Industrial cloud platforms, the engine that improves quality and performance

Industrial cloud platforms are not a new concept. With people's growing demand for personalized products and services in recent years, the accelerated progression of enterprise digitalization, and pursuit for production efficiency, industrial cloud platforms have gradually become a focus of markets and a key component of an enterprise's general competitiveness.

Simply put, industrial cloud platforms are cloud-based technology solutions designed specifically to satisfy the unique requirements of production industries and enterprises. They commonly include a suite of tools and applications that aim to simplify a company's operations, increase efficiency, and reduce costs.

Next, we will discuss industrial cloud platforms and their most critical components through an in-depth analysis of distributed control systems (DCS) and controllers.

What are industrial cloud platforms

Let's first begin the understanding of industrial cloud platforms through cloud computing. It's well known by many that cloud computing is a type of distributed computing that refers to the use of network "clouds". The computing and processing of massive amounts of data is distributed into countless smaller programs before systems composed of multiple servers are used to process and analyze these smaller programs, obtain a result, and return it to the user. In simpler words, distributed computing is solving task distribution and merging the computed results.

Cloud computing is categorized in different forms based on their provided services which may be infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). If we comprehensively consider the 4 basic elements of cloud computing: Service objects, service providers, cloud software, and data resources, we can categorize cloud computing into the 3 categories of public cloud, private cloud, and industrial cloud.
 

• Private Cloud: This refers to a cloud constructed and used internally by an enterprise or department. The service provider and service object often belong in the same community of interests, the cloud software and data belong to the interest body, and there are no requirements to provide external services.
   
• Public Cloud: This refers to cloud services provided to users over the public Internet by third party suppliers. Users may access the cloud using the Internet and enjoy various services, including but not limited to computing, storage, networks, and more. Their features are data from public pathways and that cloud software is owned by the service provider; the software is extremely confidential as it is the core competitiveness of service operators.
   
• Industrial Cloud: Also known as industry cloud, they refer to the establishment and maintenance of organizations that control key resources or have a leading role within an industry or specific area. They are internal or public cloud computing platforms that provide paid or free services to internal organizations or the public within industries.

Industrial clouds are an application form of cloud computing which utilizes its technology to unify, centralize, and provide hierarchy to data of each member unit within an industry. Data processing and application systems are then utilized to promote the sharing of data and information between member units and develop a type of cloud computing form for public services. In many circumstances, they are hybrid in nature and combine both public and private cloud environments to detail the regulatory compliant standards used to maintain security over an enterprise's data and application work load.

Here, it's clear that industrial clouds not only offer a solution for internal data aggregation and sharing, it also details how the owners of industrial data can convert data into services to increase the value of businesses.

The brain and nervous system of industrial cloud platforms: Distributed Control Systems (DCS)

If it can be said that cloud networks connections are the limbs of industrial cloud platforms, then distributed control systems (DCS) are their brain and nervous system. Distributed control systems (DCS) are a type of control systems utilized in industrial applications to control and monitor complex production processes. There are several processes that require simultaneous control and monitoring in typical industrial environments. DCS can be used to integrate and coordinate these processes to improve their performance and reliability.
DCS can be utilized in industrial cloud platforms to control and monitor the various processes and systems that comprise platforms. For example, DCS can control the temperature and humidity levels in a manufacturing plant, monitor the performance of various machines, and manage the flow of materials and products.
DCS in industrial cloud platforms usually consist of several components including:

• Controller: Equipment used to control various processes within platforms. They can be distributed in different places but must be capable of connecting to a central control system.
• Sensors: Equipment used to monitor the performance of various processes within platforms. They can be used to monitor temperature, pressure, flow, or other variables.
• Human-Machine Interface (HMI): An interface that allows operators to interact with DCS. They can include a graphical user interface (GUI) or command line interface (CLI).
• Communication Network: A networks that connects all equipment in a DCS. This can be a wired or wireless network based on the specific requirements of the platform.

