Concept: Data model

Definition

A  data model is a structured representation of a (physical) product. Its level of detail and complexity depend on the product and on requirements from a design and/or manufacturing perspective. In the KE-chain application, a data model consists of combinations of two principal components: part models and properties. Conceptually, the data model is closest to a Product Breakdown Structure.

Still not clear?

Read more regarding data modeling on this Wikipedia article.

Example of a data model: Office building

Examples of data models can be found everywhere in our day to day lives. In the figure below, an example of a data model called "Office building" is presented. An office consists of multiple rooms. These rooms are the sub-parts of the office. Similarly, the room can contain multiple desks, which in turn consist of a top and legs. The number of sub-parts is defined by its quantity. For example, the building consists of at least 1, but possibly multiple rooms. Therefore, its quantity is defined as 1 or more in the data model tree. By the same logic, we specify that each room can have 0 or more desks, with each desk having exactly 1 top and 1 or more legs.

How is it related to the product?

This "Office building" data model is linked to an example product called "Yes!Delft incubator". Check out how they are connected by reading the Concept: Explorer page.

What are quantities?

Read more about how to define them in the Concept: Part page.

Relation to existing data model breakdown

The KE-chain way of breaking down a data or product model (its ontology) is related to common standards such as STEP. While STEP itself is has a broad scope and is extensive, the KE-chain way of data modeling is more down-to-earth and easier to understand. The following picture (taken from here) shows how the KE-chain data model maps onto a basic product ontology.