With the rapid development of network technology, traditional operation and maintenance (O&M) models can no longer meet the demands, and equipment O&M is beginning to migrate to cloud platforms. Based on this, this paper proposes an intelligent remote O&M service platform. This platform adopts a SCADA system and a hybrid architecture to digitize resource data, achieving automated and efficient O&M. The paper also illustrates the application of this advanced O&M service platform in enterprises and its resulting economic and social benefits through case studies.
In recent years, with the increasing demand for high-speed processing, the demand for intelligent equipment has been rising, and more and more intelligent equipment is being sold throughout the country. However, the resulting after-sales maintenance and equipment failure repair issues have become pain points for both parties. For manufacturers, it requires the establishment of a dedicated after-sales engineering team that can be dispatched to the site at any time, resulting in high personnel maintenance and transportation costs. For customers, waiting for maintenance can lead to the shutdown of the entire production line, affecting production plans and wasting the cost of other equipment. Addressing these pain points for both equipment manufacturers and customers, this paper proposes a cloud computing platform based on a combined MVC and Bootstrap architecture. The core of the platform, through a SCADA system, integrates data acquisition, monitoring and control, parameter adjustment, and various signal alarms, solving and ensuring the high performance and high availability of the cloud platform. This maximizes resource utilization and benefits in practical applications, protecting the interests of equipment manufacturers, fostering long-term and close relationships between manufacturers and customers, and promoting the rapid development of cloud platform applications.
Overall design of cloud platform
1. Introduction to Cloud Computing
Traditional IT deployment architectures are siloed. In this architecture, when a new application system goes live, the resources required for that application system need to be analyzed to determine the specifications and quantities of computing, storage, and network equipment needed for the infrastructure. This model leads to problems such as over-configuration of hardware for underutilization, integration difficulties, and is detrimental to overall resource utilization, resulting in excessive waste of data center space and energy. However, the introduction of cloud computing effectively solves these problems. It cloudifies the infrastructure, thereby better supporting the launch, deployment, and operation and maintenance of application systems, improving efficiency, and reducing TCO. Virtualization technology is one of the key technologies of cloud computing. Through virtualization, cloud computing can integrate various resources to create a vast virtual resource library, allowing cloud users to dynamically obtain the resources they need according to their own requirements.
On the other hand, by utilizing technologies such as virtualization, previously unused resources can be integrated by cloud computing platforms and incorporated into a virtual resource library, forming a provider with massive storage capacity and high-efficiency computing capabilities. Currently, various companies have launched cloud solutions with their own characteristics. Different solutions have different understandings of cloud computing, but generally speaking, the common cloud platform architecture is divided into three layers: the application layer, the platform layer, and the resource layer. The resource layer mainly aggregates various resources into the cloud platform, forming a dynamic resource library. The utilization and recycling of various resources in the resource layer are all handled by the cloud platform. The platform layer is mainly for application software developers, presenting the deployment environment, development environment, and testing environment as a whole to developers, effectively improving development efficiency. The application layer is mainly for cloud users, enabling cloud users to access the cloud through its provided software interaction interfaces, sending service requests to the cloud platform, and ultimately obtaining and using services.
2. Overall Architecture of the Cloud Platform
The platform proposed in this paper is applicable to the remote operation and maintenance of various intelligent devices. Based on a BS, CS, and data cloud framework, it establishes a data acquisition channel through a SCADA system. Data from the PLC controllers on the devices is collected and connected to the cloud platform via 4G/WIFI. Through the channel established by the SCADA system, remote uploading and downloading of PLC programs and program diagnostics are possible. By acquiring data from the PLC controllers, remote fault prediction and analysis of intelligent devices can be achieved, providing early warning signals for potential faults and detecting and analyzing existing faults. This improves equipment efficiency, reduces maintenance costs, and ensures safe and stable equipment operation.
Figure 1 shows the overall architecture of the cloud platform, which adopts a hybrid framework of B/S (Browser/Server), C/S (Client/Server), and data cloud. It fully leverages the advantages of B/S's cross-platform compatibility and low client-side maintenance, as well as the benefits of C/S's fast response and strong security, ensuring the platform's efficient and stable operation. Therefore, based on this and under the real-time monitoring of the cloud platform monitoring system, the cloud platform can achieve the following:
(1) Automatically collect equipment performance data. With the widespread adoption of SCADA in equipment, all equipment automatically uploads its performance data (capacity, utilization rate, and efficiency rate) to the cloud platform.
(2) Automatic data parsing by the cloud platform. The cloud server automatically parses data uploaded by devices in various locations in real time, and realizes data storage and distribution.
(3) Multi-platform data display. Enables device data display on computer web terminals and mobile APPs, and updates all client versions online.
(4) Remote early warning and upgrade maintenance. Enables remote monitoring and management of equipment, query of historical equipment data, alarm handling, prediction of equipment life cycle, reminders for customers to replace or maintain consumables, and remote upgrade and maintenance of equipment control systems.
Example Application
From the perspective of the current state and future development trends of enterprise operation and maintenance services, changing existing operation and maintenance models and workflows, and leveraging advanced information technology and methods to build an operation and maintenance service management platform to accelerate response speed, improve work efficiency, and enhance user satisfaction is a natural progression and an inevitable trend. The following example, using an enterprise's use of an intelligent device operation and maintenance platform, illustrates the application of advanced operation and maintenance service models within an enterprise. The platform integrates advanced information technologies such as web services, cloud computing, and big data. It utilizes a SCADA system to solve the problems of real-time monitoring and location detection of intelligent devices, and applies a hybrid framework model of BS, CS, and data cloud to solve cross-platform issues such as communication interconnection and remote software interoperability. This combination of technologies effectively shortens the platform's fault response speed and fault recovery time for users, breaks through the traditional concept of operation and maintenance services, significantly improves the efficiency of operation and maintenance services, protects the interests of both enterprises and users, and promotes cooperation between the two parties.
Through the intelligent device operation and maintenance service platform, the operation and maintenance center's backend service system can monitor the working status of intelligent devices in real time. When a smart device malfunctions, the system automatically alarms, and the operation and maintenance service center displays the fault point in real time, generating a fault report. The platform can respond to fault alarms within 2 seconds and, based on GPS location, arrange for nearby technicians to provide on-site repair services. Users can also send repair requests to the operation and maintenance service center via mobile software. Fault response and equipment recovery times are shown in Table 1.
The practical application of the intelligent device operation and maintenance service cloud platform has brought obvious benefits, as shown in Figure 2. Quantitative analysis and calculation show that, taking 100 devices as an example, without increasing personnel input, the operation and maintenance service cloud platform can save 250 person-days per month compared to before, significantly improving operation and maintenance service efficiency, shortening fault recovery time, reducing after-sales service costs for enterprises, and protecting the interests of both customers and enterprises.
Conclusion
SCADA systems are a core component of intelligent device operation and maintenance service platforms. They provide data collection, analysis, and transmission for operation and maintenance service centers, while also monitoring and controlling on-site equipment, enabling resource sharing and configuration. This paper explores the operation and maintenance platform, deeply learning related hardware, software devices, and system modules. It proposes a mature intelligent device operation and maintenance platform that significantly shortens response time, improves work efficiency, reduces the workload of operation and maintenance personnel, enhances user satisfaction, and effectively meets the operation and maintenance needs of intelligent devices.
