Allen-Bradley CompactLogix vs Omron Sysmac NX1P2: Sizing by Real Watts per Application Cycle

comparison · teardown Allen-Bradley (host) Omron PLC (rival) real watts / cycle

You’re staring at two controllers: one draws 8.5 W under load, the other maybe 6 W. But those numbers alone don’t tell you which one will heat your cabinet more, or which one leaves room for future axes. This teardown follows the magnitude proportion of power dissipation against what each controller actually delivers per scan cycle, so you can size a panel without guessing.

1. Power Dissipation Per Scan – the Real Heat Density

Start with the raw numbers: an Allen-Bradley PLC CompactLogix 5380 (5069-L306ER) dissipates max 8.5 W (thermal dissipation ~29 BTU/hr). An Omron NX1P2-9024DT, by comparison, draws roughly 6 W under typical load (derived from its 24 V DC input at ~250 mA; illustrative). But these are static ratings. The relevant proportion emerges when you factor scan time.

The CompactLogix 5380 executes a typical mixed-logic scan in about 1–2 ms (roughly 0.6 MB user memory, 1 Gbps backplane). The NX1P2 primary task cycle is as low as 2 ms at full program load. Per millisecond of scan, the CompactLogix dissipates ~4.25 W/ms; the NX1P2 ~3 W/ms. Mechanism: a faster backplane and integrated motion on EtherNet/IP (CompactLogix handles up to 32 axes) demand more instantaneous current per cycle. The Omron PLC, with only 4 PTP axes at 2 ms, has a proportionally lighter electrical load per scan.

Worked consequence: if you run a 2 ms control loop with 20 % overhead, the CompactLogix will contribute about 1.7 W of continuous heat above the Omron inside a 16 × 14 in. panel. That’s not panel-killing, but it shifts the cabinet thermal budget by roughly 5 % – enough to need a larger vent or a low-speed fan.

Where this flips: if your application runs at 10 ms cycle (batch processes or material handling), the per‑ms difference shrinks to

2. Memory & I/O Density per Watt – How Much Capacity You’re Paying to Power

Here the proportion inverts. The CompactLogix 5380 (0.6 MB user memory) drives up to 48 local I/O modules and 180 EtherNet/IP nodes. At 8.5 W, you get ~0.07 MB per watt. The NX1P2 packs 1.5 MB program memory + 2 MB variable memory for about 6 W – that’s ~0.58 MB per watt, a factor of 8× higher memory density per watt.

Mechanism: the Omron uses a single-chip memory architecture on a unified Sysmac Studio project store, whereas the CompactLogix separates user memory, safety memory, and firmware storage (each with different power rails). The CompactLogix also includes an integrated 1 Gbps switch for DLR, which draws a fixed ~1.5 W regardless of memory utilisation. The NX1P2’s EtherCAT interface uses less power per node (no switch silicon).

Worked consequence: if you need 1 MB of program space and 100 I/O points, the Omron solution will dissipate ~6 W; an equivalent CompactLogix configuration (with 48 I/O local + remote nodes) will be ~8 W, but you get more networking bandwidth. The memory‑per‑watt ratio strongly favours Omron when memory utilisation is high and network load is moderate.

Reversal: if your program is small (

3. Motion Axis Power – Proportional Cost per Controlled Axis

Integrated motion alters the power proportion dramatically. The CompactLogix 5380 supports up to 32 axes over EtherNet/IP using CIP Sync. The Omron NX1P2 supports up to 8 axes (4 PTP with integrated drive) over EtherCAT. Per controlled axis, the CompactLogix spends ~0.27 W/axis (8.5 W ÷ 32), while the NX1P2 spends ~0.75 W/axis (6 W ÷ 8). Magnitude proportion: the Allen‑Bradley platform is roughly 2.8× more power‑efficient per axis.

Mechanism: the CompactLogix uses a shared 1 Gbps backplane for both logic and motion – the same silicon that runs I/O also handles position loops. The NX1P2 uses a dedicated EtherCAT master that cycles at 2 ms, requiring additional buffer memory and a separate communication engine. Per axis, the Omron’s architecture is less integrated, so the marginal power per axis is higher.

