Harshit Aneja
- Role
- Manufacturing Engineer at SLB
- Location
- Houston, TX, US
- LinkedIn followers
- 500 followers
About Harshit Aneja
When I first visited a manufacturing industry during my childhood, I was enthralled to…
Experience
Manufacturing Engineer
Aug 2021 — Present · Houston, TX, US
Sustained a capital expenditure project worth $3M, implementing an automated elastomer curing system that achieved a 50% reduction in cycle time,$400K in tooling and rework cost savings with a 4-year payback period. The project had a huge sustainabilityimpact with 600 tons of CO2 reduction equating to $68k natural gas savings annually. Utilized simulation and modeling software to develop and validate optimal curing profiles for process efficiency-Executed a $300K CapEx project to implement an automated mold extraction system, reducing cycle time by 40% and replacing a manual process with a PLC-modeled, fully automated setup. Improved HSE compliance and operational safety while integrating control logic and recipe modeling for reliable, repeatable extraction performance-Partnered with Supply Chain to qualify a new paint product for the manufacturing process, performing detailed coverage, film thickness, and bond strength validation tests to verify coating adhesion and durability. Ensured process compatibility and delivered up to $300K in annual savings through optimized material selection and standardized sourcing-Designed and standardized 4 tooling assemblies with 10 size variants in Creo using family tables, improving procurement efficiency via Supply Chain. Added thread reliefs and simulated tooling designs to prevent tool breakage, achieving 30% rework reduction and $12K tooling cost savings through enhanced manufacturability-Managed manufacturing-related CapEx budgeting and planning, creating detailed WBS structures, scheduling project tasks, and coordinating with suppliers for execution. Prepared funding requests and tracked project financials to ensure budget adherence and timely completion-Led the center’s transition to SAP, driving data validation using statistical methods and supporting planning, customer service, and quality teams through system ramp-up, knowledge sharing, and issue resolution.
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