Overview
The Utilization calculator analyzes how efficiently resources, machines, stations, or departments are being used in your manufacturing or operational processes. It calculates the percentage of time each category is actively working compared to the total process duration, helping you identify underutilized capacity and potential bottlenecks.
Common Uses
- Monitor machine and equipment utilization to optimize production capacity
- Identify underutilized workstations that could handle additional workload
- Detect overutilized resources that may be creating bottlenecks
- Compare utilization rates across different departments or production lines
- Support capacity planning decisions with data-driven utilization insights
- Evaluate the efficiency of resource allocation in manufacturing processes
Settings
Category Attribute: Select the attribute that defines the resource category you want to analyze (e.g., 'Station', 'Machine', 'Resource', 'Department'). This attribute groups your process events into distinct categories for utilization analysis. The calculator will compute how much time each category was actively working.
Note: The attribute you select must be either a case-level or event-level attribute containing categorical data (text, boolean, or numeric values).
Examples
Example 1: Manufacturing Station Utilization
Scenario: A manufacturing plant has five production stations (Assembly, Testing, Packaging, Quality Control, and Shipping). You want to understand which stations are underutilized and which are running at full capacity to make informed decisions about resource allocation.
Settings:
- Category Attribute: Station
Output:
The calculator displays a table with the following columns:
- Category: The station name
- Utilization: The utilization ratio (e.g., 0.85 represents 85% utilization)
- Total Active Time: The total time the station was actively working
Example results:
| Station | Utilization | Total Active Time |
|---|---|---|
| Testing | 0.92 | 147 days |
| Assembly | 0.88 | 141 days |
| Quality Control | 0.75 | 120 days |
| Packaging | 0.62 | 99 days |
| Shipping | 0.45 | 72 days |
Insights: Testing and Assembly stations are running at near-capacity (92% and 88%), indicating they may become bottlenecks during peak periods. The Shipping station shows only 45% utilization, suggesting it has significant spare capacity that could handle increased throughput from upstream improvements. Quality Control at 75% has moderate headroom for additional work.
Action Items:
- Consider adding capacity to Testing and Assembly to prevent bottlenecks
- Investigate if Shipping resources could be reallocated or used for other tasks
- Monitor Quality Control as production volume increases
Example 2: Production Line Resource Efficiency
Scenario: A production facility operates three parallel production lines (Line A, Line B, Line C). Management wants to evaluate which line is being used most efficiently and identify opportunities for better load balancing.
Settings:
- Category Attribute: Production Line
Output:
| Production Line | Utilization | Total Active Time |
|---|---|---|
| Line A | 0.95 | 342 days |
| Line B | 0.78 | 281 days |
| Line C | 0.58 | 209 days |
Insights: Line A is running at 95% utilization, indicating it's operating near maximum capacity with little room for additional orders. Line B at 78% is well-utilized but has some buffer capacity. Line C at 58% shows significant underutilization - nearly half of available production time is idle.
Action Items:
- Investigate why Line C is underutilized (maintenance issues, skills gaps, scheduling problems, or insufficient demand)
- Consider redistributing work from Line A to Line C to balance capacity and reduce strain on Line A
- Evaluate whether Line C could be temporarily shut down during low-demand periods to reduce operational costs
Example 3: Department Workload Analysis
Scenario: A service organization has multiple departments (Customer Service, Technical Support, Billing, and Administration). Leadership wants to understand departmental workload distribution to support staffing decisions.
Settings:
- Category Attribute: Department
Output:
| Department | Utilization | Total Active Time |
|---|---|---|
| Technical Support | 0.89 | 226 days |
| Customer Service | 0.82 | 208 days |
| Billing | 0.71 | 180 days |
| Administration | 0.55 | 140 days |
Insights: Technical Support shows high utilization at 89%, suggesting the team is working close to capacity and may experience delays during demand spikes. Customer Service at 82% is well-utilized with reasonable buffer capacity. Administration at 55% indicates significant idle time or capacity for additional responsibilities.
Action Items:
- Hire additional Technical Support staff or cross-train other departments to provide backup during peak periods
- Assess whether Administration's lower utilization reflects seasonal patterns, inefficient processes, or an opportunity to consolidate roles
Output
The calculator produces a data table with three columns:
- Category: The distinct values from your selected attribute (e.g., station names, production lines, departments)
- Utilization: The utilization ratio expressed as a decimal (0.0 to 1.0+), where 0.75 means 75% utilization. Values above 1.0 can occur when resources handle overlapping work.
- Total Active Time: The cumulative time this category was actively working, shown as a time duration
You can visualize this output as:
- Grid view: Tabular format with sortable columns
- Bar chart: Visual comparison of utilization rates across categories
- Interactive drill-down: Click on any category to filter your data and explore cases handled by that specific resource
This documentation is part of the mindzie Studio process mining platform.