市場調查報告書

產業用途的AI

AI in Industrial Applications

出版商 ABI Research 商品編碼 893716
出版日期 內容資訊 英文 27 Pages
商品交期: 最快1-2個工作天內
價格
如有價格方面的疑問請按下「詢問」鍵來信查詢
Back to Top
產業用途的AI AI in Industrial Applications
出版日期: 2019年07月25日內容資訊: 英文 27 Pages
簡介

本報告提供工業製造的各AI開發企業所扮演的角色和產品的相關調查,工業生產的AI概要,主要趨勢,最佳業務實踐,市場預測,主要供應商的簡介,及主要建議等資訊彙整。

第1章 摘要整理

第2章 人工智能 (AI)的定義

第3章 工業生產的AI概要

  • 利用案例
  • AI的定位

第4章 主要趨勢

  • 具恰當的結構要素很重要
  • 無教師學習是實際上的工業製造中的ML技術
  • 新的AI技術開始出現
  • 市場引進率的變動

第5章 工業製造中AI展開的最佳業務實踐

第6章 市場預測

第7章 主要供應商的簡介

  • 雲端服務供應商
  • 智慧工廠手工業環平台供應商
  • 純網路營運產業用AI平台、服務供應商
  • 產業用邊緣AI閘道器、伺服器供應商
  • 晶片組供應商
  • 系統廠商
  • 連接性供應商

第8章 主要建議、結論

  • AI的整體觀點
  • AI開發企業整體贊同是必須的
  • 公司內部專家或第三方的系統廠商

報告中所談到的企業

  • ABB Ltd
  • Ability Inc.
  • ADLINK
  • Alibaba Group
  • Amazon
  • Azure
  • Baidu, Inc.
  • Bosch
  • C3
  • EMC Corporation
  • Foxconn
  • Google
  • Hitachi Ltd
  • HPE
  • Huawei
  • IBM Corp
  • Intel Corporation
  • Microsoft Corporation
  • Movidius
  • Myriad Group
  • NN, Inc.
  • NVIDIA
  • Oracle Corporation
  • Qualcomm Inc
  • SAP
  • Sight Machine
  • Tencent
  • Xilinx, Inc.
目錄
Product Code: AN-5119

For the longest time, Artificial Intelligence (AI) has been touted as a powerful technology that will revolutionize the industrial manufacturing space. The sentiment has its validity, but there is no shortcut to AI. Firstly, AI in industrial manufacturing is an ensemble of various use cases at various phases of manufacturing, such as generative design in product development, production forecasting in inventory management, machine vision, defect inspection, production optimization and predictive maintenance on production phase. Secondly, the right data and personnel are needed for AI implementation. Many existing equipment and tools on the factory floor remains unconnected. In addition, manufacturers are facing enormous competition in building and training in-house data science team for AI implementation.

Once the right foundations are in place, including data architecture, AI frameworks, AI engines and on-premise hardware, manufacturers can start to leverage the capabilities that AI can offer. At the moment, most AI solutions are able to collect data and perform unsupervised machine learning to generate insights and recommendations, with supervision from AI experts. The rise of automated machine learning will free AI experts from the more mundane AI optimization tasks and allow them to explore new use cases for AI. However, not all AI models need to be complex. There are many low-hanging fruits that simple AI models are more than capable to address in today's factory.

To provide a clear picture on commercial AI applications, this report explores the roles and offering from different implementors of AI in industrial manufacturing, including cloud service providers, industrial cloud platform vendors, pure-play AI startups, system integrators, chipset and industrial server manufacturers and connectivity service providers. Manufacturers who want to implement AI will definitely need to engage with these companies and partner with them in their AI journey.

Table of Contents

1. EXECUTIVE SUMMARY

2. DEFINITION OF ARTIFICIAL INTELLIGENCE

  • 2.1. Classes of Machine Learning

3. OVERVIEW OF AI IN INDUSTRIAL MANUFACTURING

  • 3.1. Use Case-Centric
  • 3.2. Location of AI

4. KEY TRENDS

  • 4.1. Having the Right Building Blocks Matters
  • 4.2. Unsupervised Learning Is the De-Facto ML Technique in Industrial Manufacturing
  • 4.3. New AI Techniques Are on the Horizon
  • 4.4. Variation in Market Adoption Rate

5. BEST PRACTICES OF AI DEPLOYMENT IN INDUSTRIAL MANUFACTURING

6. MARKET FORECASTS

7. PROFILE OF KEY VENDORS

  • 7.1. Cloud Service Providers
  • 7.2. Smart Manufacturing Platform Vendors
  • 7.3. Pure-Play Industrial AI Platform and Service Providers
  • 7.4. Industrial Edge AI Gateway and Server Vendors
  • 7.5. Chipset Vendors
  • 7.6. System Integrators
  • 7.7. Connectivity Vendor

8. KEY RECOMMENDATIONS AND CONCLUSIONS

  • 8.1. Holistic View of AI
  • 8.2. AI Deployment Requires Company-Wide Buy-Ins
  • 8.3. In-House Expertise or Third-Party System Integrators

Companies Mentioned

  • ABB Ltd
  • Ability Inc.
  • ADLINK
  • Alibaba Group
  • Amazon
  • Azure
  • Baidu, Inc.
  • Bosch
  • C3
  • EMC Corporation
  • Foxconn
  • Google
  • Hitachi Ltd
  • HPE
  • Huawei
  • IBM Corp
  • Intel Corporation
  • Microsoft Corporation
  • Movidius
  • Myriad Group
  • NN, Inc.
  • NVIDIA
  • Oracle Corporation
  • Qualcomm Inc
  • SAP
  • Sight Machine
  • Tencent
  • Xilinx, Inc.
Back to Top