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Foundry ERP Database Solution
An Oracle database for a foundry's ERP, structured around jobs, patterns, heats and the metallurgical records that prove a casting is right.
Business goals
The client is a jobbing foundry pouring iron and steel alloys for heavy industry. Its work runs from pattern shop through molding, melting, pouring, lab testing, heat treatment and machining, and customers expect each casting to be traceable. The ERP that tracks all of this is only as good as the data under it. The client needed a dependable Oracle database behind that system.
Project overview
Hexagon delivered the Oracle database for the client's ERP. We structured the data around how a foundry actually runs: customer jobs, patterns, heats, lab results and later operations. Heat numbers link melt chemistry to the castings poured from it. We also set up user access, indexing for common lookups, and a backup routine, so the shop's records stay available and protected.
Challenges faced and solved
In a foundry, a bad record can be as costly as a bad pour.
Tracing a casting back to its heat
When a mining customer questions a part, the foundry must find the heat, the chemistry and the test results quickly. Scattered records turn that request into hours of searching through paper and files.
We linked each casting to its job and heat number in the database, so one lookup reaches the melt and lab records.
Jobbing work doesn't repeat neatly
A jobbing foundry can run a prototype and a repeat order in the same week, across different alloys and patterns. Rigid data structures force workarounds that eventually show up as errors.
We modeled jobs, patterns and alloys as separate related records, so a new job can reuse a pattern without duplicating its history.
Slow answers on the shop floor
Production staff need job status while molds are waiting and the furnace schedule is moving. A database that takes too long to answer soon gets replaced by a clipboard.
We indexed the lookups people use most, such as job number, heat number and pattern, to keep routine ERP screens responsive.
Records that can't be lost
Heat and test records may be needed long after a casting has shipped. A failed server without a tested backup can erase the proof that the work was done properly.
We set up a backup routine and role-based access, which protects the data from both system failures and accidental changes.
Features
| Feature | Description |
|---|---|
| Production data | |
| 1. Job and Work Order Records | Each customer job holds its part, alloy, quantity and status. This gives the ERP one record to build on. |
| 2. Pattern Register | Patterns are stored with the parts they make and the jobs that used them, which matters when repeat work comes back. |
| 3. Heat Records | Each melt gets a heat number tied to its alloy and date, covering grades such as high chrome, gray iron, ductile iron and steel. |
| 4. Operations Routing | A job's later steps, including heat treatment, machining, finishing and painting, are recorded in sequence so status is clear. |
| Quality data | |
| 5. Metallurgical Lab Results | Lab results are stored against the heat, so chemistry can be checked and retrieved when it's needed. |
| 6. Casting Traceability | Links between job, heat and result let staff follow a part from a shipment back to the furnace. |
| 7. Rejection and Scrap Records | Rejected castings are recorded against the job, which gives quality staff a place to look for repeating problems. |
| Administration | |
| 8. Role-Based Access | Users get only the data rights their job needs, reducing the chance of accidental edits to quality records. |
| 9. Backup Routine | Scheduled backups protect production and quality data against hardware failure or mistakes. |
| 10. Performance Indexing | Indexes on common search fields keep job and heat lookups quick as records build up. |
How the platform is put together
Each layer has one job.
The result
The client's ERP now runs on an Oracle database shaped around foundry records, from job to heat to lab result.
| Area | Before | After |
|---|---|---|
| ERP data | No purpose-built database structure for the ERP | An Oracle database organized around foundry work |
| Traceability | Heat and job data not reliably linked | Castings linked to job, heat and lab records |
| Access | Limited control over who can change what | Role-based access by job function |
| Data protection | Dependent on an undefined recovery path | A scheduled backup routine |
How we took it from idea to launch
Good software follows a process. Here are the six stages, and what happens in each one.
Discovery & Requirements
Goal: Define the product vision, target audience and core business requirements.
Key activities- Stakeholder interviews
- Market and competitor research
- Defining user personas
- Drafting technical specifications or a Product Requirements Document (PRD)
Design (UX / UI)
Goal: Create an intuitive user experience and visual interface.
Key activities- UX design: information architecture, user flows and wireframes
- UI design: high-fidelity mockups and interactive prototypes in Figma or similar tools
- Design system: colors, typography and component libraries
Development: Frontend & Backend
Goal: Build the functional application using agile sprints.
Key activities- Backend: set up databases, design APIs (REST, GraphQL), implement server logic, and configure authentication and authorization (OAuth, RBAC)
- Frontend: build responsive interfaces and connect components to backend APIs
- Version control: manage code through Git and GitHub
Security & Optimization
Goal: Harden the application against vulnerabilities and boost performance.
Key activities- Security: address the OWASP Top 10, including injection, XSS and CSRF, enforce encryption in transit and at rest, and implement rate limiting
- Optimization: code splitting and lazy loading, database indexing, API caching and load testing
- QA and testing: unit, integration and end-to-end tests
Beta Release
Goal: Deploy to a controlled group of real users to catch edge-case bugs and gather feedback.
Key activities- Set up staging and production CI/CD pipelines
- Launch a closed or open beta with real users
- Monitor errors through observability tools
Public Release (Launch)
Goal: Roll the software out to the general public.
Key activities- Final production deployment
- DNS configuration
- Marketing and onboarding rollout
- Post-launch performance and security monitoring
Business benefits
Staff can follow a casting back to its heat without a paper hunt.
Patterns and alloys are reused instead of being re-entered for each job.
Backups and access rules guard the data customers may ask to see.
Reports and screens draw on structured, consistent data.
Conclusion
A foundry's ERP lives or dies on data the shop trusts. Jobs, patterns, heats and lab results have to connect, or people go back to clipboards and memory. This was a focused piece of work: build the Oracle database, organize it around how castings are made, and protect it. Hexagon brings the same practical view to any manufacturing data problem. If your ERP database is slowing your shop down or you can't trace your parts, let's talk.
Talk to us about your projectRelated services: ERP development · database services · custom software development
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