FDM vs. MJF vs. SLS vs. SLA: A Practical Comparison for Engineers

AAM Navigator Team · Process Engineering August 5, 2026 8 min read

Picking a technology before picking a material is often the wrong order of operations — but in practice, most teams have a process constraint (an in-house printer, a qualified supplier) before they start the material conversation. This post compares four of the most common processes on the dimensions that actually decide whether a part succeeds: FDM, MJF, SLS, and SLA.

FDM (Fused Deposition Modeling)

FDM extrudes a molten thermoplastic filament layer by layer. It is the most accessible and lowest-cost process on this list, with the widest range of engineering-grade materials available (ABS, PETG, ASA, nylon, polycarbonate, and high-performance options like PEEK and ULTEM on industrial machines).

Strengths: lowest cost per part at low volume, widest material range including high-temperature engineering polymers, no post-processing required for functional parts.
Weaknesses: the most pronounced anisotropy of the four processes — Z-axis strength is often 50-70% of XY strength. Visible layer lines mean surface finish typically requires post-processing for cosmetic applications.
Best fit: prototypes, jigs and fixtures, low-volume functional parts where load direction can be controlled by print orientation.

SLS (Selective Laser Sintering)

SLS uses a laser to sinter powdered polymer (most commonly PA11 or PA12 nylon) layer by layer, with the surrounding unsintered powder acting as built-in support. That self-supporting nature is the process's biggest structural advantage.

Strengths: no support structures needed, which enables complex geometry and nested build packing for good production economics. Mechanical properties are far more isotropic than FDM.
Weaknesses: surface finish is naturally matte/grainy (fine for most industrial parts, often not for cosmetic ones). Powder handling and post-processing infrastructure is a real operational commitment.
Best fit: functional end-use parts, especially where geometric complexity would make tooling-based manufacturing impractical.

MJF (Multi Jet Fusion)

MJF, HP's powder-bed process, jets a fusing agent across a powder bed and applies heat/energy to fuse an entire layer at once rather than tracing it with a laser. That parallel fusing is the source of its main advantage: throughput.

Strengths: significantly faster build times than SLS at comparable quality, good mechanical isotropy, competitive surface finish, no support structures.
Weaknesses: material range is narrower than FDM (PA11/PA12 and a small number of TPU and PP options dominate). Machine and material costs are on the higher end of this list.
Best fit: production-volume functional parts where throughput and consistency matter as much as individual-part properties — the archetypal "bridge production" and increasingly true low-volume-production use case.

SLA (Stereolithography) / Resin

SLA cures liquid photopolymer resin with a UV laser or projector, layer by layer. It is the process most people associate with extremely fine detail and smooth surface finish.

Strengths: the best dimensional accuracy and surface finish of the four, by a wide margin — ideal for fit-check prototypes, master patterns, and cosmetic models.
Weaknesses: standard resins are typically more brittle than the nylon-based options above, and many resins degrade under UV/thermal exposure over time unless specifically formulated for durability. Requires wash-and-cure post-processing.
Best fit: high-fidelity prototypes, presentation models, dental/jewelry applications, and increasingly, engineering resins for functional low-load parts.

Choosing between them

In practice, the decision usually comes down to three questions in this order: does the application require isotropic strength (rules out FDM for structural parts), does it need production-representative surface finish out of the machine (favors MJF or SLA), and what volume and cost-per-part are you targeting (FDM and SLS scale down more gracefully to low volumes; MJF's economics improve with volume).

Common mistake

Choosing a process based on what a team already owns rather than what the application needs. It's a reasonable starting constraint, but validate against the six selection dimensions before committing — the cost of requalifying on a better-fit process later is almost always higher than the cost of a proper evaluation up front.

AM Navigator's catalog spans all four of these processes (plus SLA, DMLS, DLS, CFF, and BMD) so a technology comparison like this one can be run against live datasheet data for your specific application, not general rules of thumb.