Four steps away, from "manufacturing" to "intelligent manufacturing"

Transforming intelligent manufacturing is a key upgrade for the future development of manufacturing enterprises. However, in the current actual transformation process, enterprises have been hit hard: either they have insufficient awareness of themselves, or blindly invest, or do not have a clear transformation plan.

As the saying goes: You can get more with less with less effort. How many stages does a company need to go through in the process of transformation? What are the key tasks to be accomplished at different stages? According to the long-term follow-up reports of CEConlines, companies that can steadily transform and gradually move in the right direction have a clear understanding and plan of their own level and the transformation stage they will go through in the future.

From the analysis of the results of a series of interviews with managers around the world and some basic consensuses formed in the current industry, the transition from "traditional manufacturing" to "smart manufacturing" can be roughly summarized into four levels or stages: from production to production Start with automation, go to factory digitization, then "cross-border" interconnection and collaboration, and finally realize "high-level" intelligence.

I. Production automation

Focus on the process improvement and production line upgrade at the production site, from process automation, production line automation to gradually realizing the automation of the entire factory.

The work at this stage can be further subdivided into rationalization and "labor saving". Recently, CEConline interviewed Advantech, a provider with nearly 40 years of experience in automation product solutions. He Chunsheng, the company's executive director, told CEConline that the so-called rationalization refers to the rationalization and improvement of factory processes and production lines. For example, in the past, due to the abundance of labor in China, when designing a production line, one person usually looked at a process, and it was common to see employees on the on-site assembly line waiting for the end of the previous process. The redesign of the assembly line allows one person to undertake two to three processes at the same time, so that people do not have to wait for the process, which can greatly reduce labor costs.

The focus of rationalization is to realize the rational use of the production site space, make the production space more flexible production capacity, and improve the production efficiency in the unit space.

The second step is to promote the "labor-saving" of production on the basis of rationalization, starting from the automation of equipment, gradually expanding to the entire factory, and continuously realizing the automation of the entire factory. He Chunsheng pointed out that the improvement of rationalization and labor saving can increase the efficiency by 10%-15%. He took Advantech's own factory upgrade as an example. In 2015, Advantech began to gradually introduce automation equipment to promote the intelligent upgrade of its own factory. At that time, the factory had about 2,200 employees. In 2018, after three years of renovation and upgrading, the number of employees in the factory decreased by 2.2%, but the overall output doubled.

II. Factory digitization

Focus on the data collection and preliminary application of various equipment on the production site, realize the visualization of real-time factory data through emerging technologies such as the Internet of Things, and control the production of the factory in real time status; and master the preliminary data analysis ability, and make more accurate decisions and adjustments based on the data.

Building data management, not just collecting all kinds of data, but also relying on data analysis to give full play to the value of enterprise data, so as to release the innovative value contained in the data. Through data management, employees can handle higher-value tasks, and apply data management to improve the operation management of production sites, build an internal data analysis-based operation platform, and improve efficiency and risk management capabilities.

For example, a manufacturing enterprise in transition mentioned the inspection of factory equipment in an interview with "CEConline". The daily work of the inspectors needs to check the equipment and make good equipment. The daily management and maintenance of the Internet of Things technology can replace the previous manual inspection, and the data can be transmitted back from a long distance through the sensor, and the current operating status of all equipment can be grasped in the operation center. In the past, the operation management of factory equipment was usually carried out on a scheduled basis. Now, through the Internet of Things technology, predictive maintenance can be gradually implemented, and the entire life cycle of all equipment can be monitored throughout the entire life cycle. Diagnose, operate intelligently, and carry out predictive analysis on it, identify problems before they occur, formulate preventive maintenance plans in advance, and implement intelligent management of factories to ensure balanced operation of factories and greatly improve factory production efficiency.

III. "Cross-boundary" interconnection and collaboration

Objects begin to expand to the entire factory, the data interconnection between the factory and the entire enterprise, the connection between enterprise production and the outside world, Realize cross-device, cross-system, and cross-enterprise data interconnection, realize collaborative production between internal and external based on data analysis, and realize collaboration between different links.

For example, optimizing the supply chain by establishing an intelligent operation platform. Through the Industrial Internet of Things, manufacturing enterprises can obtain real-time information of the supply chain, connect factories to suppliers, master all aspects of the supply chain, and form a visual closed loop of supply chain management, which can be fed back to the production side in time to reduce risks.

Fourth, "high-level" intelligence

Realize the intelligent manufacturing stage of highly self-decision and autonomous flower such as comprehensive collaborative manufacturing and cloud manufacturing, realize the intelligent operation of the enterprise, and the target rises to The entire multi-value chain realizes continuous innovation of the entire production management system. Through cloud computing, big data, artificial intelligence and other analysis results to drive the independent decision-making and intelligent execution of the entire production process, continuously improve products and increase the intelligence of production, gradually tend to the best independent and intelligent production state, and continuously realize the product quality Customized production and the promotion of "servitization" of manufacturing.

In general, this is a reshaping and upgrading of the entire industrial value chain. Enterprises at different levels or stages have different key transformation and upgrading objects, and the development of each stage is different. It should be carried out on the basis of what has been fully realized in the previous stage. Moreover, no matter what stage it is in, enterprises should start from clarifying their own problems based on their own production sites.