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市場調查報告書

工業雲端

The Industrial Cloud

出版商 ABI Research 商品編碼 664116
出版日期 內容資訊 英文 32 Pages, 3 Tables, 5 Charts, 7 Figures
商品交期: 最快1-2個工作天內
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工業雲端 The Industrial Cloud
出版日期: 2018年07月17日內容資訊: 英文 32 Pages, 3 Tables, 5 Charts, 7 Figures
簡介

本報告提供影響未來的IIoT (工業IoT) 策略決策的促進因素,阻礙因素,及轉換點相關考察,各雲端服務模式和變化,主要企業與圍繞其地位的動向,及價值鏈等的分析。

第1章 工業雲端市場檢討

第2章 建議

第3章 工業雲端的簡介

  • IoT情報:從端點到雲端
  • 工業自動化及控制子系統
  • 工業雲端服務模式
  • 分析價值鏈
  • 工業雲端的決策組成架構

第4章 主要趨勢、觀察

  • 促進因素
  • 阻礙因素

第5章 工業雲端的預測

  • 工業IoT的連接性
  • 工業雲端服務模式
  • 工業、工廠手工業環調查結果

第6章 工業雲端供應商的策略評估

  • ABB
  • AWS
  • Bosch
  • Dell
  • 富士通
  • GE
  • 日立
  • IBM
  • Microsoft
  • PTC
  • Rockwell Automation
  • SAP
  • Siemens

本調查提及企業

  • SAP
  • Azure
  • IBM Corp
  • Microsoft Corporation
  • PTC
  • ABB Ltd
  • 富士通
  • OT
  • Bosch
  • Amazon
  • 日立
  • Ability Inc.
  • ThingWorx
  • Solar
  • Google
  • UCP, Inc.
  • Remote Technologies Inc
  • PT
目錄
Product Code: AN-5014

Today, most IoT analytics operations occur in the cloud. This is partly driven by supplier offerings and partly because the cloud offers a centralized location for large amounts of affordable storage and computing power. There are, however, a growing number of instances in which it makes more sense to perform analytics closer to the “thing” or activity that is generating or collecting data - equipment deployed at customer sites (generators, trains, wind turbines). This is particularly true in industrial and manufacturing environments, which are familiar with the challenges of managing massive amounts of generated data (typically by parking it in a data lake or the like) and general digital product development (e.g., CAD models), but lag when it comes to the virtualization of business-critical infrastructure. Advances in intelligent process manufacturing, factory automation, and AI/ML model development benefit from edge analytics implementations yet are nothing but islands of automation without the industrial cloud.

The industrial cloud covers everything from the factory floor to the industrial campus, and it is unifying the supply chain as companies employ a combination of digital business, product, manufacturing, asset, and logistics planning to streamline operations across both internal and external processes; make it easier to optimize asset and process allocations by modelling the physical world; and use data and subsequent insights to enable new services; and improve control over environmental, health, and safety issues.

This report provides foresight on the drivers, inhibitors, and inflection points fueling future IIoT strategy decisions. It examines the different cloud service models and how they are changing; identifies the key players and how they are jockeying for position, and unpacks the value chain. It also includes a snapshot of ABI Research survey data with a special lens on industrial and manufacturing.

Table of Contents

1. INDUSTRIAL CLOUD MARKET REVIEW

  • 1.1. Executive Summary

2. RECOMMENDATIONS

3. INTRODUCTION TO INDUSTRIAL CLOUD

  • 3.1. IoT Intelligence: From Endpoint to Cloud
  • 3.2. Industrial Automation and Control Subsystems
  • 3.3. Industrial Cloud Services Models
  • 3.4. The Analytics Value Chain
  • 3.5. Industrial Cloud Decision Framework

4. KEY TRENDS AND OBSERVATIONS

  • 4.1. Drivers
  • 4.2. Inhibitors

5. INDUSTRIAL CLOUD FORECASTS

  • 5.1. Industrial IoT Connectivity
  • 5.2. Industrial Cloud Service Models
  • 5.3. Industrial and Manufacturing Survey Results

6. INDUSTRIAL CLOUD SUPPLIER STRATEGY ASSESSMENTS

  • 6.1. ABB
  • 6.2. AWS
  • 6.3. Bosch
  • 6.4. Dell
  • 6.5. Fujitsu
  • 6.6. GE
  • 6.7. Hitachi
  • 6.8. IBM
  • 6.9. Microsoft
  • 6.10. PTC
  • 6.11. Rockwell Automation
  • 6.12. SAP
  • 6.13. Siemens

Companies Mentioned:

  • SAP
  • Azure
  • IBM Corp
  • Microsoft Corporation
  • PTC
  • ABB Ltd
  • Fujitsu Limited
  • OT
  • Bosch
  • Amazon
  • Hitachi Ltd
  • Ability Inc.
  • ThingWorx
  • Solar
  • Google
  • UCP, Inc.
  • Remote Technologies Inc
  • PT