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Industrial Process Automation
Automation that takes repetitive, error-prone steps out of a manufacturer's daily process.
Business goals
The client is a US manufacturer whose day-to-day process relied on steps that people had to repeat by hand. Manual steps like these cost time on every run, and each one is a chance for a mistake that someone finds later, when it costs more to fix. The client wanted that repetitive work handled automatically, so staff could spend their attention on the exceptions that actually need a person's judgment.
Project overview
Hexagon reviewed how the work moved through the client's process, then built automation around the steps that were repetitive and predictable. Routine tasks now run on rules and schedules. When something falls outside those rules, the right person gets told. Every automated action leaves a record, so staff can see what happened and when, and the process can be adjusted as the operation changes.
Challenges faced and solved
Automation pays off only when it fits how the shop really works.
Repeat work eating up skilled time
Skilled people on a production floor end up doing clerical repetition: copying values, checking status, kicking off the next step. It's necessary work that doesn't need their experience.
We mapped the repeat steps with the client and automated the ones with clear rules, leaving decisions that call for judgment with the staff.
Errors caught too late
A wrong value typed early in a process may not surface until much later. By then the rework costs far more than the original mistake would have.
We added validation at the point where information enters the process, so a bad value is rejected before it reaches the next step.
Knowing when something stalls
When a process depends on people passing work along, a stalled step can sit unnoticed until someone asks why an order or job hasn't moved.
We built exception alerts, so the responsible person hears about a stalled or failed step as soon as the system detects it.
Trusting what the system did
Staff won't rely on automation they can't check. If nobody can tell what ran and why, people quietly go back to doing it by hand.
We gave every automated action a timestamped log entry and a status view, so anyone on the team can check the work.
Features
| Feature | Description |
|---|---|
| Production and operations staff | |
| 1. Rule-Based Task Automation | Predictable steps run automatically once their conditions are met, which takes repetitive handling off the floor. |
| 2. Scheduled Jobs | Recurring work runs at set times, so it doesn't depend on someone remembering it during a busy shift. |
| 3. Input Validation | Values are checked as they come in, stopping obvious errors before they travel further down the process. |
| 4. Exception Alerts | When a step fails or falls outside the rules, the responsible person is notified so they can step in. |
| 5. Status View | A simple screen shows what is running, what's finished and what needs attention. |
| Supervisors and administrators | |
| 6. Activity Log | Each automated action is recorded with its time and outcome, which makes troubleshooting a matter of reading rather than guessing. |
| 7. Rule Settings | Authorized staff can adjust thresholds and schedules without a code release. |
| 8. Manual Override | A supervisor can pause an automated step and handle it by hand when the situation calls for it. |
| 9. Data Handoffs | Information moves between steps automatically, which removes retyping between one stage and the next. |
How the platform is put together
Each layer has one job.
The result
Repetitive steps in the client's process now run automatically, with people pulled in only when something needs them. The activity log shows what ran and when.
| Area | Before | After |
|---|---|---|
| Routine steps | Repeated by hand on every run | Run automatically by rule or schedule |
| Data entry errors | Often found downstream | Checked when the information comes in |
| Stalled work | Noticed when someone asked | Flagged with an alert to the responsible person |
| Process records | Dependent on individual memory | Timestamped log of each automated action |
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
Experienced people spend less time on clerical repetition.
Bad inputs get stopped before they cost more downstream.
Problems reach the right person rather than waiting to be noticed.
The activity log answers questions about what happened on any given run.
Conclusion
Good automation in manufacturing is rarely dramatic. It's a set of small, dependable steps that happen correctly every time, with a clear signal when they don't. Hexagon started with how the client's process actually ran, automated what was predictable and left judgment calls to the people who know the work. If your plant still has staff repeating the same steps by hand every shift, show us that process. We'd welcome a conversation about which parts are worth automating first.
Talk to us about your projectRelated services: business process automation · custom software development
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