 Historical and Current Market Trends (2019-2024)
5.2 Market Forecast (2025-2033)

6 Japan Predictive Maintenance Market - Breakup by Component

6.1 Solutions
- 6.1.1 Overview
- 6.1.2 Historical and Current Market Trends (2019-2024)
- 6.1.3 Market Forecast (2025-2033)
6.2 Services
- 6.2.1 Overview
- 6.2.2 Historical and Current Market Trends (2019-2024)
- 6.2.3 Market Forecast (2025-2033)

7 Japan Predictive Maintenance Market - Breakup by Deployment

7.1 On-premise
- 7.1.1 Overview
- 7.1.2 Historical and Current Market Trends (2019-2024)
- 7.1.3 Market Forecast (2025-2033)
7.2 Cloud
- 7.2.1 Overview
- 7.2.2 Historical and Current Market Trends (2019-2024)
- 7.2.3 Market Forecast (2025-2033)

8 Japan Predictive Maintenance Market - Breakup by End User

8.1 Energy and Utilities
- 8.1.1 Overview
- 8.1.2 Historical and Current Market Trends (2019-2024)
- 8.1.3 Market Forecast (2025-2033)
8.2 Transportation
- 8.2.1 Overview
- 8.2.2 Historical and Current Market Trends (2019-2024)
- 8.2.3 Market Forecast (2025-2033)
8.3 Manufacturing
- 8.3.1 Overview
- 8.3.2 Historical and Current Market Trends (2019-2024)
- 8.3.3 Market Forecast (2025-2033)
8.4 Healthcare
- 8.4.1 Overview
- 8.4.2 Historical and Current Market Trends (2019-2024)
- 8.4.3 Market Forecast (2025-2033)
8.5 Others
- 8.5.1 Historical and Current Market Trends (2019-2024)
- 8.5.2 Market Forecast (2025-2033)

9 Japan Predictive Maintenance Market - Competitive Landscape

9.1 Overview
9.2 Market Structure
9.3 Market Player Positioning
9.4 Top Winning Strategies
9.5 Competitive Dashboard
9.6 Company Evaluation Quadrant

10 Profiles of Key Players

10.1 Company A
- 10.1.1 Business Overview
- 10.1.2 Product Portfolio
- 10.1.3 Business Strategies
- 10.1.4 SWOT Analysis
- 10.1.5 Major News and Events
10.2 Company B
- 10.2.1 Business Overview
- 10.2.2 Product Portfolio
- 10.2.3 Business Strategies
- 10.2.4 SWOT Analysis
- 10.2.5 Major News and Events
10.3 Company C
- 10.3.1 Business Overview
- 10.3.2 Product Portfolio
- 10.3.3 Business Strategies
- 10.3.4 SWOT Analysis
- 10.3.5 Major News and Events
10.4 Company D
- 10.4.1 Business Overview
- 10.4.2 Product Portfolio
- 10.4.3 Business Strategies
- 10.4.4 SWOT Analysis
- 10.4.5 Major News and Events
10.5 Company E
- 10.5.1 Business Overview
- 10.5.2 Product Portfolio
- 10.5.3 Business Strategies
- 10.5.4 SWOT Analysis
- 10.5.5 Major News and Events

11 Japan Predictive Maintenance Market - Industry Analysis

11.1 Drivers, Restraints, and Opportunities
- 11.1.1 Overview
- 11.1.2 Drivers
- 11.1.3 Restraints
- 11.1.4 Opportunities
11.2 Porters Five Forces Analysis
- 11.2.1 Overview
- 11.2.2 Bargaining Power of Buyers
- 11.2.3 Bargaining Power of Suppliers
- 11.2.4 Degree of Competition
- 11.2.5 Threat of New Entrants
- 11.2.6 Threat of Substitutes
11.3 Value Chain Analysis