Energy Efficiency in FDM 3D Printing

Seventy percent of FDM energy goes to the heated bed, but adjusting processing parameters can cut this waste in half while maintaining part strength and surface quality.

Fused Deposition Modeling (FDM) is synonymous with flexibility and cost-effectiveness in the 3D printing sector. However, as industries shift toward sustainable manufacturing, the energy footprint of even small-scale additive processes has come under scrutiny. Recent research led by Zakaria and Mativenga provides a robust scientific framework for optimizing FDM by targeting three often-conflicting objectives: energy consumption, mechanical strength, and surface quality. Their results show that sustainability in 3D printing does not have to mean compromising on performance if there is an appropriate selection of the process parameters.

You can also read: Cutting Emissions Using PLA in 3D Printing

Rethinking the Heated Bed: A Hidden Energy Sink

The study’s most eye-opening finding is that up to 70% of total energy consumption in FDM comes from one component: the heated bed. While nozzle heating and motor movement do contribute to power usage, the sustained energy demand to maintain bed temperature dominated the energy profile, even in an industrial-grade printer.

By conducting precise thermal analysis, the authors identified an appropriate strategy: set the bed temperature to approximately 11.5°C below the material’s glass transition temperature. For PLA, this meant printing at around 50°C rather than the conventional 60°C, without compromising part adhesion or dimensional stability.

This adjustment alone can reduce energy consumption by nearly 50%, pointing to a significant opportunity for system redesign and smart heating strategies.

Maximizing Mechanical Strenght

Energy savings have functional significance only when the process preserves part performance. To evaluate this, the researchers fabricated ASTM D638 Type I tensile specimens from PLA and conducted tensile testing across multiple parameters sets to assess mechanical strength.

Interestingly, the highest tensile strength (53.3 MPa) did not come from the most energy-intensive settings. Rather, it came from a setup using:

• A nozzle temperature of 210°C

• A low layer thickness (0.15 mm)
• 100% infill
• A +45°/–45° raster angle

However, when prioritizing energy efficiency, an optimized configuration emerged: a layer thickness of 0.35 mm combined with a print speed of 40 mm/s. This configuration maintained tensile strength above 50 MPa while cutting energy use by 72% compared to the worst-case scenario.

These findings confirm that optimized parameters can achieve energy savings and preserve mechanical properties.

Surface Quality: An Overlooked Sustainability Metric

While many treat surface roughness as a post-processing issue, the study demonstrates that smoother parts cut material waste, enhance performance, and reduce total energy consumption by minimizing finishing requirements.

Among the seven tested parameters, the number of outer shells had the strongest effect on surface finish. A higher shell count (4 vs. 2) consistently reduced average surface roughness, with the smoothest sample recording Ra = 1.07 µm.

Layer thickness and nozzle temperature were critical parameters in the process. Increasing layer thickness improved deposition efficiency and reduced build time but elevated surface roughness. A higher nozzle temperature counteracted this effect by reducing melt viscosity and enhancing material flow dynamics.

Ultimately, the study identified an ideal surface quality profile using:

• 210°C nozzle temperature.
• 0.15 mm layer thickness.
• 100% infill.
• Four outer shells.

This configuration gave excellent surface finish without significantly increasing energy consumption.

Multivariate Optimization

Rather than testing thousands of combinations, the authors used a Taguchi Design of Experiments (L8 array) to isolate the influence of seven parameters. This allowed them to identify dominant variables and their interactions efficiently.

From the analysis, some parameters emerged as the primary levers for energy efficiency and product quality.

Energy efficiency:

1. Layer thickness – 46% contribution to energy consumption.
2. Print speed – 41% contribution.
3. Bed temperature – 12% contribution.

Tensile strength:

1. Infill density – 40–50% contribution.
2. Nozzle temperature – 23–25%.
3. Layer thickness – 14–15%.

Surface roughness:

1. Number of shells – ~50% contribution,

This statistical precision enables manufacturers to optimize part design and process planning by focusing on critical parameters, whether the objective is maximizing mechanical performance, enhancing aesthetic quality, or minimizing emissions.

From Energy Use to Carbon Impact

Using UK carbon intensity benchmarks, the study translated power savings into environmental impact. Optimized settings reduced Scope 2 emissions by 72%, cutting per-part emissions from 0.051 kg CO₂e to just 0.014 kg CO₂e. In a production context, this is a powerful argument for parameter optimization not only in the context of cost reduction, but also for carbon accountability.

Takeaways for the Plastics Industry

This work calls for redefining printer design, especially heated beds, and encourages material manufacturers to provide thermal response data like glass transition temperature and melting temperature up front. More importantly, it shows that energy efficiency in FDM is not a trade-off with performance but a design opportunity.

As demand for sustainable prototyping and short-run production grows, plastics manufacturers, service bureaus, and machine builders must embrace this kind of evidence-based optimization to remain competitive, and climate-conscious.