Manufacturing Data Analytics: From Claims Classification to Continuous Improvement
Modern manufacturing generates vast amounts of data every day from production lines and supply chains to customer service platforms. But data alone does not deliver value unless it can be translated into insights and actions.
At Nobisoft, we recently developed a specialized web-based App to help a manufacturing organization do exactly that. The system connects multiple enterprise data sources to support quality engineering teams in identifying root causes of issues and driving long-term product improvements.
Turning Data Noise into Actionable Claims
The client operates in the manufacturing industry and was facing a growing volume of claims and issues reported from different systems, including:
- DMS (Document Management System)
- MES (Manufacturing Execution System)
- Salesforce
These claims often lacked structure, making it difficult to spot patterns or prioritize resolutions.
We developed a solution that acts as a central processing layer for this data. The App classifies claims automatically and presents them through clear visual dashboards.
This classification is not simply about organizing information. It empowers Quality Engineers (QEs) and other stakeholders to:
- Identify recurring issues
- Assess severity levels
- Uncover systemic causes
Enhancing Root Cause Analysis and Traceability
One of the key functions of the App is to support root cause analysis.
Once claims are categorized by system and issue type, the software allows users to link each claim directly to relevant Jira tickets. This connection between classified data and project management tools ensures that insights lead to action not just reporting.
“For example, if multiple claims around defective parts are traced back to MES data within a specific shift or machine, the QE team can raise a Jira ticket that not only resolves the current issue but also feeds into broader process adjustments.
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Over time, this creates a feedback loop between data analysis and continuous improvement.
A Flexible Architecture for Scalable Data Integration
The app is designed with a modern architecture to support scalability and performance:
- Frontend: ReactJS
- Backend: .NET Core
- Database: PostgreSQL
- Hosting: AWS infrastructure
This stack allows:
- Seamless integration with various third-party systems such as Salesforce
- Lightweight and responsive access for users
- Expansion to future analytics layers (e.g., anomaly detection)
Lessons for Manufacturers Looking to Leverage Analytics
While every manufacturer has its own systems and processes, the core principle remains the same:
“Raw data must serve decision-making.
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Whether your goal is to:
- Improve product quality
- Speed up issue resolution
- Gain a clearer view of cross-functional inefficiencies
…purpose-built software can bridge the gap between data collection and actionable insight.
This project demonstrated the value of creating a user-centric analytics tool that fits naturally into existing workflows. By focusing on user experience and automation, manufacturers can empower their teams to do more with the information already at their fingertips.
Final Thoughts
At Nobisoft, we believe that digital transformation in manufacturing is not just about adopting tools, but about aligning technology with operational goals.
This project highlights how targeted solutions can:
- Reduce friction
- Close communication loops
- Bring visibility to areas where improvement matters most
👉 If your organization is seeking a better way to process manufacturing data or facing challenges in issue classification and resolution, our team is ready to help you design and implement a solution tailored to your needs.
Let’s build a smarter manufacturing workflow together.