デフォルト表紙
市場調査レポート
商品コード
1609880

日本の予知保全市場レポート:コンポーネント、展開、エンドユーザー、地域別、2025年~2033年

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
発行
IMARC
ページ情報
英文 121 Pages
納期
5~7営業日
カスタマイズ可能
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=153.81円
日本の予知保全市場レポート:コンポーネント、展開、エンドユーザー、地域別、2025年~2033年
出版日: 2024年12月05日
発行: IMARC
ページ情報: 英文 121 Pages
納期: 5~7営業日
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  • 概要
  • 目次
概要

日本の予知保全市場の市場規模は2024年に7億7,470万米ドルに達しました。今後、IMARC Groupは、市場は2033年までに74億70万米ドルに達し、2025~2033年の成長率(CAGR)は28.5%になると予測しています。この市場は、マシンツーマシン(M2M)通信の利用拡大、老朽化した産業機器の稼動寿命延長への投資拡大、高度な検査を実施するための遠隔監視の導入拡大など、いくつかの重要な要因によって推進されています。

本レポートで扱う主な質問

  • 日本の予知保全市場のこれまでの業績と、今後数年間の業績は?
  • 日本の予知保全市場にCOVID-19が与えた影響は?
  • 日本の予知保全市場のコンポーネント別の内訳は?
  • 日本の予知保全市場の展開別の内訳は?
  • 日本の予知保全市場のエンドユーザー別の内訳は?
  • 日本の予知保全市場のバリューチェーンにはどのような段階がありますか?
  • 日本の予知保全における主な促進要因と課題は?
  • 日本の予知保全市場の構造と主要プレーヤーは?
  • 日本の予知保全市場における競合の程度は?

目次

第1章 序文

第2章 調査範囲と調査手法

  • 調査の目的
  • ステークホルダー
  • データソース
  • 市場推定
  • 調査手法

第3章 エグゼクティブサマリー

第4章 日本の予知保全市場:イントロダクション

  • 概要
  • 市場力学
  • 業界動向
  • 競合情報

第5章 日本の予知保全市場情勢

  • 過去および現在の市場動向(2019年~2024年)
  • 市場予測(2025-2033)

第6章 日本の予知保全市場:コンポーネント別の内訳

  • ソリューション
  • サービス

第7章 日本の予知保全市場:展開別の内訳

  • オンプレミス
  • クラウド

第8章 日本の予知保全市場:エンドユーザー別の内訳

  • エネルギーと公共事業
  • 輸送機関
  • 製造
  • ヘルスケア
  • その他

第9章 日本の予知保全市場:競合情勢

  • 概要
  • 市場構造
  • 市場プレーヤーのポジショニング
  • 主要成功戦略
  • 競合ダッシュボード
  • 企業評価象限

第10章 主要企業のプロファイル

第11章 日本の予知保全市場:業界分析

  • 促進要因・抑制要因・機会
  • ポーターのファイブフォース分析
  • バリューチェーン分析

第12章 付録

目次
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?

Table of Contents

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

12 Appendix