Industrial internet-of-things platform

Abstract

Disclosed in the application is an industrial internet-of-things platform comprising a raw material data acquisition and management system, a production data collection and management system, a sales data acquisition and management system, a storage data acquisition and management system, an equipment material data acquisition, and a quality control tracing collection and management system. The raw material data acquisition and management system consists of a sample extraction report generation module, an initial review report generation module, a recheck report generation module, a raw material warehousing report generation module, and a settlement report generation module. The production data collection and management system includes a raw material link data generation module, a production link data generation module, a finished product package link data generation module, and a finished product link data generation module. The sales data acquisition and management system contains a cargo data management module, a sales contract management module, and a customer data management module.

Description

technical field [0001] This application relates to an industrial internet of things platform, which belongs to the cross-technical field of industrial automatic identification and data acquisition. Background technique [0002] The Industrial Internet of Things platform is an industrial Internet of Things management system, relying on Internet of Things, cloud computing, big data and other technologies, with the most advanced domestic industrial automatic identification and data collection technology (AIDC technology) as the core, it is a set of industrial automatic identification, An intelligent management platform integrating information collection, data modeling, and process reengineering. [0003] At present, enterprises are paying more and more attention to informatization construction, but there are many problems and deficiencies in the existing enterprise information management system. The physical flow and information flow of enterprises are out of touch, and the dev...

AI Technical Summary

Problems solved by technology

[0004] 1. The connection between the enterprise information system and the actual workflow is quite problematic, the lack of automatic data collection capabilities, and the inefficiency of various production process data collection methods

All data collection relies on manual labor, and there are tedious tasks such as paper documents, handwritten statistics, and checks in all departments, and there are prominent problems such as information delay, high cost, low accuracy, low labor efficiency, and employee boredom

[0005] 2. There is a lack of scientific and effective information management of production equipment, and there are big problems in the operation and maintenance management system of production equipment in enterprises. The management methods of production equipment and spare parts are backward, and the management of production equipment in most enterprises is manually recorded and entered into the system; Extensive management leads to waste of working hours; inspection management is difficult to implement and supervise, and the frequency and time of production equipment inspections are difficult to implement as required; equipment inspection information lags behind, resulting in waste of maintenance costs; equipment maintenance and repair records are all recorded manually and manual input system, the amount of information is large and the waste of non-production man-hours

[0006] 3. At present, there are still many deficiencies in the logistics management system of most traditional enterprises, especially in the establishment of warehousing mode and warehousing management are still in the manual operation management stage

The data in and out of the warehouse needs to be entered manually, which reduces work efficiency, and causes the data in and out of the warehouse to not be updated in time and the data is inaccurate

The lag of information makes it difficult to take inventory of spare parts

The identification of spare parts still relies on experience. Effective storage location management has not been realized in system management, and the storage capacity of the warehouse and t

Images