IEEE Transactions on Industrial Electronics (ieee-transactions-on-industrial-electronics)

Journal positioning

IEEE Transactions on Industrial Electronics (TIE), published by the IEEE Industrial Electronics Society, is a flagship venue for the application of electronics, control, instrumentation, and computational intelligence to industrial systems: motor drives and motion control, power-electronics applications, industrial informatics and communication, mechatronics, fault diagnosis and condition monitoring, and robotics for industry. The defining expectation is a concrete advance demonstrated on a real industrial problem and validated experimentally, not a pure theory paper or a converter-topology study with no system-level industrial framing. Its scope is broader on the application side than ieee-transactions-on-power-electronics, whose center of gravity is the converter/topology itself. This skill is a fit / venue-selection / re-framing tool. It does not replace the journal's current official author information. Before submitting, re-check the live IEEE TIE author guidance and submission system.

When to trigger

• The author names TIE for a drives, motion-control, industrial-informatics, mechatronics, or fault-diagnosis manuscript and wants a fit/framing check.
• A contribution must be re-framed from "we propose a method" into an industrial-application advance with experimental hardware evidence.
• The author is choosing between TIE and ieee-transactions-on-power-electronics, ieee-transactions-on-automatic-control, or ieee-transactions-on-robotics.
• The author needs TIE's experimental-validation bar and desk-reject heuristics.

Scope & topic fit

• Motor drives and electrical machines control: field-oriented and direct-torque control, sensorless drives, multiphase and fault-tolerant drives.
• Motion control and mechatronics: servo systems, precision positioning, vibration suppression, and actuator/sensor integration for industrial machines.
• Power-electronics applications at the system level: renewable interfaces, grid-tied inverters, EV powertrains — framed by the industrial use, not the topology alone.
• Industrial informatics and the industrial IoT: real-time communication, edge/embedded computation, digital twins, and Industry 4.0 system integration.
• Fault diagnosis, prognosis, and condition monitoring of drives, machines, and power-electronic systems, with measured or realistically emulated fault data.
• Computational intelligence (learning, fuzzy, evolutionary methods) deployed in an industrial control/diagnosis loop, evaluated against an industrial baseline.

Method & evidence bar

• Experimental validation is expected: a hardware prototype, test bench, or dSPACE/FPGA real-time implementation; simulation-only papers are a weak fit unless the contribution is explicitly a modeling/design framework with a strong rationale.
• Report the experimental setup completely: machine/converter ratings, switching frequency, controller hardware, sampling rate, and sensing, so results are reproducible.
• Benchmark against an established industrial method under matched operating conditions; quantify the improvement (efficiency, dynamic response, THD, ripple, accuracy).
• Demonstrate robustness to the realities of industrial operation: parameter variation, load disturbance, measurement noise, and transients — not only nominal steady state.
• Stability/convergence claims, where made, must be justified; for learning-based schemes, address generalization beyond the single rig.
• Position the advance against recent TIE-relevant literature, not a decade-old strawman.

Structure & house style

• IEEE double-column format; TIE publishes full Papers and shorter contributions — match the article type to the contribution and re-check current definitions and length policy on the live guide.
• The introduction motivates an industrial need and the gap in existing practice, then states the contribution; survey-style introductions without a sharp gap are discouraged.
• Figures are load-bearing: control block diagrams, experimental waveforms with labeled scales, and comparison plots against the baseline method.
• A clear experimental-results section is central; tables should summarize quantitative comparisons under defined operating points.
• Keep the theory proportionate to the application contribution; deep proofs that dwarf the industrial result suggest a control-theory venue instead.

Official-submission checklist

• Before giving submission-ready advice, read ../../resources/source-basis.md and ../../resources/official-source-map.md; start from the IEEE Author Center anchors, then cite the current TIE-specific page you checked.
• Search the live site for "IEEE Transactions on Industrial Electronics information for authors" and follow the current ScholarOne/IEEE version.
• Re-check article types, page/length limits and any overlength/mandatory-page policy, and the IEEE double-column template.
• Confirm experimental-data, reproducibility, and any video/supplementary-material expectations.
• Re-check ORCID, competing-interests, funding, author-contribution, and AI-use disclosure requirements, and IEEE open-access options.
• If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

• The contribution is an industrial-application advance, not a generic method with no industrial framing.
• Results are validated on hardware / a real-time platform; the setup is reported reproducibly.
• The improvement is quantified against an established industrial baseline under matched conditions.
• Robustness to parameter variation, load/disturbance, and transients is demonstrated.
• Theory is proportionate to the application; the paper is not a pure-theory submission.
• Article type and length fit current TIE limits; figures and tables carry the experimental story.

Common desk-reject triggers

• Pure-theory or simulation-only paper with no experimental validation and no compelling reason.
• A converter-topology or power-stage study with no system-level industrial application framing.
• Incremental tweak to a known control/diagnosis scheme with marginal, unbenchmarked gains.
• A machine-learning paper using an industrial dataset as a label, with no deployment or industrial loop.
• Scope mismatch: control theory, communications, or signal processing with industry only as a keyword.

Re-routing decision

• Converter topology / power-stage design as the core → ieee-transactions-on-power-electronics.
• General control theory with provable guarantees as the contribution → ieee-transactions-on-automatic-control / automatica.
• Robotics for manipulation/locomotion as the central result → ieee-transactions-on-robotics.
• Signal/biosignal processing as the core → ieee-transactions-on-signal-processing.
• Antenna/EM or instrumentation-measurement focus → ieee-transactions-on-antennas-and-propagation or a measurement venue.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] IEEE Transactions on Industrial Electronics
[Topic tags] <2–3 closest industrial-electronics subtopics>
[Application] <the industrial problem and the advance in one line>
[Method/evidence] <does the experimental validation clear TIE's hardware + benchmark bar?>
[Top risk] <the single most likely reason for rejection>
[Article type] Paper / shorter contribution
[Official items to re-check] <article type / length / template / experimental-data / disclosures>
[Re-route suggestion] <if not a fit, a better-matched venue>