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Alternative vs. Composition Dataset Mapping
Alternative vs. Composition Dataset Mapping

What is the difference between 'Alternative' and 'Composition' mapping when importing a BOM

A
Written by Alex Inglis
Updated over a week ago

Introduction

When importing a BOM into Makersite there is an option to set each mapped dataset as either 'Alternative' or 'Composition'.

The option is toggled by clicking on the 'Alternative' (Red) or 'Composition' (Yellow) button next to the dataset name on the import page.

'Alternative' is selected by default for newly imported data.

Alternative

Mapping a dataset as an Alternative is the most common type of mapping in Makersite, this links or 'maps' an imported dataset directly to an existing Makersite dataset, like for like. This means, when any results are calculated for the imported dataset, Makersite will use the mapped Alternative.

For example:

Imported Dataset Makersite Dataset

Polypropylene = Polypropylene Injection Moulding

Capacitor 1 = Capacitor X5R

Power Cable = Generic Power Cable

It is also possible to map an imported dataset to multiple Alternatives, if this is the case a 'Preferred Route' is set which acts as the default option for calculating results.

Composition

A dataset mapped as a Composition is used when an imported dataset will be composed of multiple Makersite datasets to make up the whole material, substance or product being imported. The Product Group is 'made from' the datasets mapped to it.

For example:

Steel is made up of multiple different elements, so to import Steel into your model you would set the dataset to Composition and map all of the separate elements that Steel contains.

Imported Dataset Makersite Datasets

Steel = Chromium + Nickel + Manganese + Silicon + Iron

Alternatively, if a Pen was imported as a single dataset, it would contain multiple components.

Imported Dataset Makersite Datasets

Pen = Cap + Barrel + Ink etc.

Automatic mapping to datasets in Makersite is prioritized by GUID, CAS and Composition in this order to build the dataset.

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