In recent years, the technology industry has seen a growing emphasis on cloud computing, artificial intelligence, the Internet of Things (IoT), mobile internet, big data, and smart cities. In 2016, the concept of “Yunzhi†emerged as a new trend, focusing on big data, intelligence, mobile internet, and cloud computing. Whether it's IoT or smart cities, the underlying theme is shifting toward greater intelligence.
A few years ago, while IoT and smart cities were hot topics in theory, their practical implementation lagged behind expectations. Despite the deep integration of big data, cloud computing, and mobile internet, the lack of intelligent systems hindered the widespread adoption of IoT and smart city initiatives.
The term "intelligentity" here refers not only to artificial intelligence but also to making traditional devices and equipment more intelligent. Once everything becomes smart, the connection and data exchange between them become smoother. From this perspective, IoT is expected to continue gaining momentum in 2017.
**First, the investigation background**
With the continuous advancement of China’s industrial transformation strategy, the development of smart factories has become a key approach for manufacturing enterprises to modernize. As a critical supporting technology, the Industrial Internet of Things (IIoT) experienced rapid growth in 2017. At the end of 2017, e-works conducted a comprehensive survey on the current implementation and application of IIoT in enterprises, aiming to provide guidance for its ongoing use in manufacturing.
The survey was conducted from early October to mid-November 2017, lasting 40 days. A total of 350 valid questionnaires were collected through online, email, and telephone surveys. The target respondents included enterprise IT supervisors, IoT project implementation managers, and top executives responsible for IIoT deployment.
**Second, sample analysis**
The survey covered major industries such as electronics, textiles, aerospace, mechanical engineering, automotive parts, transportation, food and light industry, biopharmaceuticals, petrochemicals, rubber products, metallurgy, and instrumentation. Among these, mechanical engineering, automotive parts, and electronics ranked among the top three, accounting for 51.83% of the samples. These industries are known for having more mature IIoT applications.
[Image: Figure 1 – Industry Analysis of Enterprises]
[Image: Figure 2 – 2016 Corporate Revenue Analysis]
According to the revenue analysis of 2016, the majority of participating companies had revenues between 10 billion and 50 billion yuan, representing 23.15%. Companies with revenues between 1 billion and 50 billion yuan accounted for 19.01%, while those with over 10 billion yuan made up 18.18%. This balanced distribution ensures that the results reflect a wide range of enterprise sizes and real-world conditions.
[Image: Figure 3 – Industrial IoT Implementation]
**Third, application analysis**
The survey revealed that most companies were actively implementing or planning to implement IIoT solutions. Only 21.31% of participants had no plans at all. This highlights the growing interest in IIoT as part of broader digital and intelligent transformation strategies.
[Image: Figure 4 – Implemented Industrial IoT Platform]
To understand the mainstream IIoT platforms used by enterprises, e-works analyzed the data from the survey. The Siemens MindSphere platform had the highest implementation rate at 26.56%, followed by GE’s Predix at 9.38%. This indicates that MindSphere remains dominant in the industrial IoT space, particularly across diverse sectors, while Predix is more concentrated in energy and petrochemical industries.
[Image: Figure 5 – Industrial IoT Platform Features for Major Applications]
The main reasons for deploying IIoT platforms include solving challenges related to equipment connectivity, data collection, and monitoring equipment status. These three areas accounted for over 60% of the responses, highlighting the core needs of enterprises.
[Image: Figure 6 – Main Driving Force for Implementing IIoT Platforms]
As Chinese manufacturing continues to evolve, understanding the drivers behind IIoT implementation helps identify key application needs. Companies are particularly interested in monitoring plant equipment and production lines, building virtual factories, and using IIoT for real-time product monitoring and predictive maintenance.
[Image: Figure 7 – Using IIoT to Address Production Management Needs]
When asked about the main management issues IIoT can solve, the top choices included equipment status monitoring, workshop equipment connectivity, production scheduling, quality management, and site information management. These insights show that IIoT is being used primarily to improve efficiency and product quality.
[Image: Figure 8 – Industrial IoT Applications to Be Further Deepened]
Looking ahead, 40.96% of enterprises plan to optimize process performance using IIoT, while 39.16% aim to develop custom IIoT applications. Only 19.88% plan to enable plug-and-play access for industrial equipment.
[Image: Figure 9 – Industrial IoT Application Level and Status]
Despite progress, many enterprises still face challenges. The lack of unified standards and protocols was the top concern, affecting 45.81% of respondents. Other issues included a shortage of skilled personnel and an immature ecosystem.
[Image: Figure 10 – Industrial IoT Platform Selection Reference Elements]
For platform selection, 23.17% of companies prioritized industry-specific application practices, followed by data collection and analysis capabilities (22.29%) and support for data standards and protocols (16.72%).
[Image: Figure 11 – Problems in the Application of IIoT Platforms]
Looking forward, 43.9% of companies see IIoT as a key enabler for smart factory construction, while 33.54% plan to shift from manufacturing to service-oriented models. 22.56% intend to build their own IIoT platforms through industry collaboration.
[Image: Figure 12 – Future Application Planning of IIoT]
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