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市場調查報告書

軟體定義型車輛的預想、預防的整備功能

Prognostics and Preventive Maintenance for Software-Defined Vehicles

出版商 ABI Research 商品編碼 369107
出版日期 內容資訊 英文 22 Pages, 4 Charts, 12 Figures
商品交期: 最快1-2個工作天內
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軟體定義型車輛的預想、預防的整備功能 Prognostics and Preventive Maintenance for Software-Defined Vehicles
出版日期: 2016年09月08日 內容資訊: 英文 22 Pages, 4 Charts, 12 Figures
簡介

所謂預想的功能,是即時地觀察汽車零件的性能,(從使用年數) 測量預期的性能和實際性能的差異後,預測各零件的耐久年數的功能。汽車零件產業正將產業的主力,從(應對必要的) 單純的零件製造、替換,轉移到使用預知功能的耐用性資料的收集,和零件替換預測、傳達。

本報告提供全球汽車 (小客車、商用車) 的預想、預防的整備功能的市場相關分析,預想的整備功能概要和優點、缺點,汽車產業/汽車零件產業的關聯性和影響力,今後的市場趨勢預測,相關企業簡介、產業策略等的相關調查。

第1章 概要

  • 車輛正常性解決方案的演進
  • 擴增實境 (AR)的潛在成長空間
  • 故障的徵兆
  • 資料的收集
  • 持續性整備體制

第2章 PHM (預知性的車輛狀態管理)的優點與課題

  • 優點
  • 課題

第3章 預知功能的供應鏈

  • 各產業公司的策略
  • 賺取收入的可能性
  • 在小客車/商用車的普及預測比較
  • 飛機、軍用車輛的關聯性
  • 航空、國防工業中預知功能的企業

第4章 預知功能的專業企業

  • MathWorks
  • DataRPM
  • Covisint

分析對象企業

  • Amazon
  • AR Technologies
  • Azure
  • BMW Group
  • Boeing
  • Bosch
  • BT Group
  • CA Inc.
  • Caterpillar
  • Compuware
  • Covisint Corporation
  • Cummins
  • Delphi Corporation
  • EMC
  • Equinox
  • Facebook
  • Firmware
  • Freightliner Corporation
  • Google
  • Hyundai
  • Lockheed Martin
  • Microsoft Corporation
  • 三菱自動車
  • Morgan Stanley
  • Moving technologies
  • NASA
  • Netflix
  • Omnitracs Inc
  • OnStar
  • Oracle Corp
  • Predii
  • PT
  • Rolls Royce
  • Sentinel Group
  • STS
  • Teleca
  • Telogis
  • TTM
  • Uber
  • United Technologies Corporation
  • USA Technologies
  • Verizon
目錄
Product Code: AN-2267

Advances in telematics, ECUs and numerous ADAS features are facilitating growth in vehicle health management systems including prognostics and repair management. These enable over the air (OTA) lifecycle management, customer satisfaction, and loyalty as well as reduced costs for the OEMS. Prognostics monitor and predict anticipated performance of a component in real time by estimating the degree of deviation of a component from its expected norm.

The automotive and commercial vehicle industries are moving from merely corrective, manual repairs to predictive and preventable occurrences. The transformation also presents an opportunity for OEMs to harvest valuable data from the cars and drivers. The value will increase as vehicle diagnostics move from tires and engines into a full spectrum of connected components and extend to a vehicle in motion and processed in real time.

Table of Contents

1. OVERVIEW

  • 1.1. Evolving Vehicle Health Solutions
  • 1.2. Augmented Reality Potential Grows
  • 1.3. Failure Precursors
  • 1.4. Data Correlation
  • 1.5. The Maintenance Continuum

2. PHM BENEFITS AND CHALLENGES

  • 2.1. Benefits
  • 2.2. Challenges

3. PROGNOSTICS SUPPLY CHAIN

  • 3.1. Industry Strategies
  • 3.2. Profit Generation Potential
  • 3.3. Car Versus Commercial Vehicle Adoption
  • 3.4. Aviation and Military Linkage
  • 3.5. Prognostics Companies in Aero and/or Defense

4. PROGNOSTICS SPECIALISTS

  • 4.1. MathWorks
  • 4.2. DataRPM
  • 4.3. Covisint

Companies Mentioned

  • Amazon
  • AR Technologies
  • Azure
  • BMW Group
  • Boeing
  • Bosch
  • BT Group
  • CA Inc.
  • Caterpillar
  • Compuware
  • Covisint Corporation
  • Cummins
  • Delphi Corporation
  • EMC
  • Equinox
  • Facebook
  • Firmware
  • Freightliner Corporation
  • Google
  • Hyundai
  • Lockheed Martin
  • Microsoft Corporation
  • Mitsubishi Corp
  • Morgan Stanley
  • Moving technologies
  • NASA
  • Netflix
  • Omnitracs Inc
  • OnStar
  • Oracle Corp
  • Predii
  • PT
  • Rolls Royce
  • Sentinel Group
  • STS
  • Teleca
  • Telogis
  • TTM
  • Uber
  • United Technologies Corporation
  • USA Technologies
  • Verizon
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