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Standardized Machine Readable Information Models
Module developed by ingenjör5.0

Standardized Machine Readable Information Models

Starting date: Autumn 2026
Price: 4 995 SEK ex. vat

This module walks through an example using one of the standards covered in the previous module

Overview

The module Standardized machine readable information models is the second module following the module on Interoperability and standards in digitized industry.

This module requires some background knowledge and is therefore merged with the content of the module on Interoperability and standards in digitized industry.

The module Standardized machine readable information models will walk through an example using a one of the standards covered in the previous module, for the exchange of product information. This module will be hands on and software and data will be used to understand what type of information content can be used and how it is represented using the selected standard. Also, the example is focusing on one selected standard, but the content being represented by this standard will also be possible to be exchanged and use other standards. Further, relations to other standards will be high-lighted, for example using the selected standard will show that different parts of the information is managed by other standards. One such example is the Reference designation information. Another example is the external classification and property (units and measure).

Below is a description of the previous module: Interoperability and standards in digitized industry

The module on Interoperability and standards in digitized industry will give an understanding of how standards enable interoperability, in the sense that information should flow seamlessly between the computer systems and services in a connected system. Many different standards exist and are in development for the digitized industry. However, it is difficult to know which standard to use, and how to use it, without prior knowledge and experience. The module on Interoperability and standards in digitized industry provides an overview of existing standards and the standard bodies and communities that are of relevance to smart industry.

A selection of the most relevant standards will be presented to give an understanding of the scope, content and intended use of the information models of those standards.

The different types of computer systems used in smart industry and how they relate to the relevant standards will also be presented. Examples of types of computer systems, or applications, used are CAD, CAM, CAPP, PDM/PLM, ERP, MES, and maintenance management.

Time commitment

To complete this module, the participant is expected to schedule approximately 4 hours per week over 5 weeks (20 hours in total).

The schedule
Starting date: Autumn 2026
TBD — Webinar 1
TBD — Webinar 2
TBD — Webinar 3
TBD — Webinar 4
Learning objectives
Understand the main conceptual and technological landscapes of Industry 4.0.
Understand some of the human implications and reach of potential Industry 4.0 developments.
Understand some of the main design and technical principles and directions to be considered during the implementation of Industry 4.0 systems.
Module structure
  • This module will make some re-cap on the relevant sections of the first module.
  • A selected standard (AutomationML) will be used as a case study with example data.
  • Software and data will be used to get an understanding of how relevant product data is represented using the standard.
  • Self-study and recommended readings to background material, exercises, reflections that you share with other participants, webinars for cross-participant discussions
Targeted participants

Mechanical, Production and Automation Engineers.

Engineers and practitioners with with an Industrial Background.

Computer Scientists with an interest in understanding Industry 4.0 from an applied computer science perspective.

More importantly everyone with a genuine interest in the digital information management aspects for smart industry.

Content
A unique module created in co-operation between academic partners
Related Learning Area
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