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Key statistics

The identity block — every fact is canon, none is generated.

1 of 8

Track

Support

Family rungs priced

S1 · S2 · S3 · S4 · S5

49-0000

industrial_energy_operations

Coordinates

3 / 4 spaces

pay@2 · 2026-07

What this role is

Entry-level support role assisting with routine upkeep and monitoring of engine room and plant equipment. At the Support Associate (S1) level, the role owns a single task type or queue, routine, well-defined requests, and drives individual transactions. None.

What this level does

Perform preventive maintenance tasks assigned through the plant CMMS work-order queue following the step-by-step job instructions provided, and mark each task complete in the system.
Examine parts for defects such as breakage or excessive wear during routine inspections, and flag anything abnormal to a senior technician or the Plant Maintenance Lead.
Record repairs and maintenance performed against the correct CMMS work order, noting parts used and time spent as instructed.
Assist senior technicians on repair jobs by fetching parts, holding/staging components, and running basic hand tools under close supervision on running equipment.

Knowledge applied: General knowledge of maintenance routines and CMMS task entry; performs prescribed PM tasks with answers readily available in the work-order instructions.
Complexity & problem solving: Routine, prescribed tasks; when something is unclear or abnormal, escalates rather than deciding.
Collaboration & interaction: Works under close supervision with detailed instructions; standard interactions with senior technicians and the Lead.
Typical experience: 0–1 years; minimal maintenance experience, typically HS diploma with initial on-the-job training.

Skills at this level

CMMS Work-Order Execution: — Receives, actions and closes preventive and corrective work orders in the plant's Computerized Maintenance Management System, recording parts used, labor time and repair notes so equipment history stays accurate and usable.
Technical Schematic Interpretation: — Reads mechanical, electrical, hydraulic, pneumatic and control schematics to locate components and trace faults through power and control circuits on plant and mining equipment.
Preventive Maintenance: — Performs scheduled lubrication, adjustment, inspection and component replacement on running equipment so small mechanical or technical problems are caught before they become major failures.
Equipment Defect Inspection: — Examines parts and assemblies for breakage, excessive wear and abnormal condition during inspections, and documents findings to trigger corrective action.
Broad Multi-Discipline Maintenance: — Applies a skill set spanning mechanical, electrical, hydraulic, pneumatic and control systems — from welding and wiring to hand tools and hydraulics — to diagnose and repair diverse plant equipment.
Heavy Mining Equipment Repair: — Maintains and repairs drills, loaders, conveyors and utility systems, including installing wire, connecting power sources and restoring equipment to safe running condition.
Breakdown Diagnosis: — Isolates the root cause of moderately-to-highly complex faults across interacting systems and decides repair, replacement or modification and the safe sequence to execute it.
Repair Job Planning: — Assists in planning repair work and special projects by estimating parts, design/layout and downtime windows, and coordinating the shutdown so work fits the operational envelope.
Reliability-Centered Maintenance: — Applies RCM principles to decide which failure modes warrant planned intervention, shaping PM routines and job plans for a specialty equipment area.
Predictive Maintenance / Condition Monitoring: — Uses condition-monitoring and IoT-based techniques to detect degradation early and shift a specialty area from reactive repair toward planned, forward-looking intervention.
Energy Consumption Optimization: — Monitors facility energy use, maintains energy-recovery systems and improves equipment efficiency to support plant sustainability targets in energy/mining operations.
Spare Parts Inventory Judgment: — Recommends spares and stocking levels for specialty equipment, balancing the downtime risk of a stockout against carrying cost.
Working Lead / Peer Coaching: — Assigns and checks the work of less experienced technicians on repair jobs and shutdowns, and trains peers on diagnosis and repair methods for difficult equipment.

Model-authored from 21 retrieved sources, then adversarially reviewed by an independent judge panel and held to a minimum-evidence floor before publication. Distinct from corpus-extracted content, which is labelled as such.

Pay across the ladder

Plant Maintenance (Energy/Mining) — median with , by . Real canon data.

National-base pricing — this family's function differential is pending review, so dollar levels are not function-adjusted (level-over-level % is unaffected).

Pay figures are modeled estimates from our market equation — level-differentiated, with honest-wide bands. They refresh as new leveling evidence lands; treat per-role dollars as directional.

Demand — is the field growing, or just turning over?

SOC 49-0000 · national

Employment growth 2019–2024, BLS OEWSobserved

+8.9%Industrial Machinery Mechanics · United States

387,630 → 421,940 jobs

45,700 openings / year, split into:

growth 7,078

replacement / exits 38,622

Growth — new jobs (15%)Exits — backfill (85%)

15% of hiring here is genuine expansion; the rest backfills people who move on.

Projected growth 2024–34 expanding: +16.1%
Growth share of hiring: 15%
Exit / retention pressure moderate: 85%
Openings / year: 45,700

Two quantities, kept apart: observed = employment growth differenced from two BLS OEWS vintages (what already happened); projected = BLS Employment Projections 2024–34, openings decomposed into growth + exits (growth derived from projected employment change). Neither is a pay figure.

Where this role sits — growth vs. pay

level S1 held

Demand axis is projected growth (not raw openings — that just measures churn). A curated, de-duplicated set of recognizable occupations held at this level; this role is highlighted.