Clearly, DCS are a key component of industrial cloud platforms that ensures all processes and systems can work effectively.

Controllers, the core of DCS

Distributed control systems (DCS) are computer systems used to control and monitor industrial processes within factories; controllers are the core of DCS. It's not hard to see that the design and implementation of controllers in DCS are a challenging task that must solve the following critical challenges:

• The dynamics of processes: The activities within a process can be complex and dynamic. Understanding the dynamics of processes is extremely critical in designing effective controllers. Controllers must be capable of adapting to changes within processes and maintain reliable operation.
• Selection of control algorithms: There are several control algorithms that can be used in DCS including proportional-integral-derivative (PID), model predictive control (MPC), and fuzzy logic. Selecting an appropriate algorithm for processes is the key to achieving optimal control performance.
• Controller calibration: Once a control algorithm is selected, controllers must be calibrated to ensure optimal performance. This involves calibration of a controller's parameters to minimize the difference between required settings and process variables while maintaining stability.
• Communications and networks: DCS controller are often distributed across multiple nodes and must be connected via network. Ensuring reliable communications between nodes is extremely important to prevent impact to control performance such as delay or data loss.
• Network security: DCS controllers are often need to be connected to the Internet or other external networks, making them vulnerable to cyber attacks. Implementing powerful network security measures to protect DCS against unauthorized access or malicious attacks is absolutely necessary.
• Maintenance and upgrade: DCS controllers are complex systems that require regular maintenance and upgrade to ensure optimal performance. This may be a challenge in industrial production environments because it's necessary to reduce downtime and prevent interruptions to production.

It can be seen from the above that the design and implementation of controllers in DCS is a task that requires a wealth of industry knowledge and accumulation of experience. To a certain extent, this explains why industrial cloud platforms contain the most ecosystem attributes out of all cloud platforms. Enterprises can sufficiently utilize the potential of ecosystem partners in the joint building of this platform. For example, STMicroelectronics (STM) can contribute their expertise in hardware and software development to provide enterprise customers with specific products and services that solve the unique challenges and requirements of IoT industrial cloud platforms. These collaborative models allow enterprise developers to focus on developing the added value of vertical applications and pass on the complexity of node to cloud connections to the team at STM.

Future and Development of Industrial Cloud Platforms

The development of industrial cloud platforms is currently undergoing a phase of strong growth. The primary factors driving this growth can be summarized into:

• Targeting: The increased specialization of enterprises has resulted in software solutions targeted towards specific requirements. Industrial cloud platforms offer these solutions as general purpose cloud platforms are not equipped for the specific properties and functionalities required in industries.
• Effectiveness: Compared to internal software solutions in the past, industrial cloud platforms offer significant cost savings and performance increases. Through cloud-based infrastructure and economies of scale, industrial cloud platforms can offer powerful software functionality at lower costs compared to traditional software solutions developed internally.
• Competitiveness: Industrial cloud platforms can help enterprises remain competitive by offering the industry's latest technologies and best practices. By using industrial cloud platforms, enterprises can keep up with fast changing technology trends and regulatory requirements without the need to develop and maintain their own software solutions.

Recently, Gartner conducted an investigation of North American and European enterprises and discovered that nearly 40% of interviewees have already adopted industrial cloud platforms. Approximately 15% of enterprises are conducting pilot programs while another 15% are considering deployment before 2026. Most interviewees familiar with industrial cloud platforms believe that they are adopters or potentially considering industry-specific cloud platforms. By 2027, Gartner estimates that more than 50% of enterprises will apply industrial cloud platforms to accelerate key business initiatives; as of 2021, less than 10% of enterprises have adopted these practices.

As more companies turn to professional software solutions that can help maintain their competitiveness in their field of industry, it's clear that the development of industrial cloud platforms will be an indispensable engine that drives improvements in both quality and performance.