Featured Image

Semantic Data in Digital Manufacturing

Semantic data models are an information systems technology that has been finding its way into the manufacturing world to address many of the issues, costs, and complexities associated with the configuration process. The models are used to enhance data...
by AMT
Nov 30, 2020

Semantic data models are an information systems technology that has been finding its way into the manufacturing world to address many of the issues, costs, and complexities associated with the configuration process. The models are used to enhance data produced from shop floor equipment and other manufacturing processes by incorporating information (semantics) so that a software system can read the data and fully understand its meaning and how each piece of data relates to the manufacturing process. Semantic data models are not a new technology, and the application of semantic data models to manufacturing processes has been evolving over the past 10-15 years.

The traditional method for collecting and managing manufacturing data involves retrieving raw data from shop floor equipment and then processing each piece of data through a configuration process to transform that data into useful information for further processing by software applications. Once configured, the transformation process itself is automatic. However, the configuration process that defines the rules for the transformation is a significant issue in most software systems.

There are a number of semantic data models defined for a wide variety of different types of industrial equipment, facilities management, and other manufacturing processes. AMT has been leading the effort to develop a semantic data model focused on discrete parts manufacturing equipment and processes with its MTConnect standard. MTConnect provides the definitions for describing manufacturing data in a common format so that the shop floor no longer appears as a “sea of babble.” All information is provided in an orderly fashion and communicated with a common language. MTConnect helps to lower integration costs for deploying software solutions in manufacturing, enables equipment to publish more valuable and useful data, and in the end, enables better and expanded “data-driven” management processes.

The potential impact of semantic data on the future of digital manufacturing is significant. Its benefits include: reduction in the level of expertise required to deploy software solutions; reduction in the time and expense to deploy a software tool; more analytic tools focused specifically on manufacturing operations; cooperation between standards groups which creates standardized solutions for exchanging data between different environments – shop floor, quality, planning and scheduling, maintenance, etc.; and flexibility to scale a digital manufacturing solution to the unique requirements of every manufacturing operation.

Yet the adoption of semantic data models by suppliers of industrial software applications has been slow. There are two issues impacting the rate of adoption. From a technical perspective, most communication protocols used by industrial equipment to publish data do not support semantics, and the changes to support semantic data require significant resources. From a commercial perspective, software suppliers and their implementation partners derive significant revenue from developing the custom configuration required to deploy the software application. Semantics remove much of this configuration process and therefore the associated revenue. It is up to each company, as a member of the manufacturing industry, to encourage the rate of adoption of semantics in digital manufacturing – for the benefit of all.

To learn more about Semantic Data Models read the white paper here.

PicturePicture
Author
AMT
AMT – The Association For Manufacturing Technology represents and promotes U.S.-based manufacturing technology and its members – those who design, bui ...
Recent technology News
When it comes to digital twins and digital threads, there is no widespread agreement what they are and how the can be expressed in terms of data artifacts. This presentation proposes a standards-based definitions...
NSF’s mission is to promote the progress of science to advance national health, prosperity and welfare. To fulfil this mission, the ENG directorate invests in engineering research and education to foster innovations for the benefit of society.
Additive subtracts costs. Implementing automation and the details that aren’t automatically addressed. The machine vision community offers some clarity on future challenges and more. Recycling powder for additive. Standards make the digital twin real.
In his presentation “Manufacturing Digital Twins: Understanding Digital Twins and How Standards Can Enable Them,” Jan de Nijs, LM Fellow for Enterprise Digital Production, Lockheed Martin, reviews the formal definition of the digital twin...
Blockchain enables a secure digital twin. The underlying components are secure real-time data streams through blockchain security, predictive failure, object detection, 3d models, process analytics, and remote operations.
Similar News
undefined
Intelligence
By Jonathan Nguyen | Nov 13, 2020

U.S. machine tool exports valued $118.41 million in August, up 25.8% from July’s total of $94.12 million. Exports for year-to-date 2020 totaled $917.75 million, a decrease of 28.0% when compared to the same period for 2019. Monthly machine tool imports...

1 min
undefined
Intelligence
By Christopher Downs | Nov 09, 2020

Last month, manufacturing executives from around the country attended the virtual MTForecast conference which brought together nationally recognized economists and industry analysts – as well as machine tool forecasts and industry outlooks for...

1 min
undefined
Technology
By External Contributor | Sep 02, 2020

As organizations continue to see the value in industrial analytics, making sense of the sheer amount of data produced can be a difficult task. Finding the right product and developing a proper workflow is important to get long-term use out of the system...

7 min