GB/T 42137-2022 in English
VALIDGuidelines for intelligent manufacturing capability construction for discrete industry
- Issued on:2022-12-30
- Implemented on:2023-07-01
- File Format:PDF
- Delivery:Via email within 1~3 business days
$117.00
《GB/T 42137-2022离散型智能制造能力建设指南》由339-1（工业和信息化部（电子））归口，主管部门为工业和信息化部（电子）。
Introduction
1. Background of standard formulation
With the rapid development of Industry 4.0 and intelligent manufacturing, discrete manufacturing enterprises are increasingly in need of intelligent transformation. This standard is based on GB/T39116-2020 "Intelligent Manufacturing Capability Maturity Model" and GB/T39117-2020 "Intelligent Manufacturing Capability Maturity Assessment Method", and aims to provide systematic construction guidance for enterprises.
2. Overall approach to intelligent manufacturing capability construction
| Steps | Specific content | Implementation suggestions |
|---|---|---|
| Confirmation basis | Apply GB/T39116-2020 and GB/T39117-2020 to complete the confirmation of intelligent manufacturing capability basis. | It is recommended that enterprises first conduct a status quo assessment to clarify the stage they are in. |
| Clear goals | Develop construction goals in combination with the enterprise development strategy and existing capabilities. | It is recommended to set short-term, medium-term and long-term goals and ensure that they are consistent with the enterprise strategy. |
| Develop a route | Select a suitable improvement path from the two dimensions of life cycle and system level. | It is recommended to select a suitable technical route based on the characteristics and scale of the industry and implement it in stages. |
3. Capacity building in the life cycle dimension
Data collection capabilities:According to different scenarios, methods such as three-dimensional digital models, RFID and barcode technologies are used.
Interconnection capability:Achieve through a unified product data management system and an integrated workshop-level manufacturing execution management platform.
Data visualization capability:Establish a product design interactive platform and virtual model, and use digital modeling methods for visualization management.
Data analysis capability:Improve the analysis level by using parametric model databases, simulation optimization technology, and energy integrated management platforms.
Optimization decision-making capability:Establish a dynamic optimization model and collaborative optimization mechanism to maximize overall benefits and dynamically optimize the supply chain.
4. Capacity building at the system level
| Level | Construction method | Technical means |
|---|---|---|
| Device level | Data collection based on the device host system or the installation of sensors. | Industrial Ethernet, Internet of Things (IoT), edge computing technology, etc. |
| Unit level | Status data collection using RFID, barcode and fieldbus technologies. | PLC control system, industrial communication protocol technology, etc. |
| Workshop level | Data collection using Industrial Ethernet, Internet of Things and Manufacturing Execution System (MES). | Digital twins, data analysis technology, etc. |
5. Implementation suggestions
Step-by-step implementation: From the equipment layer to the collaboration layer, gradually promote intelligent transformation.
Technology selection: Select appropriate technical solutions based on the scale of the enterprise and the characteristics of the industry.
Continuous optimization: Regularly evaluate the construction effect and make adjustments and optimizations.
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