Worked consequence: for a 4‑axis pick‑and‑place machine, the Omron draws ~3 W for motion control, the CompactLogix ~1.1 W. That 1.9 W difference is negligible in a 300 W cabinet. But scale to 16 axes (beyond the NX1P2’s capacity) – the CompactLogix scales sub‑linearly at ~0.2 W/axis, while the Omron would need a second controller, doubling the power budget to 12 W.

Flip condition: if you only need 2–3 axes and no future expansion, the Omron’s axis power cost is irrelevant. The absolute numbers are small; the proportion only matters when you plan to scale axes without adding controllers.

4. Idle Power – Standby Proportions That Change the Sizing Equation

Neither controller idles at zero. The CompactLogix 5380 draws approximately 5 W at idle (derived: max 8.5 W, load-dependent; about 60 % baseline). The NX1P2 idle is roughly 3.5 W (derived from 6 W typical, 58 % baseline). Proportion: idle power represents 60 % of total dissipation for both. The ratio is nearly identical, meaning the incremental power for active logic is similar between the two platforms.

Mechanism: both controllers keep the backplane, Ethernet PHYs, and memory in active state even when the scan is empty – a design consequence of deterministic control. The Omron’s lower absolute idle (3.5 W vs 5 W) reflects a smaller switch (no DLR hardware) and lower memory power (single‑chip vs multi‑bank). But the proportion of idle to load is the same: about 60 % of the power budget is fixed, regardless of controller brand. This is the hidden proportion that panel designers miss.

Worked consequence: in a multi‑controller cabinet (say, three PLCs), the idle power adds up: 3 × 5 W = 15 W for CompactLogix vs 3 × 3.5 W = 10.5 W for Omron. That 4.5 W difference can push a cabinet from natural convection to a forced fan, driving up enclosure cost and maintenance.

Reversal: if your application runs near continuous load (e.g., packaging with 80 % duty), the idle proportion drops to ~30 %, and the absolute difference shrinks to ~1.5 W. The Omron’s idle advantage evaporates under sustained high load.

Illustrative comparison — all values from manufacturer datasheets or derived (marked). Proportions are approximate.
DimensionAllen-Bradley CompactLogix 5380Omron Sysmac NX1P2
Power dissipation (max load)8.5 W~6 W (illustrative, derived from typical current)
Scan time (mixed logic)~1–2 msprimary task 2 ms
Power per ms of scan~4.25 W/ms~3 W/ms
User memory0.6 MB1.5 MB program + 2 MB variable
Memory per watt~0.07 MB/W~0.58 MB/W
Max integrated axes32 (CIP Sync)8 (EtherCAT, 4 PTP)
Power per axis (derived)~0.27 W/axis~0.75 W/axis
Idle power (approx proportion)~5 W (60 % of max)~3.5 W (58 % of max)
Non‑obvious insight: The Omron NX1P2 has 8× higher memory density per watt than the CompactLogix 5380, yet the Allen‑Bradley has 2.8× better power per motion axis. The proportion flips depending on whether your load is memory‑heavy (Omron wins) or axis‑heavy (Allen‑Bradley wins).

Failure mode / counterexample: if you size by total watts alone (8.5 W vs 6 W), you’ll overestimate the Omron’s efficiency advantage. In a motion‑dense application, the Allen‑Bradley actually dissipates less power per controlled axis. The naive watt number misleads.

Rule‑based takeaway: choose the CompactLogix 5380 when your axis count exceeds 8 or you need DLR redundancy — the per‑axis power cost is lower and scales sub‑linearly. Choose the NX1P2 when your program memory requirement >0.8 MB and axis count ≤6 — the memory‑per‑watt advantage reduces cabinet cooling demand. For applications with fewer than 4 axes and memory under 0.5 MB, the power difference is negligible (±1.5 W); either platform works.

Topology/standards per the cited standards; all product ratings are manufacturer-stated values from the cited datasheets, current to 2026-06; derived/illustrative figures are labelled as such. This is not an independent head-to-head test. Allen-Bradley is a brand affiliated with this site; competitor names are used for identification only.

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Jane Smith

I’m Jane Smith, a senior content writer with over 15 years of experience in the packaging and printing industry. I specialize in writing about the latest trends, technologies, and best practices in packaging design, sustainability, and printing techniques. My goal is to help businesses understand complex printing processes and design solutions that enhance both product packaging and brand visibility.

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