Businesses have been running on profits and profits usually are the function of the costs. After industrialization, the costs were reduced by creating efficient processes to run things smoothly over a predictable timeline. This was all good till the time computers came and along came the internet connectivity.

The processes moved from humble registers to computers and when the computer labor became costly in a certain market some of the processes moved to the low-cost centers. All this for maintaining the cost to generate more profits. The business process automation(BPA) has been doing the same. It is about finding the efficiencies in the business processes to cut down unnecessary steps and make them less costly.

RPA capabilities

The latest revolution was when the virtualized platforms that allowed the addition and removal of resources required for processes based on the workloads. This allowed the companies to investigate opportunities to define their processes based on automated rules. This was the evolution of the Robotic process automation.

RPA goes a step further in terms of making the repetitive processes automated so that human intervention is lost. A simple application for this could be rule-based responses you need to provide for certain workflows. When you code in the Rules once they do not need an intervention of any kind and the RPA takes care of it all. Companies have benefited by implementing RPA based solutions and processes to cut costs multiple times. This is the time where bots started taking over communication as one of the first use cases.

Where is RPA headed?

The current revolution is Industry 4.0 which is going to change the dynamic once again. The RPA process still requires to be trained before they can apply the rules correctly for the given use case. The AI, ML, and cognitive computing provide the capability of self-learning to these systems and make the learning an on the job task, very similar to human way of learning. This change of process automation is being touted as Intelligent robotic process automation (iRPA) and it is here to stay.

iRPA can not only make bots more intelligent with every interaction they have but can also be trained to identify new areas where they could start assisting. So let’s say you create a bot for customer support and over the period of time the bot can start providing options of features required in your products based on the feedback received in the interactions or provide you insights about whether a product may be successful or not based on similar product launches in the past.

iRPA is the future and use case are being defined for almost all industries however we feel that Insurance and banking would be the first ones to take the bite.

Smart Manufacturing Dashboards: A Real-Time Guide for Data-Driven Ops

By : Divyanjali Gupta

Published on Jul 31, 2025

Data Science Manufacturing Analytics Smart Manufacturing

Smart Manufacturing starts with real-time visibility.

Manufacturing companies today generate data by the second through sensors, machines, ERP systems, and MES platforms. But without real-time insights, even the most advanced production lines are essentially flying blind.

Manufacturers are implementing real-time dashboards that serve as control towers for their daily operations, enabling them to shift from reactive to proactive decision-making. These tools are essential to the evolution of Smart Manufacturing, where connected systems, automation, and intelligent analytics come together to drive measurable impact.

Data is available, but what’s missing is timely action.

For many plant leaders and COOs, one challenge persists: operational data is dispersed throughout systems, delayed, or hidden in spreadsheets. And this delay turns into a liability.

Real-time dashboards help uncover critical answers:

What caused downtime during last night’s shift?
Was there a delay in maintenance response?
Did a specific inventory threshold trigger a quality issue?

By converting raw inputs into real-time manufacturing analytics, dashboards make operational intelligence accessible to operators, supervisors, and leadership alike, enabling teams to anticipate problems rather than react to them.

1. Why Static Reports Fall Short

Reports often arrive late—after downtime, delays, or defects have occurred.
Disconnected data across ERP, MES, and sensors limits cross-functional insights.
Static formats lack embedded logic for proactive decision support.

2. What Real-Time Dashboards Enable

Line performance and downtime trends
Track OEE in real time and identify underperforming lines.

Predictive maintenance alerts
Utilize historical and sensor data to identify potential part failures in advance.

Inventory heat maps & reorder thresholds
Anticipate stockouts or overstocks based on dynamic reorder points.

Quality metrics linked to operator actions
Isolate shifts or procedures correlated with spikes in defects or rework.

These insights allow production teams to drive day-to-day operations in line with Smart Manufacturing principles.

3. Dashboards That Drive Action

Role-based dashboards
Dashboards can be configured for machine operators, shift supervisors, and plant managers, each with a tailored view of KPIs.

Embedded alerts and nudges
Real-time prompts, like “Line 4 below efficiency threshold for 15+ minutes,” reduce response times and minimize disruptions.

Cross-functional drill-downs
Teams can identify root causes more quickly because users can move from plant-wide overviews to detailed machine-level data in seconds.

4. What Powers These Dashboards

Data lakehouse integration
Unified access to ERP, MES, IoT sensor, and QA systems—ensuring reliable and timely manufacturing analytics.

ETL pipelines
Real-time data ingestion from high-frequency sources with minimal latency.

Visualization tools
Custom builds using Power BI, or customized solutions designed for frontline usability and operational impact.

Smart Manufacturing in Action: Reducing Market Response Time from 48 Hours to 30 Minutes

Mantra Labs partnered with a North American die-casting manufacturer to unify its operational data into a real-time dashboard. Fragmented data, manual reporting, delayed pricing decisions, and inconsistent data quality hindered operational efficiency and strategic decision-making.

Tech Enablement:

Centralized Data Hub with real-time access to critical business insights.
Automated report generation with data ingestion and processing.
Accurate price modeling with real-time visibility into metal price trends, cost impacts, and customer-specific pricing scenarios.
Proactive market analysis with intuitive Power BI dashboards and reports.

Business Outcomes:

Faster response to machine alerts
Quality incidents traced to specific operator workflows
4X faster access to insights led to improved inventory optimization.

As this case shows, real-time dashboards are not just operational tools—they’re strategic enablers.

(Learn More: Powering the Future of Metal Manufacturing with Data Engineering)

Key Takeaways: Smart Manufacturing Dashboards at a Glance

Aspect	What You Should Know
1. Why Static Reports Fall Short	Delayed insights after issues occur Disconnected systems (ERP, MES, sensors) No real-time alerts or embedded decision logic
2. What Real-Time Dashboards Enable	Track OEE and downtime in real-time Predictive maintenance using sensor data Dynamic inventory heat maps Quality linked to operators
3. Dashboards That Drive Action	Role-based views (operator to CEO) Embedded alerts like “Line 4 down for 15+ mins” Drilldowns from plant-level to machine-level
4. What Powers These Dashboards	Unified Data Lakehouse (ERP + IoT + MES) Real-time ETL pipelines Power BI or custom dashboards built for frontline usability

Conclusion

Smart Manufacturing dashboards aren’t just analytics tools—they’re productivity engines. Dashboards that deliver real-time insight empower frontline teams to make faster, better decisions—whether it’s adjusting production schedules, triggering preventive maintenance, or responding to inventory fluctuations.

Explore how Mantra Labs can help you unlock operations intelligence that’s actually usable.

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