Converging Manufacturing Processes with the Industrial Cloud

This resource provides manufacturers and technology solution providers a better understanding of the expanding industrial cloud market, what hyperscalers are doing to differentiate themselves, and the latest customer priorities.

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Market Overview

  • The first manufacturing technologies to migrate to the cloud were data derived directly from Industrial Internet of Things (IIoT) devices for simple storage, then Two-Dimensional (2D)/Three-Dimensional (3D) Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM) software, followed by Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MESs), Product Lifecycle Management (PLM), Artificial Intelligence (AI), quality, and digital twin solutions.
  • The global market for manufacturing cloud infrastructure and services will grow from US$43.67 billion to US$333.69 billion from 2023 to 2033 (a 22.57% Compound Annual Growth Rate (CAGR)) as these developments take shape and the thrust for capabilities enabled by the cloud extends beyond large industrial enterprises into the Small and Medium Enterprise (SME) segment.
  • Cloud manufacturing revenue by provider totaled US$35.6 billion in 2022, broken down as follows:
    • Amazon Web Services (AWS): US$12.8 billion (35.98% market share)
    • Microsoft: US$10.8 billion (30.27%)
    • Google: US$4.2 billion (11.82%)
    • IBM: US$2.4 billion (6.88%)
    • Alibaba: US$1.9 billion (5.29%)
    • SAP: US$1.8 billion (4.95%)
    • Oracle: US$941 billion (2.64%)
    • Tencent: US$763 billion (2.14%)
  • ABI Research reports that the manufacturing sector accounts for 16% of the cloud's global Gross Domestic Product (GDP) contribution. East Asia & Pacific sees the highest regional contribution (23%).

“Prior to the cloud, local, on-premises, or External Data Warehouses (EDWs) were used to store and analyze data. While local, on-premises, and EDWs have the capacity to run manufacturing solution offerings, they are vastly more expensive and have critical segmentation flaws. These servers were prone to fragmentation and duplication, along with creating data silos where critical datasets sat independent of one another, not collaborating to produce new KPIs. Cloud manufacturing systems eliminate these concerns by interconnecting applications bi-directionally, leading to sharing and communication between applications and their data.” – James Iverson, Industry Analyst at ABI Research


Table 1: Cloud Manufacturing Revenue for Hyperscalers and Major Players

2018 to 2022

(Source: ABI Research)

Company

Revenue

2018

2019

2020

2021

2022

CAGR 18-22

Google

(US$ Millions)

934

1,427

2,089

3,073

4,205

35.11%

AWS

(US$ Millions)

4,104

5,600

7,200

9,952

12,800

25.55%

Microsoft

(US$ Millions)

4,181

5,220

6,621

8,414

10,771

20.84%

Total

(US$ Millions)

9,219

12,246

15,910

21,439

27,776

27.16%

 

 

 

 

 

 

 

 

Alibaba

(US$ Millions)

342

589

898

1,468

1,882

40.67%

IBM Cloud

(US$ Millions)

1,376

1,520

1,837

2,186

2,448

12.20%

SAP

(US$ Millions)

799

1,109

1,293

1,507

1,763

17.15%

Tencent

(US$ Millions)

203

364

585

675

763

30.34%

Oracle

(US$ Millions)

923

936

821

864

941

0.38%

Total

(US$ Millions)

3,643

4,518

5,433

6,700

7,797

20.15%

               

Overall Total

(US$ Millions)

12,861

16,765

21,343

28,139

35,573

22.57%

Table 2: Total Cloud Manufacturing Revenue Forecast

2023 to 2033

(Source: ABI Research)

 

Revenue

2023

2024

2025

2026

2027

2028

2029

2030

2031

2032

2033

CAGR 23-33

Total

(US$ Billions)

43.6

53.44

65.5

80.28

98.41

120.62

147.84

181.21

222.11

272.24

333.69

22.57%

Key Decision Items

The next two sections provide strategic guidance for manufacturers evaluating the industrial cloud, followed by recommendations for technology solution providers.

Examine the Entire Manufacturing Process from a Data Perspective, from Design through Assembly

Manufacturers should speak to on-site engineers, industrial designers, and plant managers about data access and efficiency while on the job. Understanding hardships and tedious processes at these junctions will provide critical insight into whether the cloud should be implemented.

Common issues for manufacturers include accessing data stored in multiple locations and deficient usable assets; cloud-based manufacturing systems can solve both. At the same time, many manufacturers are unsuitable for cloud systems due to heavy investment in existing on-premises servers or smaller production lines (for 2D/3D CAD software). For these manufacturers, industrial cloud offerings just don’t have the same appeal, as they won’t be able to leverage many of the base offerings that hyperscalers provide.

Understand Your Business Needs

Talking to customers and key purchasers is another important thing for manufacturers to do when considering industrial cloud solutions. That way, you can gauge how receptive they are to a transition to the cloud. Security concerns, such as data ownership and accessibility, may inhibit some customers. It should be communicated to them that modern security solutions from AWS, Microsoft, and Google are safer and more secure than on-premises servers.

Other customers may find the costs of transitioning company servers to the industrial cloud a reason for caution. In this case, flexible payment options should be introduced. Hyperscaler payment plans include pay-as-you-go, on-demand, and spot instanced—all of which enable customers to adopt cloud solutions with minimal risk.

Now, we provide a couple of recommendations for technology solution providers facilitating industrial cloud applications.

Speak to Customers Regarding Operability

Industrial cloud innovation and development pipelines should come from end-user feedback, not solely as a response to competition in the market. Feedback from manufacturers, such as ineligibility to operate functions within cloud applications, should be the driver for updates. AWS, Google, and Microsoft offer 200+ managed services for data ingestion, storage, and analytics. Therefore, the process of understanding the optimal use and building out the correct cloud architecture of industrial applications for manufacturers is daunting.

Implementing AI with Large Language Models (LLMs), along with expert advice, has been the active solution taken by hyperscalers to address these challenges. Having digital assistants guide users through comprehensive analyses with easily digestible instructions, LLMs are slowly curbing these issues arising from manufacturers. Improving AI integration into cloud manufacturing systems will reassure manufacturers that they are getting the most out of their platform of choice.

Establish Exclusive Partnerships

Well-known manufacturing solution providers have already adapted their software to run on all three cloud systems provided by hyperscalers. Autodesk, Dassault Systèmes, and Siemens are examples of service providers that operate in conjunction with the big three. For differentiation, hyperscalers should explore the cost-benefit of offering services from exclusive solution providers.

Although it is more expensive to lock down a provider to a single hyperscaler service, the benefit of product distinction will drive more industrials to adopt the specific cloud option with these partnerships. For example, Microsoft has been exclusively partnered with OpenAI, a generative AI LLM that assists in almost every application within its Azure network.

When done correctly, being the only hyperscaler to offer a specific industrial cloud solution will bolster new customer adoption and increase revenue through existing customers who use these exclusive offerings. Additionally, with the integration of exclusive partnerships, poaching clients from other cloud service providers becomes more likely.

Key Market Players to Watch

Dig Deeper for the Full Picture

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