> For the complete documentation index, see [llms.txt](https://linecraft.gitbook.io/ikshana-pro-knowledgebase/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://linecraft.gitbook.io/ikshana-pro-knowledgebase/product-guides/dashboards/kpi-dashboards.md).

# KPI Dashboards

## Overview

KPI Dashboards provide real-time visibility into manufacturing performance through configurable KPI trackers and visualizations. By visualizing manufacturing KPIs in real time, the dashboard enables teams to identify performance deviations early, monitor production targets, and respond quickly to changing shopfloor conditions.

## Creating KPI Visualizations

The KPI Dashboard supports the creation of customized KPI trackers and visualizations tailored to specific operational monitoring requirements. Each tracker can be configured based on the production objectives and performance indicators most relevant to the user.

{% stepper %}
{% step %}

### Graph definition

<figure><img src="/files/ybuR6lPlsJkPAHBGMHI2" alt=""><figcaption></figcaption></figure>

Every KPI tracker begins with a descriptive name that clearly communicates its monitoring purpose.
{% endstep %}

{% step %}

### KPI selection

<figure><img src="/files/TxpyhAxOAhMqnJ7I6gRh" alt=""><figcaption></figcaption></figure>

Users can select the KPI they wish to monitor and configure the level at which the metric is evaluated.

> *This flexibility allows teams to focus on the performance indicators most relevant to their operational objectives.*
> {% endstep %}

{% step %}

### Entity selection

KPI visualizations can be scoped to specific operational entities, including:

* Machines
* Cells
* Process Inputs/Outputs
* Machine States

> *This enables performance monitoring at both asset and line levels.*
> {% endstep %}

{% step %}

### Visualization configuration

Users can configure:

* Date range
* Chart type
* Visualization settings

These options help ensure KPI data is presented in the format most suitable for operational monitoring.
{% endstep %}
{% endstepper %}

## Managing KPI Visualizations

Once a KPI tracker has been created and saved, it becomes part of the KPI Dashboard and is immediately available for real-time monitoring.

As operational priorities evolve, existing visualizations can be modified to:

* Update KPI selections
* Change visualization settings
* Refine monitoring objectives
* Adjust asset scope

> *This flexibility allows dashboards to remain aligned with changing production requirements.*

## Best Practices

### Focus on actionable KPIs

Prioritize metrics that directly influence operational decisions and production outcomes.

### Monitor performance against targets

Real-time visibility is most valuable when actual performance can be compared against expected outcomes.

Track KPIs alongside operational targets to quickly identify performance deviations.

### Investigate deviations early

Significant KPI changes often indicate emerging operational issues.

Use KPI Dashboards as an early warning system to identify:

* Production instability
* JPH losses
* Equipment performance degradation
* Increasing downtime

before they have a larger impact on manufacturing performance.

### Combine KPI monitoring with deeper analysis

KPI Dashboards highlight what is happening in real time.

When performance deviations are identified, Analytical Dashboards and IoT & Quality Dashboards can be used to investigate the underlying causes and contributing factors.

## Operational Outcome

The KPI Dashboard provides real-time visibility into manufacturing performance and operational health.

By enabling continuous monitoring of critical production indicators, it helps teams detect performance deviations early, maintain operational stability, improve responsiveness, and make informed decisions based on live production data.