The Industrial Internet




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Towards the 4th industrial revolution

This report describes the phenomenon of the Industrial Internet.
It analyses the impacts on the integration of IoT technologies into industrial assets (the 'smart factory'), as well as into end products.

It also provides insights regarding innovative business models and illustrative case studies from various verticals.

It describes the main drivers and barriers for the take-off of the Industrial Internet market.

Table of Content

1. Executive Summary

2. Methodology & definitions
2.1. General methodology of IDATE's reports
2.2. Definitions and scope

3. Infrastructure: towards the smart factory or networked production
3.1. Concept description
3.1.1. Concept
3.1.2. Context, adoption and future trends
3.2. Existing national and international initiatives
3.2.1. Different types of initiatives supporting smart manufacturing
3.2.2. European initiatives
3.2.3. Other national initiatives
3.2.4. Industrial Internet Consortium
3.3. Key providers
3.4. Focus on selected implementations
3.4.1. Aeronautics
3.4.2. Automotive
3.4.3. Energy
3.4.4. Transportation
3.5. Impacts
3.5.1. Transformation of the manufacturing ecosystem
3.5.2. Risks and barriers

4. Products and services: innovative end-products and related services
4.1. A key enabler of servicisation strategy
4.1.1. Key objectives
4.1.2. Commercial approach
4.2. Adoption
4.3. Focus on selected implementations
4.3.1. Aviation
4.3.2. Automotive
4.3.3. Heavy equipment
4.4. Impacts
4.4.1. Corporate vertical transformation
4.4.2. New businesses for industrials

5. The customer relationship
5.1. Impacts due to servicisation
5.2. Innovative pricing models
5.3. Focus on selected implementations
5.3.1. Transportation
5.3.2. Healthcare

6. Market analysis
6.1. Value chain
6.1.1. Sensor providers
6.1.2. Industrials
6.1.3. Telcos
6.1.4. Platform providers
6.1.5. Service providers and IT players
6.2. Organisational change
6.3. Data potential and related monetisation issue
6.3.1. Data owned by business clients
6.3.2. Data owned by consumers clients
6.4. Drivers and barriers
6.4.1. Drivers
6.4.2. Barriers

Table 1: Main providers of smart factory solutions
Table 2: Main initiatives around the smart factory
Table 3: Main initiatives around connected end-products
Table 4: Main initiatives around innovative pricing schemes
Table 5: Main initiatives of Medtronic in connected health market

Figure 1: The IDATE framework for digital transformation
Figure 2: Technologies of the third wave of digital transformation
Figure 3: Smart factory use case
Figure 4: Evolution of the manufacturing domain
Figure 5: Smart manufacturing research roadmap
Figure 6: New Balance shoes with 3D-printed midsoles presented at CES 2016
Figure 7: The Siemens automated factory, in Amberg, Germany
Figure 8: The Siemens vision of smart factory convergence
Figure 9: ABB control rooms
Figure 10: Augmented Reality deployment at Bechtle
Figure 11: Baxter uncaged robot
Figure 12: Uncaged robots deployed in a ceramic factory
Figure 13: HTC Vive virtual reality headset
Figure 14: Optis HIM VR solution used to validate assembly movements in aerospace industry
Figure 15: Track and Trace IIC Testbed
Figure 16: Use of big-data analytics in manufacturing
Figure 17: Intel production line data analytics set-up
Figure 18: Overview of European initiatives on digitising industry
Figure 19: Dassault Systèmes 3DExperience platform
Figure 20: Siemens digitalisation
Figure 21: Siemens Digital Factory portfolio, compared with Industry 4.0 plans
Figure 22: Kuka divisions and offerings
Figure 23: Kuka future vision integrating moving and fixed robots in a uniform factory platform
Figure 24: National Instruments vision as a provider of data analytics for the Internet of Things
Figure 25: Typical aircraft assembly environment
Figure 26: Smart glasses usage within factory
Figure 27: Use of uncaged robot at Audi
Figure 28: Competence islands at Audi
Figure 29: A centre to pilot the production and consumption of energy
Figure 30: Monitoring production by layers
Figure 31: Industrial Internet strategy at SNCF
Figure 32: SMILE distribution of value added, by manufacturing activity
Figure 33: Survey by Citigroup linking smart factory development and reshoring
Figure 34: Impact of automation on the job market
Figure 35: Interest of servicisation in margins
Figure 36: Survey answers to “What functionality is most valuable?”
Figure 37: Direct operating costs of an airline company
Figure 38: Rolls-Royce engines equipped with sensors
Figure 39: The Industrial Internet applied to aviation industry
Figure 40: The Predix platform
Figure 41: Value proposition evolution, GE Aviation
Figure 42: Connected car service roadmap
Figure 43: Key services in the automotive sector for major stakeholders
Figure 44: Willingness to pay for connected services in a subscription-based model
Figure 45: 17-inch Touch screen features
Figure 46: Supercharger network plan in the US and in Europe for 2016
Figure 47: Autopilot feature setting, by Tesla
Figure 48: Ford SYNC AppLink applications
Figure 49: GoRide experience
Figure 50: Use of drones at Caterpillar
Figure 51: Driverless truck, by Komatsu
Figure 52: Roadmap of different services offered by industrials
Figure 53: Evolution of Michelin's commercial offering
Figure 54: EFFIFUEL solution principle
Figure 55: Continuous Glucose Monitoring (CGM) systems
Figure 56: 2014 ranking of MEMS players
Figure 57: TE connectivity positioning in sensors
Figure 58: Key positioning differentiation among carriers in the Industrial Internet market
Figure 59: Connected Industry Platform showcased at the CEBIT 2015
Figure 60: Taleris home page
Figure 61: Michelin Solutions architecture
Figure 62: Data resale to service company
Figure 63: Data resale to a third-party service company
Figure 64: INDUSTRIE 4.0 to generate significant productivity gains in Germany
Figure 65: The power of the 1% by GE
Figure 66: Industrial Internet potential GDP share
Figure 67: European industrials to invest €140 billion annually in Industrial Internet applications, to 2020
Figure 68: Industrie 4.0, smart factory pipeline
Figure 69: Industries that named security as a top challenge in the implementation of big data