Smart manufacturing leverages data and technology to adapt to changes in real-time—whether those changes are in customer demand, factory conditions, or the supply network. To achieve these goals, smart manufacturing relies on integrated, collaborative systems that use big data and evolving technologies such as cloud computing, AI, and Internet of Things (IoT). 

Standards for smart manufacturing systems help to ensure that enterprises can access low-cost, highly efficient mechanisms to maximize production efficiency, speed up market response, maintain quality and sustainability, and minimize both their resource consumption and impact on the environment.

In 2019, the IEEE Computer Society Smart Manufacturing Standards Committee (IEEE C/SM) was established to create, manage, and promote a new series of standards to define and solve smart manufacturing problems. In their paper, “Toward Smart Manufacturing: Key Technologies and Trends Driving Standardization,” Sha Wei, Yuanye Ma, Ruiqi Li, and Lin Hu describe this effort and the initial set of standards it targeted.

Smart Manufacturing Standards
The IEEE C/SM is responsible for guiding, managing, reviewing, releasing, and disseminating, IEEE smart manufacturing standards. As the paper describes, this committee targets multiple smart manufacturing areas, including the following technologies.

Digital Twins
In the past, industry was focused on and in physical spaces. As digital technologies and virtual places emerged, however, the concept of digital twins was introduced as a pragmatic way to seamlessly integrate physical and virtual spaces to solve real-time optimization challenges.

A digital twin digitizes and simulates physical assets in virtual space. It then connects the two spaces and forms a closed loop, gathering data from physical space and integrating optimizations in virtual space; the digital twin then makes decisions and applies adjustments to the physical space accordingly.

Among the standards activities in this area is P2806, System Architecture of Digital Representation for Physical Objects in Factory Environments. This standardized architecture describes key components, data resources, and basic procedures for digitally representing objects in factories.

Machine Vision
Machine vision uses technology to take measurements and make judgments. This makes possible various manufacturing applications, including automatic inspection, process control, and robot guidance. 

Standards activities in this area include IEEE Standard P2671, “General Requirements of Online Detection Based on Machine Vision in Intelligent Manufacturing” The P2671 standard offers guidelines for data format, data quality, application scenarios, and performance indicators for online detection based on machine vision.

Manufacturing Patterns
Digital transformation and smart manufacturing have enabled a new generation of manufacturing patterns. Among them are those related to mass customization, which helps enterprises more rapidly respond to customer demands while also lowering costs, reducing residual production capacity, filling loopholes, destocking, and deleveraging.

The IEEE P2672 standard “Guide for General Requirements of Mass Customization” seeks to define and describe mass customization. P2672 describes definitions, terminologies, operation procedures, system architectures, key technological requirements, data requirements, and mass customization applications.

Learn More
The IEEE C/SM’s efforts are ongoing, contributing to the growing demands for innovative technology that enhance manufacturing processes and meet customer demands.

You can read more about the roots of the IEEE C/SM’s work in “Toward Smart Manufacturing: Key Technologies and Trends Driving Standardization,” which is available in the IEEE Computer Society Digital Library. For additional information and updates on this crucial standards work, see the IEEE C/SM website.

Toward Smart Manufacturing: Key Technologies and Trends Driving Standardization
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