Siemens unlocks value of industrial AI

Siemens has been focusing on industrial AI for some 30 years, helping customers with intelligent prediction, advanced diagnostics and automatic optimization throughout the entire lifecycle.

Siemens unlocks value of industrial AI

Siemens has been focusing on industrial AI for some 30 years, helping customers with intelligent prediction, advanced diagnostics and automatic optimization throughout the entire lifecycle.

Everyone can benefit from AI

Today, artificial intelligence (AI) is everywhere: mobile phone voice assistants, smart home lighting systems, and soon autonomous vehicles. But these only touch the tip of the iceberg in terms of AI’s potentials.

Dr. Roland Busch, the COO, CTO and Member of the Managing Board of Siemens AG, said, “There’s a form of AI that we can all benefit from: AI that’s integrated into industrial processes to create value on an industrial scale.”

Implement industrial AI now

Big data and AI are influencing every industry

AI applications in industrial contexts are facing unique challenges that consumer AI developers don’t have to deal with. Weak digital infrastructure and lack of domain knowledge are the most common barriers to investment in industrial AI.

Siemens has been focusing on data analytics and AI for some 30 years, and developing business by successfully applying AI in industrial contexts. In 2019, Siemens Corporate Technology set up AI Lab China in Beijing, the company’s first in Asia. It acts as a new innovation hub for Siemens, extending its global AI network, linking Europe, North America and Asia, and providing Chinese customers with leading industrial AI solutions.

“AI Lab creates an open ecosystem for emerging AI opportunities,” said Tian Pengwei, Head of Research Group at Siemens Corporate Technology China. “From ideation to creation to prototype validation, our data scientists and AI experts help customers discover the potential of AI and apply it to their businesses.”

Siemens’ suite of AI solutions is custom-tailored to each individual customer’s needs, playing an important role in intelligent prediction, advanced diagnostics and automatic optimization.

Shift from periodical inspection to real-time prediction

Leveraging data analytics and AI, Siemens is developing an intelligent predictive maintenance solution for Qingdao Refining & Chemical Co., Ltd. (Qingdao Refining).

Qingdao Refining has laid a solid digital foundation by adopting Siemens SIMATIC PCS 7, SIMIT and COMOS, creating a favorable environment for its AI implementation.

The AI solution from Siemens helps the highly automated plant consolidate data from hundreds of sensors, and detect correlations that human minds are incapable of identifying. Based on historical data and current conditions, AI technologies enable the plant to accurately predict potential malfunctions in real time, which can be hours or even days earlier than errors found by traditional periodical inspection.

In the future, Siemens and Qingdao Refining will continue to explore the value of big data via advanced technologies, such as cloud computing and edge computing.

Advanced diagnostics and “Sino-western therapy”

CR Power will work together with Siemens to build a Centralized Supervision and Analysis Specialist System

A primary objective for industrial enterprises is to maintain long-term stability, which requires the ability to not only predict potential risks but also understand reasons behind them.

In the thermal power industry, for example, CR Power Holdings Co., Ltd. (CR Power) hopes to leverage advanced digital technologies to achieve remote early warning, analysis, diagnosis and optimization for its power plants across the country. So, CR Power will work together with Siemens to build a Centralized Supervision and Analysis Specialist System (CSASS) based on Siemens’ MindSphere platform.

For advanced diagnostics, enterprises can now benefit from the Siemens AI solution that acts as an “equipment doctor” for plants. Its intelligent systems can identify patterns of sensor data through machine learning and, at the same time, incorporate knowledge graphs to diagnose problems according to signs and symptoms. Such AI approach is similar to a “Sino-western therapy” to ensure the health of plants throughout the entire lifecycle.

The “equipment doctor” from Siemens is helping customers from a wide range of industries avoid unplanned downtimes and ultimately increase operating efficiency.

Balance the cost and quality in CNC machining

FAWDE partners with Siemens to balance the cost and quality in precision CNC machining.

Like the supercomputer AlphaGo that can improve its performance while playing, industrial devices and systems can use AI to automatically optimize during operation.

In the plant of FAWDE, Jiefang Automotive Co., Ltd. (FAWDE), the high-end CNC machine tools use more than 10 types of expensive cutting tools, whose parameter settings are the key to balancing the cost and quality. Setting short lifetimes on tools will lead to high costs, while setting long lifetimes may affect product quality or even cause damage to CNC machine tools. Through machine learning algorithms, Siemens AI team helps FAWDE determine the optimal lifetimes of tools in real-time production.

Identify optimal parameter settings for yield improvement

Siemens AI experts help Nexteer identify optimal parameter settings through machine learning.

Yield improvement is another important topic for intelligent manufacturing.

Nexteer Automotive (Suzhou) Co., Ltd. (Nexteer) is working with Siemens to optimize the yield of a core component. Current technical requirements and dynamic production processes must all be considered when setting parameters on CNC machine tools. Experts from Siemens apply advanced AI technologies in precision CNC machining at Nexteer to identify optimal parameter settings.

AI and “Industrie 4.0”

Undoubtedly, industrial AI is giving the fourth Industrial Revolution a huge boost and taking “Industrie 4.0” to the next level.

Based on end-to-end IT infrastructure, intelligent software solutions allow in-depth processing of high volumes of data generated by a factory, and direct the factory to operate and optimize on its own in a dynamic environment. Meanwhile, people are relieved from the drudgery of repetitive tasks to focus on result assessment and plan development. This is how AI empowers digital transformation from production patterns to management methods, so as to establish the real “intelligent factory”.

“Our goal is to create a digital companion that will help people make better decisions,” said Dr. Michael May, Head of Company Core Technology, Data Analytics and Artificial Intelligence at Siemens AG. “Nevertheless, it is still people themselves who will ultimately make the decisions.”