Stage I: Informatization
Most businesses collect data using manpower, with the following characteristics: poor timeliness; accuracy needs to be improved; simple data types, mostly text, data, audio, and video; single data dimension, primarily result data; largemining site in comparison to the amount of information before the popularity of computers, but cannot be called "big data"; poor data connectivity, the company Internal data silos are extremely common.
The company's IT architecture is mostly IOE, computers are the company's office supplies, and broadband and Wi-Fi are the primary networks used. The goal of informationization is typically to improve the efficiency of a single value chain link, and the typical action is to purchase MES, PLM, ERP, CRM, and other software.
The second stage is the intelligent stage.
Sensors automatically collect and transmit data to mobile terminals. Rich data types, presented in a variety of formats such as text, data, photos, voice, video, object conditions, sales and purchases, payments, and so on; data dimensions are diverse, and the amount of behavioral data [illustration] has increased dramatically; the amount of information has surged several levels, and people have entered the Internet era; data connectivity is strong, and companies are internally connected to data silos.
The company's IT architecture is mostly cloud-based, and its software is mostly SaaS-based. The goal of company digitalization is not only Used minerto improve efficiency, but also to hope that digital technology can participate and reshape multiple links of the value chain, integrate more closely with business, and even change enterprise business models.
Third, intelligent Internet of things stage, sensors all over the world, the Internet of things era is approaching. The data level will continue to rise, the amount of IoT information will far outnumber non-IoT data, and the data dimension will remain diverse. Valley ware offers comprehensive MES, SRM, WMS, company data center, smart factory, and digital factory solutions.
Building a digital twin entails creating data models and physical entities that can be projected interactively and synchronously in webbitmain space to complete the combination of digital and physical worlds. The digital twin can recognize, diagnose, and predict the state of physical entities, thereby improving and evolving their data models. It has the potential to improve the operational efficiency of a wide range of industries.