The network transmits various types of information from the access layer to the management component via the underlying bearer network. The management component provides users with a visual system management and configuration platform, helping them quickly build the entire architecture of their IoT application systems and providing the technical foundation supporting the operation of the entire IoT application system, primarily manifested in rapid data analysis and event processing capabilities. The application component provides users with a visual data display platform, including real-time data display, basic data analysis results such as data comparison and correlation, and event alarms. The application component provides users with various clearly defined big data application APIs for easy user invocation or integration, while also providing open API interfaces to allow user-defined application modules to access the platform.
An industrial IoT cloud platform should have the following functions:
Device integration function
This encompasses the configuration, management, and decommissioning of all devices, including sensors, actuators, tags, and beacons, within the Industrial Internet of Things (IIoT). An IIoT cloud platform should be able to automatically acquire IoT data and make it available to other elements on the network.
Data integration function
The value of the Industrial Internet of Things (IIoT) lies in its data, which must be captured, integrated, and managed. IIoT cloud platforms correlate new IoT master data with existing application software data and data from other sources such as social media to explore their correlations.
Process integration function
As part of the digital ecosystem, Industrial IoT elements are not isolated from business operations. Industrial IoT solutions must be embedded into enterprise business processes and workflows. To this end, Industrial IoT cloud platforms integrate IoT business logic into other backend systems and deploy IoT data into workflow management, thereby achieving the integration of IoT solutions, business processes, and workflows.
Ecosystem services
Industrial IoT cloud platforms are responsible for securely establishing, launching, and managing trusted interactions between people, devices, data, and equipment within the digital ecosystem.
The Industrial Internet of Things (IoT) is often seen as an innovative way to enhance enterprise efficiency and product quality, with a high return on investment (ROI). However, the problem is that every IoT cloud platform is different, and this does not mean that every Industrial IoT cloud platform is suitable for every enterprise's business scope and process needs.
Enterprises typically start by deploying one or two key IoT solution demonstration sites, but they are unaware that some industrial IoT cloud platforms focus on providing basic technical equipment for the solutions, while other IoT service platforms focus on providing solutions for specific business areas.
To select a suitable industrial IoT cloud platform, you must understand the following:
1. Different types of industrial IoT cloud platforms
Before selecting an industrial IoT cloud platform, you must determine the type of service platform that is suitable for your solution.
Currently, there are more than 700 industrial IoT cloud platforms, and each platform offers different content. Generally speaking, they belong to the category of IoT technology platforms or IoT technology operation service platforms.
Choosing the right type of industrial IoT cloud platform depends on the company's internal requirements. Some companies have already integrated controllers into their property and mobile data solutions to capture device statistics, while others are looking for a data analytics solution to provide their teams with data visualization and actionable insights.
Ideally, you should find an industrial IoT cloud platform that can provide solutions for your business use cases, and a service platform built on service specifications and mature technologies (such as IoT device maintenance, information security, and data storage).
2. Industrial IoT Cloud Platform Solution
While industrial IoT cloud platforms must provide technical infrastructure to ensure that delivered IoT solutions are scalable, secure, and manageable in manufacturing, the business value of such service platforms stems from their solutions.
Some IoT service platforms claim not to provide solutions; instead, they offer manufacturers specialized tools for building and testing their own solutions. This requires manufacturers' employees to possess expertise in information security, mobile data, database management, computer science, and big data visualization—a daunting task for most manufacturers.
Other industrial IoT cloud platforms focus on business-wide solutions, such as predictive maintenance, predictive analytics, and network monitoring of product quality and conditions.
Before verifying the capabilities of an industrial IoT cloud platform, you should define the main solutions you intend to apply. In fact, solution functionality is a primary consideration when selecting an industrial IoT cloud platform.
How to choose an industrial IoT cloud platform that matches your business?
1. Identify the pain points
Identify the company's main pain points and pinpoint areas where resources or revenue are flowing out. Based on an examination of overall equipment efficiency (OEE) and by selecting areas with the greatest potential for improvement, determine suitable solutions as test cases.
In a recent Seebo survey of manufacturers, 62% of respondents said that the root cause of their major failures was related to the manufacturing process; another 25% said that the root cause of common failures was related to the motors and rolling bearings of the production line; while power energy and logistics system problems ranked third and fourth, respectively.
Enhancing manufacturing processes or using stronger network monitoring to prevent equipment failures requires different service support. Some service platforms are better suited for process manufacturing than discrete manufacturing, and vice versa. However, it's clear that not every industrial IoT cloud platform is suitable for every solution; therefore, before researching a service platform, internally determine what tasks are most needed.
2. Contextualization and Raw Data
For some production lines, especially those outside the manufacturing process, collecting statistical data from the processing steps is sufficient. However, in more complex manufacturing processes, various independent variables can affect the results. To control production volume and product quality, manufacturing results must be contextualized based on statistical data from the production process. For manufacturers, contextualizing statistical data within the manufacturing environment and process framework is particularly important.
3. Security
Information security has always been a serious challenge. Industrial assets are not as vulnerable to hacking as customer equipment, but it is essential to protect collected data, and you must develop strict measures to protect who can access what data, from which location, and when that data is accessed.
Statistical data integration
Integration is multifaceted. In the manufacturing process, you not only need to obtain operational statistics from the production planning monitoring center and statistical history personnel, but you also need to correlate them with statistics from MES, ERP, and quality management systems.
Most importantly, you must ensure that the service platform takes into account the production process in its statistical data to accurately reflect your production process and its assets.
