Manufacturing
BI Dashboards & Analytics for Manufacturing
BI Dashboards & Analytics for manufacturing, built around the constraint that defines the sector: plant networks are unreliable and decisions must happen locally in milliseconds.
- Regulations in scope
- 4
- Systems we integrate
- 5
- Typical first release
- 6 weeks
What changes when it is manufacturing
Orqent Labs builds BI that ends with a decision, a small set of numbers, defined once, that someone acts on.
In manufacturing, plant networks are unreliable and decisions must happen locally in milliseconds. That single fact reshapes how bi dashboards & analytics has to be built here, the guardrails, the approval points and the evidence trail are design inputs rather than things bolted on before go-live.
The workload we are most often asked to take on first is downtime root-cause analysis, usually integrated against MES. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.
Built by engineers who ship production systems, not by a practice that subcontracts the build. You own the code, the models where they are open-weight, and the documentation to run it without us.
The sector constraints we design around
- Defining constraint
- plant networks are unreliable and decisions must happen locally in milliseconds
- Regulations in scope
- ISO 9001 · factory safety regulations · environmental compliance · sector-specific quality standards
- Systems of record
- MES · SCADA and PLC · ERP · CMMS · quality management systems
- Where we usually start
- visual defect inspection
BI Dashboards & Analytics workloads in manufacturing
- visual defect inspection
- predictive maintenance
- production scheduling
- quality documentation
- downtime root-cause analysis
What is included
- Metric definitions agreed and documented once
- A semantic layer so numbers cannot diverge by report
- Dashboards designed for decisions, not for decoration
- Scheduled distribution to the people who need it
- Natural-language follow-up questions over the same data
- Usage tracking so unused dashboards get retired
Questions from this sector
Do we need to upgrade our machines?
Usually not. Most value comes from data your PLCs and cameras already produce and nobody is currently using.
What if the network goes down?
Edge deployment keeps inference local and tolerates disconnection, syncing when connectivity returns. On a shop floor that is a requirement, not an option.
Which BI tool do you use?
Power BI, Metabase, Superset or a custom build, chosen on your licensing, team skills and how much customisation you need. We are not tied to one vendor.
Why do our reports disagree?
Almost always because the same metric is defined differently in different places. A semantic layer with one agreed definition fixes it structurally rather than report by report.
Can non-technical staff ask their own questions?
Yes, natural-language querying over the governed semantic layer, so answers stay consistent with the dashboards.
Other capabilities for manufacturing
- AI Agent Development for Manufacturing
- Agentic Workflow Automation for Manufacturing
- LLM Application Development for Manufacturing
- RAG & Knowledge Retrieval for Manufacturing
- Chatbot Development for Manufacturing
- Computer Vision for Manufacturing
- Document Processing & IDP for Manufacturing
- AI Copilot Development for Manufacturing
- Predictive Analytics & Forecasting for Manufacturing
- Data Engineering for Manufacturing
BI Dashboards & Analytics for manufacturing, worth a conversation?
Tell us the workload and the regulation it sits under. We will tell you what is realistic.
Or email bd@dtrasglobal.com · call +91 74118 77878