How Google Is Helping Siemens IIoT Ambitions
While there are still many problems with the Internet of Things (IoT) and the Industrial IoT (IIoT), it has not stopped many of the companies that are developing IIoT applications and infrastructure from developing new products and even alliances. One of the most notable alliances in recent weeks has been the recently announced partnership between Google and Siemens, who are to pooling resources to better facilitate better IIoT applications in the enterprise.
This follows the announcement earlier this month that TX-based Siemens plans to integrate Google Cloud’s data cloud and artificial intelligence/machine learning (AI/ML) technologies with Siemens factory automation solutions. The partnership is a logical one and the two together should enable organizations to develop a more powerful and effective IIoT presence.
Google Cloud accelerates organizations' ability to digitally transform their business with infrastructure, platform, industry solutions and expertise. Over the past quarter (Q, 2021) it brought in $4.047 billion in sales, Alphabet, Google's parent company, reported recently.
Siemens Digital Industries (DI) for its part offers organizations the ability to deploy automation and provides them with the tools for digitalization enabling the automation of the entire value chain.
Improving Productivity on the Plant Floor
This “cooperation,” as the companies are calling it, is specifically targeted at factory processes and aims to improve productivity on the shop floor. To do that Siemens will integrate Google Cloud's data cloud and artificial intelligence/machine learning (AI/ML) technologies with its factory automation solutions to help manufacturers innovate for the future.
While data is driving all organizational processes across the digital workplace, many manufacturers continue to use legacy software and multiple systems to analyze plant information, which is resource-intensive and requires frequent manual updates to ensure accuracy. In addition, while AI projects have been deployed by many companies in "islands" across the plant floor, manufacturers have struggled to implement AI at scale across their global operations.
Combining Google Cloud's data cloud and AI/ML capabilities with Siemens' Digital Industries Factory Automation portfolio, manufacturers will be able to harmonize their factory data, run cloud-based AI/ML models on top of that data, and deploy algorithms at the network edge. This enables applications such as visual inspection of products or predicting the wear-and-tear of machines on the assembly line.
Deploying AI to the shop floor and integrating it into automation and the network is a complex task, requiring expertise and cloud products, especially at the edge. The goal of cooperation between Google Cloud and Siemens is to make the deployment of AI in connection with the Industrial Edge — and its management at scale — easier, automating mundane tasks, and improving overall quality at the shop floor.
Related Article: 7 Big Problems With the Internet of Things
Digitization Forces Change
The rise of technologies such as IoT, AI and 5G, and the rapid acceleration of innovation driven by software-defined solutions with continuous delivery models is forcing the industrials to change their approach. It is a necessity for them to “cross the chasm” and remain competitive because there’s not enough money in the world to fend off the onslaught on new innovators, not to mention the growing dominance of the cloud scalers. This in turn is forcing a blurring of lines between the OT and IT worlds, Jason Shepherd, VP Ecosystem at San Jose, Calif.-based Zededa, told us in respect of the Google Siements partnership.
This trend has emerged over the past seven years or so. GE Digital came out swinging with Predix in 2014, but failed because they tried to take on too much in both building out the Predix software platform and their own IT data centers. Then Siemens came out with Mindsphere, and from the start decided to not build their own data centers, deploy their customer Industrial IoT platform on Azure and AWS infrastructure (in this case IaaS). This was a better strategy, but still required a lot of internal lift within Siemens. As a result, Mindsphere has made minimal impact on the market over the past several years.
He believes that this is the winning strategy for the long run — focusing on value creation vs. reinvention. The industrial providers that will emerge as leaders in the new world of digital transformation will apply their domain knowledge to open, consistent infrastructure while offering necessarily unique hardware, software, and services. Open collaboration, increasingly though open source communities like the Linux Foundation’s LF Edge organization, will help providers avoid “undifferentiated heavy lifting” and drive scale through a network effect, as open models have proven to do in the IT world for years.
