Configurable Dashboards + New Widgets

The Configurable Dashboards feature is designed to provide a comprehensive and personalized view of your KPIs. With Configurable Dashboards, you can seamlessly mix and match charts, custom reports, and various widgets to create dashboards that cater to your specific needs. This reduces the need for manual data compilation and ensures you have all the critical insights at your fingertips for data-driven decision-making.

Navigate to the Dashboards are of MachineMetrics via the sidebar and choose Create Dashboard in the upper right. After giving your dashboard a name, click the Add Widget button to display the gallery of available widgets. Choose the widget that you’d like to include and configure it using the options presented. Widgets can be resized and positioned to your liking and many widgets can be added to a dashboard to give you all the information you need in one view. Dashboards can further be configured to be sent out on a regular basis via email - putting it right in your inbox when you need it.

At launch, there were 4 widgets available. We are expanding that list with 8 new widgets and many more to follow. Here’s a breakdown of these 8 new widgets:

Multi-Plant Comparison Widget

View Utilization, OEE, Availability, or Parts Goal for each plant in your enterprise. Instantly compare performance and spot improvement opportunities across locations. Enables the ability to drill down to a plant or machine to spot a problem.

The Multi-Plant Comparison Widget enables manufacturing enterprises to compare key performance metrics (Utilization, OEE, Availability, or Parts Goal) across multiple plant locations within a customizable date range, allowing decision-makers to quickly identify performance gaps and improvement opportunities. Users can select specific locations from their enterprise network, choose their preferred KPI, and set custom performance thresholds to visually highlight underperforming plants. This visualization tool is particularly valuable for operations executives and plant managers who need to monitor multi-site manufacturing performance at a glance, identify best practices from top-performing locations, and drill down to specific plants or machines when performance issues are detected.

Multi-Region Utilization Widget

Show Utilization by region or group of plants. It's ideal for identifying geographic trends, aligning regional strategies, and spotlighting high or low-performing clusters—enabling enterprise leaders to act decisively with clarity and speed.

The Multi-Region Utilization Widget visualizes utilization metrics across different geographic regions or plant groupings, allowing enterprise leaders to compare performance, identify trends, and spot high or low-performing clusters. Users can customize the analysis by selecting from various date ranges (from today to year-to-date), defining specific location groups for comparison, and setting performance thresholds with goal, warning, and failure percentages that are visually color-coded for quick assessment. This visualization tool is particularly valuable for executives and regional managers who need to make data-driven decisions about resource allocation, identify operational inefficiencies across locations, and develop targeted improvement strategies based on geographic performance patterns.

Continuous Improvement Tracker

Highlight measurable improvements from the moment goals are set.

The Continuous Improvement Tracker widget visualizes performance metrics like Utilization, OEE, Availability, Quality, and Performance against set goals, allowing users to monitor progress from a specific start date across selected machines or machine groups and shifts. It helps manufacturing teams identify improvement trends, track goal achievement, and pinpoint areas needing attention by displaying the gap between current performance and targets. This experimental tool is particularly valuable for production managers implementing continuous improvement initiatives who need to demonstrate measurable progress toward operational excellence goals over time.

Single KPI Metric

Quick visualization of a single metric for a certain timeframe.

The Single KPI Metric widget provides a focused visualization of critical manufacturing performance indicators like utilization rate, OEE, availability, quality, or performance for a customizable timeframe, with options to display the data as a dial gauge or simple value. Users can filter metrics by specific machine groups, individual machines, and shifts while customizing the display period from daily to yearly views, making it ideal for operations managers who need quick visibility into key performance metrics across their production environment. This experimental widget delivers immediate insight into manufacturing performance, allowing supervisors and managers to quickly assess equipment effectiveness and identify potential bottlenecks or issues without navigating through complex dashboards.

Top Five

Highlight the top performers and assets needing improvement across your machines and machine groups, enabling data-driven decision making and performance optimization.

The "Top Five" widget highlights top performers and underperforming assets across manufacturing equipment by displaying comparative performance metrics like utilization, OEE, availability, quality, and performance in either a tile grid or leaderboard format. Users can filter by various time periods (from today to year-to-date), compare individual machines or machine groups, and choose to display either top performers or assets needing attention. This widget provides valuable insights for production managers and operators to quickly identify both successful operations and problem areas, enabling data-driven decision making for performance optimization and resource allocation across manufacturing facilities.

Downtime Pareto

Identify and prioritize the most impactful causes of machine downtime through interactive visualization of duration and frequency.

The Downtime Pareto widget visualizes machine downtime causes in a Pareto chart format, allowing users to quickly identify the most significant contributors by either total duration or frequency (instance count) across various time periods ranging from today to year-to-date. This experimental visualization tool helps manufacturing teams prioritize maintenance efforts and process improvements by highlighting which downtime causes have the greatest impact on operations. The widget is particularly valuable for maintenance managers, production supervisors, and continuous improvement teams who need to make data-driven decisions about where to focus resources to maximize uptime and productivity.

Goal Tracker

Track performance against goals and historical baselines, enabling teams to monitor progress, identify trends, and maintain accountability for operational targets.

The Goal Tracker widget enables manufacturing teams to monitor operational performance metrics (such as Utilization, OEE, Availability, Quality, and Performance) against defined targets, comparing current results with historical baselines across customizable time periods. Users can configure specific goal targets, select different time frames for analysis, and filter data by machine groups, individual machines, or shifts to identify performance trends and accountability gaps. This experimental widget provides valuable insights for production managers seeking to track progress toward operational targets, identify underperforming assets or shifts, and make data-driven decisions to improve manufacturing efficiency.

Startup Delay

Track wasted time at shift start before CNC machines go active. Filter, group, and visualize with charts or hero metrics. Add a burden rate to see cost impact. Show data as hours or dollars lost.

The Startup Delay widget tracks and visualizes time wasted at the beginning of shifts before CNC machines become productive, allowing manufacturing teams to identify inefficiencies across machines, shifts, and days of the week. Users can calculate average or total delays, view data in hours or monetary value (with customizable hourly rates), filter by specific machines or shifts, and group results in various ways to identify patterns or problem areas. This experimental tool helps operations managers quantify productivity losses during machine startups, enabling targeted improvements to reduce wasted time and associated costs in manufacturing environments.