CASE STUDY
Automating BOM Extraction & Process Documentation
AI-Powered Efficiency with AroTrace
In the highly competitive automotive supply chain, managing complex wire harness BOMs and ensuring accurate BOM extraction is a daily challenge. A leading Tier-1 supplier, working with global OEMs, partnered with Arorian to modernize its engineering workflows. By deploying AroTrace with its AI automation layer, the company transformed PDF-based BOM handling into a streamlined, AI-supported process — reducing errors, saving engineering time and ensuring production-ready documentation.
THE CHALLENGE
Manual, Error-Prone BOM Handling
Despite a dedicated team of engineers, the BOM process relied heavily on manual steps and disconnected tools. From retyping customer drawings into spreadsheets to preparing process documentation without digital continuity, inefficiencies consumed valuable engineering capacity.
Key pain points included:
1. Customer Drawings (PDFs)
BOMs received as one-page PDFs had to be manually entered into Excel. This introduced delays and errors, with no direct link between the drawing and the BOM in Windchill.
2. MOB & Process Sheets
Engineers manually calculated wire lengths, connector counts and prepared MOB and process sheets. The approach was error-prone, lacked consistency and provided no version control.
3. Overall Impact
More than half of engineers’ time was spent on repetitive, non-value-added tasks, limiting scalability and putting compliance at risk.
THE SOLUTION
Step-by-Step Automation with AroTrace
To address these inefficiencies, the supplier implemented AroTrace with its AI automation layer, bringing intelligent automation into BOM handling. The workflow combined structured AI-driven outputs with human oversight to ensure accuracy and compliance:
1
PDF BOM Extraction
AI applied OCR and NLP to extract structured BOM data directly from customer drawings.
2
Storage in AroTrace
The team stored structured BOMs in AroTrace with the original drawing attached for traceability.
3
AI-Supported MOB Sheets
Wire lengths, grouping and connector counts were automatically calculated and compiled into MOB sheets.
4
AI-Supported Process Sheets
Process steps, tooling and cycle times were generated by AI, ensuring consistency and completeness.
5
Human-in-the-Loop Review
Engineers validated and approved the AI outputs, retaining full control over production readiness.
THE OUTCOME
From Manual Rework to AI-Supported Documentation
The deployment of AroTrace delivered measurable results:
70% Reduction in Manual Effort
Engineers saved the equivalent of several FTEs annually by eliminating repetitive data entry and manual calculations.
Faster Time-to-Production
The team prepared BOMs, MOBs and process sheets in a fraction of the time, accelerating project timelines.
Higher Accuracy and Consistency
AI ensured uniform outputs, while human review guaranteed quality and compliance.
Improved Traceability
Original PDFs, structured BOMs and derived process documentation were all linked within AroTrace, strengthening audit readiness.
Foundation for Scalability
Standardized workflows enabled the Wire Harness division to scale practices across projects and prepare for further automation phases.
Start Your Proof of Concept with AroTrace
The fastest way to experience the value of AI-powered BOM automation is through a short Proof of Concept. With AroTrace your team can validate automation in a controlled environment before deciding on full-scale adoption.
DURATION
2–4 weeks, depending on scope and complexity
COMMITMENT
No obligation to continue if success criteria are not met
AGREEMENTS
NDA and Proof of Concept Statement of Work (SOW) signed prior to kickoff
SUPPORT
Full access to Arorian’s engineering and product teams throughout the POC
ABOUT ARORIAN
Arorian is a global leader in providing digital solutions and services that drive transformation and growth for businesses across various industries. With a focus on innovation and excellence, Arorian delivers unparalleled value to its customers by harnessing the power of technology to solve complex challenges.