Even still, he says legacy thinking lingers, and internal alignment within the incumbent industrial providers continues to be an issue. Bill Rue’s executive directive to use Predix was shunned by the GE business units because the platform was immature and not meeting their needs, so the BUs went to outside vendors or invented their own solutions. Interestingly, even this new Siemens announcement with Google is orthogonal to the Mindsphere organization’s investments.
This partnership was driven by Siemens’ Simatic hardware business unit which bought Pixeom in late 2019 to enable orchestration for their Industrial Edge offering for factory floors. Pixeom also already had an established relationship with Google, which was the connective tissue that led to this more formal collaboration. In doing so, the Simatic team has effectively created a full stack offer that effectively competes with Siemens’ own Mindsphere effort.
Related to all of this is the role the AI/ML space will play out over time. AI software frameworks like TensorFlow driven by Google will become more standardized as part of foundational infrastructure, and the algorithms, domain knowledge and services on top will be where developers continue to meaningfully differentiate.
Learning Opportunities
“It makes great sense for industrial players like Siemens to increasingly build on the platforms and infrastructure provided by the cloud scalers, with a focus on differentiating through their domain knowledge and necessarily unique industrial hardware and software.
Stuck In Legacy Software
Eden Cheng marketing is director and co-founder of Singapore-based software developer WeInvoice. He points that with data primarily driving most industrial processes these days, most manufacturers are still stuck using legacy software and programs to analyze plant information. This is often ineffective and mundane as it requires consistent manual updates to ensure accuracy. Moreover, while AI projects have often been implanted by many industrial leaders across their plant floors, many manufacturers have still been unsuccessful in trying to efficiently implement AI across most of their global operations.
With this partnership, Google will be able to provide Siemens an opportunity to harmonize its factory data, run cloud-based AI/ML models and effectively deploy algorithms at the network edge. This could lead to the creation of applications that can handle tasks, like visual product inspections or the prediction of the wear-and-tear of assembly-line machinery.
“While deploying AI software programs and integrating them on an automated plant floor is often a complicated process, it’s safe to say that a successful partnership between these two giants can significantly help in empowering employees, automating mundane tasks as well as improve overall product quality on the plant floor for Siemen,” he said.
In other words, the combination of both industrial and technology expertise of Siemens and Google has implications in bringing about holistic AI solutions that traverse beyond pilot projects and test cases, not only for Siemens but for other industry leaders in similar markets as well.
Siemens' Ambitions
But Google is not the limit of Siemens’ ambitions in IIoT space. It has also recently announced a new partnership with Tangent Works for its’ InstantML technology to add to MindSphere giving it new AI capabilities for AI for IIoT
The new AI for Everybody solution integrates the power of Tangent Works InstantML technology into MindSphere, the industrial IoT as a service solution from Siemens, to enable users to use IoT data collected by Sieman’s MindSphere to generate new insights without the need for complex model training and management.
Many organizations are still struggling to scale their digital transformation projects and use IoT data harvested using advanced AI and machine learning (ML) technologies. This is problematic as ML offers huge opportunities for industrial applications. However, it often requires deep knowledge about advanced statistics and how it is applied in industrial use cases, as well as the scarce and expensive resource of data science experts.
“We are witnessing massive investments into digital and AI as companies get ready for post COVID-19 operations. Already before the pandemic, our research showed that a shortage of digital talent, especially in IT and data science, was the biggest challenge for companies looking to realize IoT, Industry 4.0 and AI initiatives,” said Knud Lasse Lueth, CEO at IoT Analytics.
“This challenge will only get worse in the coming years and most firms will simply not find the experts that can build the machine learning models and integrate them into everyday operations. Companies that cannot find or afford these highly specialized digital employees will turn to low-code software tools to empower non-technical employees, or ‘citizen developers’.”
About the Author
David is a full-time journalist based in Paris, who spends his time working between Ireland, the UK and France. A partisan of ‘green’ living and conservation, he is particularly interested in information management and how enterprise content management, analytics, big data and cloud computing impact on it.
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