solutions for industrial Internet data processing and portable digital infrastructure
The industrial Internet, a byproduct of Bentley Microstation the deep integration of information technology and the industrial economy, has been fostering the m...
The industrial Internet, a byproduct of Bentley Microstation the deep integration of information technology and the industrial economy, has been fostering the manufacturing sector's rapid expansion since its inception. The industrial Internet has grown to play a significant role in the digital transformation of industrial organizations by connecting industrial equipment to the cloud and the Internet and enabling intelligent chain cooperation.
Digital communication equipment makes up the perception layer and CDE Solution provider the control layer of the "transmission link" between the bottom layer of the industrial Internet in order to realize all of its components, the entire industrial chain, and the entire value chain of the comprehensive connection, which is inseparable from the collection and transmission of data in all aspects of the industry. The only approach to fully activate the production vitality and support manufacturing businesses' digital transformation and development is to open the data islands and link the equipment network as much as feasible.
Data Management Challenges
A brand-new challenge for CDE solution conventional manufacturing firms is using data as a new production component into the production and operation activities of enterprises and developing new forms of company.
Problem 1: Complicated data processing
Manufacturing companies have a lengthy and complicated chain that connects production with sales; although data precipitation occurs, the linkages are dispersed among several systems. As a result, integrating and cleaning the data during analysis and processing takes a lot of time, and data loss may also be an issue. Data redundancy is a major barrier to company productivity because of the lower degree of data control and quality.
Difficulty 2: Data application challenges
A lot of businesses are still mired in data collection, processing, statistics, and comparison. They haven't combined data analysis techniques with real-world business scenarios decision-making, processes, or practice cases for data application. This is because the digital transformation of manufacturing enterprises is still in the exploration and development stage.
3rd difficulty: Data realization is difficult
Enterprise digital transformation ultimately needs to be put into place to improve the capacity of personnel and transformation, with data, data analysis, data mining, and corporate decision-making needing to be completed by people. Undertake enterprise digital empowerment departments are primarily middle and back-office departments, and the majority of the employees based on data innovation and refinement of the operational capacity is difficult to be fully activated.
Solutions
Business generates data, which will eventually feed business. Through years of ongoing self-research, Hambold has developed four core products (MES, QMS, DAMS, and WMS) that are sufficient to support intelligent manufacturing. We have also perfected the construction of the system based on the actual needs of the business by taking the onlineization, digitization, and intellectualization of the business application scenarios as the entitl We boost the digitization level of staff, precipitate and integrate data, create data application scenarios, and optimize system building based on the actual company demands.
Hanbold's intelligent manufacturing products are capable of offering a complete end-to-end integrated solution, covering everything from the development of the lowest data control layer up to the development of the data management layer (which primarily includes enterprise data architecture, data standard management, data quality management, metadata management, master data management, etc.).
Automation of Data Acquisition
utilizing technology methods, achieve automatic data gathering from instruments and meters, increase operational effectiveness, and avoid data distortion;
Data Point of View
reviewing financial data in each area of company and implementing accurate real-time data management, that is, gathering data and status updates all the way from taking orders to producing finished goods;
Intelligent Data Analysis Utilization
Making use of data analysis tools and algorithms to analyze high-quality data and use it for intelligent decision-making, intelligent correction, and intelligent prompting.
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