Equipment assembly, integration and testing
STEMP Solutions, in partnership with a leading automation solutions provider who has a strong presence in Singapore & India, we support end-to-end components assembly, sub-assemblies, system integration, functional testing for high-tech industries including semiconductors, advanced manufacturing and precision engineering. Leveraging years of hands-on experience with capital equipment build, tool qualification and test process design, we bolster our OEMs and manufacturing partners.
For Customized cable assemblies, we have established a solution partner in India and we are committed to exceed your needs.
In near future, STEMP Solutions plans to support with our manufacturing engineering expertise on:
Translate engineering designs into production-ready prototypes, taking care of Bill of Materials, coordinate with design team on early product changes
Develop and execute integration protocols across mechanical, electrical, and control systems, establish labour hours baseline, Process FMEA
Define and implement robust testing procedures and checklists to ensure system reliability, safety, and performance at modular, sub-system, system level.
Support factory acceptance testing (FAT) and site acceptance testing (SAT) for global deployments
Whether you're launching a new tool platform or scaling up a proven design, STEMP Solutions will be providing technical project support that reduces time-to-market, improves yield, and ensures quality from build to deployment.
Where AI fits practically:
Robotics & Vision Systems: AI enhances robotics and vision systems by enabling real-time defect detection, adaptive quality control, and intelligent object recognition in automated workflows.
Time Study: AI accelerates time studies by automatically analyzing video footage to identify task durations, inefficiencies, and potential process optimizations.
Bill of Material (BOM) Analysis: AI streamlines BOM analysis by predicting cost impacts, identifying redundant or obsolete components, and suggesting optimized alternatives based on historical procurement and production data.
Deploy predictive maintenance models using equipment telemetry (vibration, temperature, acoustic sensors). Anomaly detection models to pre-emptively flag wear/failure risks before unexpected downtime occurs.