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市場調查報告書

預知保全 (PM)的全球市場:2019年∼2024年

Predictive Maintenance Report 2019-2024

出版商 IoT Analytics GmbH 商品編碼 481634
出版日期 內容資訊 英文 136 Pages
商品交期: 最快1-2個工作天內
價格
預知保全 (PM)的全球市場:2019年∼2024年 Predictive Maintenance Report 2019-2024
出版日期: 2019年06月21日內容資訊: 英文 136 Pages
簡介

本報告提供全球預知保全 (PM) 市場相關調查分析,主要13個產業的發展,目前引進情形,主要11個趨勢,主要9個企業,各地區市場,使用案例詳細內容等系統性資訊。

摘要整理

第1章 預知保全 (PM)的簡介

  • 定義、歧義性消除
  • IoT I4.0所扮演的角色

第2章 技術

  • 應用領域
  • 技術堆疊
  • 感測技術
  • 分析

第3章 市場規模、預測

  • 綜合市場、促進因素
  • 市場:各技術
  • 市場:各產業
  • 市場:各地區

第4章 競爭情形

  • 概要
  • 企業簡介
  • M&A活動記錄

第5章 經營模式、案例研究

  • 引進的優點
  • 軟體供應商預測
  • OEM預測
  • 業者/工作現場預測
  • 案例研究

第6章 趨勢、課題

  • 主要趨勢
  • 課題、障礙

第7章 調查手法、定義

  • 關於IoT Analytics

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目錄

Comprehensive 136-page industry report detailing the $23.5B Predictive Maintenance market including:

  • Market forecast 2019 to 2024
  • Market size by technology, industry and region
  • Database of 110+ real world predictive maintenance projects
  • Database of 180+ predictive maintenance providers
  • 8 Market drivers & characteristics
  • 9 Company profiles, detailing leading vendors
  • 9 Case studies of recent deployments
  • 11 Industry trends
  • 10 Challenges/barriers to adoption
  • Business Model analysis
  • And More

This Predictive Maintenance report details the fastest growing use case for the Internet of Things.

FIND OUT:

  • How the market is developing in 13 key industries (Automotive & Transport, Buildings, Chemicals, Consumer Products, Energy, Healthcare, Machinery, Metals & Mining, Oil&Gas, Discrete Other, Pulp & Paper, Water & Wastewater, and Other)
  • How Predictive Maintenance solutions are being implemented today (9 detailed use cases and list of 110+ real world projects)
  • What the 11 current main trends are
  • How the 9 leading Predictive Maintenance companies compare and how they fit into the landscape of 180+ Predictive Maintenance technology vendors
  • Regional Market Split for 2018 to 2024
  • How OEMs monetize Predictive Maintenance and what the corresponding services look like

QUESTIONS ANSWERED IN THIS REPORT:

  • What is Predictive Maintenance? ( i.e., a Predictive Maintenance definition)
  • Which technologies are used for Predictive Maintenance (including a sensing and analytics technology deep-dive)?
  • What are the examples of Predictive Maintenance vendors and Predictive Maintenance case studies?
  • Which new business models does Predictive Maintenance allow?
  • How does the Predictive Maintenance market look like (i.e., overview by regions, technologies, industries)?
  • Which benefits are companies seeing from their Predictive Maintenance investments, and which KPIs are they using to measure them?
  • What are the market drivers, trends & challenges in Predictive Maintenance space?

AT A GLANCE:

Predictive Maintenance continues to be a hot topic for the Internet of Things (IoT) , helped by the parallel advances in many fields; namely sensing technologies, connectivity, IoT architectures, data science & artificial intelligence. The global Predictive Maintenance market reached $3.3B in 2018 and is expected to grow at a CAGR of 39% to become a $23.5B market by 2024.

This report outlines the Predictive Maintenance market by segment. It examines current and expected spending for Predictive Maintenance solutions in greater detail across 13 vertical-industry segments (Automotive & Transport, Buildings, Chemicals, Consumer Products, Energy, Healthcare, Machinery, Metals & Mining, Oil&Gas, Discrete Other, Pulp & Paper, Water & Wastewater, Other ), 7 technology areas (Hardware, Connectivity, Platform, Storage, Analytics, Applications, and System Integration & Services) as well as a regional breakdown with country level deep dives for 5 regions (APAC, Europe, MEA, North America, and South America).

To better understand the market players 9 of the top Predictive Maintenance providers are profiled and a Database of 180+ Predictive Maintenance companies in the field is included. The study also describes the top 11 industry trends and 10 main challenges affecting Predictive Maintenance. The report comes with an additional Database of 110+ detailed Predictive Maintenance projects and provides a deep-dive into 9 specific case study examples of Predictive Maintenance currently in the market.

DEFINITION OF PREDICTIVE MAINTENANCE

For this report the following slide presents the definition of Predictive Maintenance used in the analysis.

SELECTED COMPANIES FROM THE PREDICTIVE MAINTENANCE REPORT

Accenture, Bosch, C3, Cassantec, Cisco, Dell, E.ON, General Electric, Falkonry, Heidelberger Druck, Helium, Huawei, Hitachi, IBM, Keysight Technologies, Konux, Microsoft, National Instruments, OSIsoft, Pronosis, PTC, Rockwell Automation, SAP, SAS, Schneider Electric, Senseye, Siemens, SKF, Software AG, SparkCognition, Splunk, Tachyus, thyssenkrupp, Uptake +160 more.

Table of Contents

Executive Summary

  • What has changed since the last report

1. Introduction to Predictive Maintenance

  • 1.1. Definition & Disambiguation
  • 1.2. Role in IoT&I4.0

2. Technology

  • 2.1. Application areas
  • 2.2. Technology stack
  • 2.3. Deep-dive: Sensing techniques
  • 2.4. Deep-dive: Analytics

3. Market Size & Outlook

  • 3.1. Total Market & Overall Drivers
  • 3.2. Market by Technology
  • 3.3. Market by Industry
  • 3.4. Market by Region

4. Competitive Landscape

  • 4.1. Overview
  • 4.2. Company Profiles
  • 4.3. M&A Activity Log

5. Business Models & Case Studies

  • 5.1. Benefits of PdM implementations
  • 5.2. Software vendor perspective
  • 5.3. OEM perspective
  • 5.4. Operator/Shopfloor perspective
  • 5.5. Case studies

6. Trends & Challenges

  • 6.1. Major trends
  • 6.2. Challenges & Barriers

7. Methodology & Definitions

  • About IoT Analytics