Jeanologia Expands EIM to Measure Environmental Impact from Yarn to Garment
New EIM modules for yarn, fabric and garment finishing aim to connect production data under a common methodology
Jeanologia has expanded its Environmental Impact Measuring (EIM) methodology to cover multiple stages of textile production, extending its scope from garment finishing to yarn, fabric and finished garments.
The updated EIM introduces dedicated modules for yarn, fabric and garment finishing. By connecting the results through a common methodology, the system is designed to provide an integrated view of a textile product’s environmental impact, including water, energy and chemicals use.
EIM Expands Beyond Garment Finishing
EIM was developed by Jeanologia more than 15 years ago to measure the environmental impact of garment finishing processes. The latest development expands the methodology to different production stages and types of textile products.
The new system includes three independent modules:
- Yarn Module: Measures yarn production processes.
- Fabric Module: Covers fabric production.
- Garment Finishing Module: Measures the finishing stage of garments.
Each module can be used independently to assess a specific production stage. EIM+ connects the results from these modules to provide a broader view of the product and its production impact.
The expanded methodology allows EIM to be applied beyond its historical association with denim and garment finishing, covering textile products from yarn through to finished garments.
Measuring Water, Energy and Chemicals
EIM evaluates environmental impact across water, energy and chemicals. At the garment-finishing stage, it also assesses worker impact.
Using a common methodology, EIM classifies environmental performance into three categories: low, medium or high impact. According to Jeanologia, this classification is intended to make results easier to understand and compare.
Production Data Designed for Traceability
The updated EIM uses primary data collected directly from production processes. The information is structured using a common methodology to support consistency and comparability between different stages.
Data generated through the system can be connected across the production chain while maintaining traceability. The resulting information is also structured for applications including Life Cycle Assessment (LCA) and Digital Product Passports (DPP).
This approach is intended to allow environmental information generated during manufacturing to remain connected to the product as it moves through different stages of the supply chain.
With requirements for environmental information and traceability increasing, the system provides brands and manufacturers with structured production data rather than requiring environmental impacts to be reconstructed from fragmented information across the supply chain.