Smart Manufacturing Platforms: Best Practice for Winning in the Next Industrial Revolution

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1Q 2018 | IN-5015

Since the start of the industrial Internet of things (IIoT) revolution a few years ago, manufacturers have both excitedly anticipated and feared the changes it brings. So far, the sector has witnessed the rise and fall of GE Predix; the rise of Siemens MindSphere; and the emergence of transformative technologies such as digital twins, additive manufacturing, augmented reality (AR) and artificial intelligence (AI). The cloud mentality has shifted. Fear of cloud solutions in manufacturing sparked increased investment in edge analysis. Many major manufacturers recognize the benefits of increasing the access to insights and application enablement platforms (AEPs) throughout the enterprise while wanting to keep more raw data at the source and perform real edge computing.

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Manufacturers Overcoming Fear

NEWS


Since the start of the industrial Internet of things (IIoT) revolution a few years ago, manufacturers have both excitedly anticipated and feared the changes it brings. So far, the sector has witnessed the rise and fall of GE Predix; the rise of Siemens MindSphere; and the emergence of transformative technologies such as digital twins, additive manufacturing, augmented reality (AR) and artificial intelligence (AI). The cloud mentality has shifted. Fear of cloud solutions in manufacturing sparked increased investment in edge analysis. Many major manufacturers recognize the benefits of increasing the access to insights and application enablement platforms (AEPs) throughout the enterprise while wanting to keep more raw data at the source and perform real edge computing.

What started as a totally fragmented market with incomplete ‘one-stop-shops’ and microservices that struggled to share data has developed into large groups of partner ecosystems designed to meet the individual needs of any prospective client. Because of this and pushes from the Alliance of Industrial Internet (AII), the Chinese government, and the Industrial Internet Consortium (IIC), we see adoption of IIoT platforms starting to take off in the United States, Japan, China, and Germany.

Applications Will Evolve

IMPACT


So far, most smart manufacturing apps have focused on predictive maintenance and zero downtime. Already, most of the major platform providers have advertised case studies in which they all but eliminated downtime for a client. In addition, we have already seen how networking equipment on an IIoT platform can help reconfigure assembly lines for customized orders to reduce cycle time for those orders. These proof of concepts (PoCs) have encouraged a couple manufacturers to scale IIoT solutions, resulting in 16 million connected devices in the IIoT at the end of 2017.

In the latest iteration of the Industrial Internet Connectivity Tracker (MD-IICT-102), ABI research forecast that the number of IIoT connections will grow to 608 million by 2026. This does not sound like an overwhelming number of connections, but the device and app platform revenue for these connections will reach US$16 billion by 2026.  That global total rises from US$373.9 million in 2017 with a CAGR of 52% over the forecast period. This rise largely results from new software-as-a-service (SaaS) applications for industrial smart glasses, which only account for 5% of these revenues as of the end of 2017 but will make up 89% of that US$16 billion in 2026.

Recommendations for Platform Providers

COMMENTARY


To take advantage of both the current up-tick in IIoT platform adoption and the future adoption of transformative technologies, ABI Research believes that platform providers should consider the following recommendations:

  • Deepen and broaden the capabilities of your platform to support and integrate emerging transformative technologies such as AR and AI: Build software development kits (SDKs) for AR apps and partner with an AI tooling specialist.
  • Sell to IT, work with OT: IT often has the more open budget, while OT professionals often must work more hands-on with the IIoT solutions, especially the edge solutions.
  • Open your platform to as many technologies, protocols, and sources as possible: Manufacturers need their IIoT platforms to ingest data from legacy systems. Openness and flexibility will improve scalability and minimize the need for custom work for each new client.
  • Operate at the edge: Edge or fog computing can provide near real-time computing, functionality, and security for hundreds of machines or robots with centralized control in the facility without the bandwidth costs of the cloud.
  • Develop your partner ecosystem to meet the needs of your clients: Every platform provider needs a variety of partners ranging from industrial equipment suppliers to gateway suppliers and cloud infrastructure providers.

Following this strategic guidance should help minimize custom work and maximize scalability while also preparing for the future opportunities that transformative technologies will bring.

For more insights and perspectives on manufacturing and the Industrial Internet, please check out ABI Research’s Smart Manufacturing service.

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