No matter the size of which industrial enterprise, it has the ambition to become a "lighthouse factory", which is the embodiment of realizing the self-worth of the enterprise, and it is also the result of the strategic layout of an entrepreneur.
I believe that you have heard of sweatshops, smart factories, smart factories, digital factories, but the frequency of lighthouse factories is still relatively small, lighthouse factories are jointly selected by the World Economic Forum and McKinsey Consulting, it is a model of digital factories, the leader of Industry 4.0, it already has the necessary characteristics of the fourth industrial revolution, such as automation, industrial Internet of Things (IIOT), digitalization, big data analysis, the fifth generation of mobile communication technology (5G) and other technologies. They are not necessarily super large, varying in size, and even some are not necessarily fully automated, or do not use machines to replace workers, but focus on developing and implementing cost reduction and efficiency increase strategies, and technologically or institutionally achieve efficient advanced factories.
If the manufacturing industry wants to become a lighthouse factory, in addition to digitalization, informatization and automation, it is also one of the necessary conditions to be able to analyze the industrial big data generated by itself.
The industrial manufacturing industry that realizes digitalization has gradually begun to pay attention to the big data generated by itself, and industrial big data is a large amount of data generated by industrial equipment at high speed, corresponding to the state of the equipment at different times, which is the information in the Internet of Things. Industrial big data refers to the general term for various types of data and related technologies and applications generated in the industrial field, around the typical intelligent manufacturing model, from customer demand to sales, orders, plans, research and development, design, process, manufacturing, procurement, supply, inventory, delivery and delivery, after-sales service, operation and maintenance, scrap or recycling and remanufacturing.
The most commonly used data acquisition system in China is the SCADA system, through the Internet of Things technology, the operation of equipment and instruments in the production process, product information, personnel information, energy situation... And so on, can be collected, screened, analyzed, stored and displayed through the SCADA system. Compared with foreign industrial software companies, domestic SCADA configuration software can also compete.
The application of industrial big data is an important starting point for promoting industrial transformation and upgrading, and as a new production factor resource, industrial big data supports supply-side structural reform and drives the transformation and upgrading of the manufacturing industry, and is becoming a new engine to promote quality change, efficiency change and power change. The value of industrial big data has been generally recognized by enterprises, the scale of industrial big data reserves and industrial scale will continue to rise, the degree of specialization and intelligence is higher, the scale of industrial big data market continues to grow, and the development prospects of the industrial big data market are broad, which will drive a series of new industrial structures.
1, improve operational efficiency: in a network system to achieve interconnection of various equipment or machines, through the Internet to cooperate with each other, improve the overall operational efficiency of the network. In the digital factory, the operating data of each device can be clearly displayed, and when there is a problem or a faulty person, machine, environment, it can quickly appear to the location of the problem, and allows for optimized routing to find the most effective AI solution.
2, reduce costs: through industrial big data can achieve optimization, low cost, and is conducive to the operation and maintenance of the entire equipment or machine. For example, after the production equipment and parts are networked, a monitorable production status will be realized, the optimal number of parts can be delivered to the exact location at the right time, the parts inventory requirements and maintenance costs will be reduced, and the stability of the equipment or machine will be improved.
3, stable intelligence: by establishing a wide range of big data information, it can help the network system to recover more quickly and effectively after a devastating blow. When encountering an emergency, the big data system of the digital factory will play a good guiding role, according to the data information, it can independently restore the system, and can repair the damaged system, and realize the intelligence of the whole process. The operating experience of each plant or machine can be aggregated into one big data, enabling the entire plant or machine to learn on its own. Self-learning data will continue to feed back into big data systems, and the entire digital factory operation will become more and more intelligent.