Where it pays — by metro

OEWS metro median

San Jose-Sunnyvale-Santa Clara, CA$64k

San Francisco-Oakland-Fremont, CA$58k

Washington-Arlington-Alexandria, DC-VA-MD-WV$53k

Boulder, CO$53k

Seattle-Tacoma-Bellevue, WA$53k

Boston-Cambridge-Newton, MA-NH$50k

Lexington Park, MD$49k

Trenton-Princeton, NJ$49k

Pay only — metro-level demand isn't in public data (it needs job postings). National median $39k; the demand-cube initiative will add growth-by-metro.

What changes across the ladder

Level-distinction canon isn't available for the adjacent levels of this profile yet.

Level differentiators

What separates S1 (S1 — Support Associate) from the levels around it — this level only. Every word is real canon for this profile.

Scope: A single task type or queue
Autonomy: Close supervision; follows defined procedures
Complexity: Routine, well-defined requests
Impact: Individual transactions
Decision rights: Acts within scripts; escalates exceptions
Leadership: None

Full level-by-level matrix (side by side across the ladder) lives on the Ladder drill-down — not here.

Promotion

The next rung from S1 is S2.

Performance criteria for this profile render in the assessment kit →

People also watch

Nearest coordinate neighbors — same , same level. Each row's (confident / review / no match) comes from its — computed, not curated.

Profile	Key	Median	Δ structural
VP of Plant Maintenance	jf_plant_maintenance_energy_mining::E1	$169,459†	confident0.06
Plant Maintenance Supervisor	jf_plant_maintenance_energy_mining::M1	$85,619†	confident0.06
Associate Plant Maintenance Technician	jf_plant_maintenance_energy_mining::P1	$61,862†	confident0.06
Plant Maintenance Technician	jf_plant_maintenance_energy_mining::S2	$42,923†	confident0.06

†National-base pricing — this family's function differential is pending review, so the dollar level is not function-adjusted.

Capability cluster

O*NET 49-9041

Core to this role. Click any element with an ⓘ for its O*NET definition. A job-specific capability model (SkillFrame) will sharpen this and add worked examples.

The Job Swatch

S1

jf_plant_maintenance_energy_mining::S1

Plant Maintenance Assistant

Plant Maintenance (Energy/Mining)

The swatch is JobFrame's core primitive: a hueset deterministically by the role's superfunction, the profileKey as its color code, the level ladder, and a content fingerprint. Two swatches that look alike are alike.

Because every role carries computable coordinates, similarity, leveling, and pricing become measurable instead of arguable— the whole point of "Pantone for jobs."

Structural

structural@1

Where it sits— position in the work taxonomy + level (weighted Gower, level > function > focus).

Track: S
Superfunction: industrial_energy_operations
Function: plant_operations
Family: plant_maintenance_energy_mining
Universal level: 1 / 8

Content

content@2

What it's about— a fingerprint over the role's tasks & capabilities.

Two roles can sit far apart structurally yet be close in content — that gap is itself a signal.

3-state matching

How any two swatches compare — a real distance in coordinate space, resolved to a calibrated verdict (never a fake "94% match").

Mining Processing Plant · S1review0.17

Nuclear Power Plant · S1review0.17

Plant Operations (Energy/Mining) · S1review0.17

Power Plant Management · S1review0.17

Refinery · S1review0.17

Renewables Plant · S1review0.17

Editions — frozen & versioned

structural@1live

Released 2026-06-17

content@2live

Released 2026-07-28

pay@2live

Released 2026-07-02

semantic@1live

Released 2026-07-02

Coordinates belong to a frozen, versioned edition — a coordinate computed today still means the same thing next quarter. Re-fitting issues a new edition, so comparisons are never silently redefined.

How to read this profile

Every number here is traceable — to a named source, a stated method, and an as-of date — and each value is labeled by how we know it: observed from data, computed by a model, projected forward, or governed canon. Nothing is a black box, and nothing is invented to fill a gap.

Where every number comes from

What	Source & method	Edition	State
Median pay + range	JobFrame pay equation (function base × family multiplier × level × focus differential)	pay@2	computed
Pay across the ladder	Same equation applied at each universal level	pay@2	computed
Demand — growth & openings	BLS Employment Projections; openings decomposed into growth + exits	EP 2024–34	projected
Pay by metro	BLS OEWS metropolitan medians	OEWS 2024	observed
Level distinctions	JobFrame universal-level canon (scope · autonomy · complexity · impact · decision rights · leadership)	canon	canon
Capability cluster	O*NET Knowledge / Skills / Abilities	O*NET 49-9041	computed
Coordinates	JobFrame coordinate system — structural (weighted Gower) + content fingerprint	structural@1 · content@2 · pay@2 · semantic@1	computed
Related roles	Nearest neighbors in the structural coordinate space	structural@1	computed

The principles behind the numbers

Ranges, not false precision

Pay is P10 · median · P90, never a single misleading number.

Three honest states, never a fake %

Role matches resolve to confident / review / no-match — a calibrated verdict, not a made-up percentage.

Provenance on every value

Each number carries whether it's observed, computed, projected, or canon — so you always know how much to lean on it.

Gaps shown as gaps

When a figure isn't available at the grain you need, we say so — we don't fabricate a number to fill the cell.

Frozen, versioned editions

Pay and coordinate editions are pinned, so a comparison you make today still means the same thing next quarter.

Privacy by min-N

Any aggregate over people is suppressed below a minimum count, so no individual is identifiable.

Freshness

As of2026-07-30Editioncanon-v2@2.1.0-completeSourcecanon-v2 cell + salary-benchmark (model)