Manufacturing is also undergoing digital transformation, and the cloud plays an important role
The technological progress of the manufacturing industry usually faces operational challenges. They face the problems of information collection, high operating costs, weak integration of operating technology (OT) / information technology (IT), high-speed computing requirements, and machine downtime. However, most traditional infrastructures are not fully prepared for a long-term digital transformation journey. Industrial companies are seeking cloud service providers to meet the ever-increasing performance requirements. The cloud can assist in dynamically expanding storage and achieving cost optimization, which makes it the key to solving current and emerging manufacturing challenges.
Although cloud computing is one of the keys to Industry 4.0 and the Industrial Internet of Things (IIoT), most of the manufacturing industry has not started using the cloud yet because of the challenges of integration, income worth of the capital investment, data privacy, security issues and employees’ anxiety about changes in operating processes are keeping many companies on the sideline.
Modern manufacturing scenarios require embracing the cloud and starting their transformation journey more than ever. According to Frost & Sullivan’s research, the use of cloud asset management technology can increase over 10% uptime in one year compared to the average. In order to achieve this operational benefit, it is recommended to start from a small place to achieve ROI, rapidly expand the scale, and increase the degree of adoption within the enterprise. The typical digital transformation needs to last five to seven years, and the general manufacturing industry will start preparing about 14 to 16 months ahead and prepare for digital applications in the next three to five years. This newsletter will introduce you to the benefits of using cloud services in the Manufacturing Industry and how to transform with the cloud.
Eight aspects of manufacturing that can be applied to the cloud
Establish backup and disaster recovery
The manufacturing industry generates a lot of critical data, so regular backups are required. The loss of data may be caused by a variety of reasons, such as database damage, hardware failure, human error, or even natural disaster. To determine which data backup solution is suitable, companies should make decisions based on the needs of capacity, speed, and scalability. However, if there is no reliable method of data restoration, the backup solution is meaningless. After the backup solution goes online, routine tests should be performed to ensure that the data can be restored.
After establishing a cloud architecture, manufacturers can decide where applications generate the most value. For example, products and design are areas where the cloud excels. They use high-performance computing resources (such as computational fluid dynamics, finite element modeling, etc.), which can be put on the cloud as a cost-saving method to execute, and other workloads can be used for local resources.
Product design tools, such as electronic design automation (EDA), are costly to deploy on the ground. In recent years, the computing power and infrastructure requirements for designing, testing, verifying, and building these systems have also grown significantly. Running product design workloads in the cloud can accelerate innovation and improve collaboration, while also reducing costs.
Manufacturing companies can develop cloud-based applications with high-value capabilities that affect almost every aspect of their business. Enterprise-level application development allows manufacturers to reconsider how to manage the operations of various business units in the value chain.
Enable data streaming analysis
Streaming analysis refers to the processing of streaming data promptly. Now, this feature is a prerequisite for effective implementation of IIoT solutions. The manufacturing process is a fast-paced and interdependent situation. Stream analysis can monitor timely performance and provide timely optimization suggestions. The benefits it brings to manufacturers include improved operational efficiency, reduced costs, balanced interdependence, and reduced risk. Smart devices are powerful for data. Their emergence will require reliable pipelines to coordinate with smart manufacturing. Manufacturers can conduct comprehensive development through cloud and streaming analysis platforms.
The data lake is a centralized repository that can store data of different structures. The data can be stored as is, and whether or not the structure can be analyzed through AWS-related big data services. In today’s diverse manufacturing environment, pushing all data to a data lake can help establish an understanding of the manufacturing environment. Also, the data lake can be automatically expanded by scheduling, collection, retrieval, storage, and calculation to improve operational performance.
Machine Learning and Artificial Intelligence can execute and recognize beyond human capabilities. This feature is very important for manufacturers who want to improve complex production processes and make predictions before machine failures.
Edge analysis deployment
The analysis model is usually trained by a cloud server. However, through edge analysis, sensors, or tags embedded in the product or device can take immediate action on the source of the problem. Messages generated by the micro data center and connected devices can be aggregated, classified, and processed in a quick response at the edge.
During the merger, the data was managed and used immediately, irrelevant messages were accurately deleted, and important remedial alerts were immediately generated.
Factory data center replacement
The growing demand for data storage in the manufacturing industry may require data centers to reconfigure their servers to handle a wider and more diverse data stream. Many people may think that security is the biggest threat to migration to the cloud, but cloud service providers have invested in strong security standards based on this demand. Such performance has already aroused high recognition in industries such as healthcare and financial services.
The following is the architecture diagram of manufacturing industry combined with AWS services:
Three benefits of adopting cloud in manufacturing
Improve the operating efficiency of the overall equipment
Manufacturers can store production data in data lakes, which can be used to safely store, classify, and analyze data, and use these data to train AI / ML services. Subsequent applications of these functions can help optimize production processes. Previously, internal experts could only optimize based on the problems that had occurred. Now, industrial and manufacturing software vendors can provide real-time and predictive analysis. This can improve overall equipment efficiency (OEE), service levels, product quality, and supply chain efficiency.
Improve agility: rapid expansion
Developers can get cloud computing resources in minutes. Organizational agility can significantly improve as the cost and time required for experiments and development are greatly reduced and resources can be increased or decreased according to capacity requirements.
Cloud services can help organizations develop new sources of income and save costs by optimizing the benefits of capital investment, reducing constraints, and discovering new ways to profit from their services.