Lead AI-Driven Shop Floor Planner for Metal Fabrication

Clark Development Corporation

Philippines

Hybrid

PHP 1,339,000 - 2,344,000

Full time

14 days+

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Job summary

ETS PRODUCTS PHILIPPINES, INC. seeks an experienced Scheduling Engineer to optimize AI-driven production planning for metal fabrication. You will translate shop-floor constraints into software rules and integrate AI modules with ERP/MES and CAD/CAM nesting tools.

Responsibilities include benchmarking solutions, leading implementation, and maintaining machine telemetry-driven scheduling with real-time labor constraints, plus generating cycle-time analytics to improve accuracy.

Qualifications

Bachelor's degree in Mechanical Engineering, Manufacturing/Industrial Engineering, or a highly technical related field.
3–5+ years of planning inside high-mix, low-volume metal fabrication or assembly plants.
Thorough understanding of data-driven scheduling rules, algorithmic constraints, and predictive machine-learning engines.
Ability to interpret operational dashboards, spot floor data anomalies, and diagnose why the scheduling engine shifted a pipeline.
Fluency with 3D design software (SolidWorks/AutoCAD) and industrial nesting programs (e.g., TruTops, Lantek, Radan, CYPCUT).
Deep comprehension of sheet metal K-factors, grain orientation, bend deductions, and weld distortion.
Comprehensive skill reading advanced mechanical blueprints, Geometric Dimensioning and Tolerancing (GD&T), and AWS/ISO welding symbols.
Direct background scheduling industrial lasers, multi-axis press brakes, MIG/TIG welding, and mechanical assemblies.
Hands-on experience with modern ERP/MES systems (e.g., SAP, Epicor, Odoo) alongside Advanced Planning and Scheduling (APS) software.

Responsibilities

Translate plant-floor constraints into software rules and lead AI-driven scheduling implementations.
Benchmark, select, and integrate AI scheduling modules with ERP/MES/CAD-CAM nesting databases.
Manage AI-driven scheduling engines using machine telemetry and real-time labor constraints.
Monitor rescheduling outputs and override AI during major disruptions.
Map production steps across fiber lasers, CNC press brakes, welding stations, and manual assemblies.
Use predictive analytics to simulate shop floor capacity constraints and proactively smooth machine loads.
Review advanced nesting options to maximize sheet metal efficiency and coordinate scrap reclamation.
Compile comprehensive production files including flat-pattern DXF files, bending sequences, and Weld Procedure Specifications (WPS).
Run production cycle-time audits to feed historical data back into the AI system, sharpening scheduling accuracy.