The world is promoting the deep integration of information technology and manufacturing technology in digitization, networking, and intelligence, and many enterprises are planning to build smart factories. As is well known, the planning and construction of smart factories is a very complex system engineering, so how to "simplify" the construction of smart factories? Perhaps we can provide a brief explanation from two aspects.
A major core element to consider in construction and a key dimension to focus on is data collection and management. Data is the blood of smart factory construction, flowing between various application systems. During the operation of a smart factory, business data such as design, process, manufacturing, warehousing, logistics, quality, personnel, etc. may be generated, which may come from application systems such as ERP, MES, APS, WMS, QIS, etc.
During the production process, it is necessary to timely collect data on output, quality, energy consumption, processing accuracy, and equipment status, and associate them with orders, processes, and personnel to achieve full traceability of the production process. In addition, in the construction process of smart factories, it is necessary to establish data management standards to ensure data consistency and accuracy. When necessary, a dedicated data management department should also be established to clarify the principles and construction methods of data management, establish data management processes and systems, coordinate the problems in implementation, and regularly inspect the implementation of technical standards, processes, and execution of optimized data management.
In addition, production quality management and equipment management are also the core business processes of smart factory construction. Equipment is a production factor, and maximizing its effectiveness is a fundamental requirement for smart factory production management. The production management information system needs to set up a device management module to release ****** production capacity, and through reasonable production arrangements, reduce waiting time for equipment, especially critical and bottleneck equipment. Implementing the concept that quality is designed and produced, not inspected. Quality control needs to be embedded in the production mainstream process in the information system, such as inspection and testing being processed as processes or steps in production orders; The process, forms, data, and production orders of quality control are interrelated and penetrated.
In the equipment management module, it is necessary to establish various equipment databases, set codes, and timely maintain the equipment; Provide equipment capability data for production scheduling through real-time collection of equipment status data. In addition, establish a health management file for equipment, establish a fault prediction model based on accumulated equipment operation data, and perform predictive maintenance to minimize unplanned downtime of equipment and manage spare parts for equipment.
Many cutting-edge enterprises in the SMT field have released a series of smart factory solutions along this line of thought.
For example, ASM (E2 Hall 2534, 2020 Shanghai Electronic Production Equipment Exhibition, Munich) recently showcased a new generation of ASM Material Tower and innovative products such as ASM AutoRefill Feeder at the productronica in Munich, Germany. In order to coordinate and integrate personnel, machines, materials, and processes in a smart factory, ASM provides a series of innovative software combinations, such as ASM
