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Company Dashboard Guide

Overview​

What is the Company Dashboard?​

The Company Dashboard is your central hub for monitoring overall manufacturing performance across your entire operation. It provides high-level insights into key metrics, identifies performance issues, and helps you understand trends over time.

Key Capabilities:

  • Track utilization, OEE, availability, and performance
  • Monitor production volume (good parts, scrap, non-conforming)
  • View live machine status across the shop floor
  • Identify downtime patterns
  • Spot machines performing below baseline
  • Detect operations with slower-than-expected cycle times

Who Uses This:

  • Executives: High-level performance overview
  • Managers: Department and shift analysis
  • Continuous improvement teams: Trend identification
  • Operations leadership: Daily status monitoring

Accessing the Company Dashboard​

Navigation:

  1. Log into MachineMetrics at app.machinemetrics.com
  2. Click Company in the main navigation menu
  3. Dashboard loads with default view (typically "Today")

Company Dashboard Overview

The Company Dashboard provides a comprehensive view of your entire operation, including utilization, OEE, performance, availability, production volume, machines active, machines in production, downtime analysis, and cycle time tracking.

Default View:

  • Shows current day's performance
  • Compares to previous period
  • Displays live machine status

Dashboard Controls​

Date Range Selector​

Available Date Ranges:

  • Today: Current 24-hour shop day
  • Yesterday: Previous 24-hour shop day
  • Last 7 Days: Rolling 7-day window
  • Week to Date: Current week from start
  • Last Week: Previous complete week
  • Month to Date: Current month from start
  • Last Month: Previous complete month
  • Custom Range: Select specific start and end dates

Selecting a Date Range:

  1. Click date range selector (top of dashboard)
  2. Choose preset or select Custom Range
  3. If custom: Pick start date and end date
  4. Click Apply
  5. Dashboard updates with new data

Shift Filter​

Purpose: Filter all metrics to specific shifts.

Using Shift Filter:

  1. Click Shift dropdown
  2. Select one or more shifts:
    • First Shift
    • Second Shift
    • Third Shift
    • Weekend
    • (Or your custom shift names)
  3. Dashboard filters to selected shifts only

Impact:

  • All widgets filter to selected shifts
  • Baseline calculations adjust to shift data
  • Useful for comparing shift performance

Machine Groups Filter​

Purpose: Focus on specific departments or machine types.

Using Machine Groups:

  1. Click Machine Groups dropdown
  2. Select one or more groups:
    • All Machines (default)
    • By department (e.g., CNC, Lathes, Mills)
    • By production line
    • By machine type
  3. Dashboard shows selected groups only

Impact:

  • Narrows focus to relevant machines
  • Baseline adjusts to group-specific data
  • Compare groups side-by-side by switching filters

Tip: Use combination of shift + machine group filters for deep analysis (e.g., "How does the Lathe department perform on second shift?")

Main KPI Metrics​

Metric Cards Overview​

The dashboard displays four primary KPI cards at the top:

  1. Utilization
  2. OEE (Overall Equipment Effectiveness)
  3. Availability
  4. Performance

Each card shows:

  • Current Value: Metric for selected date range
  • Variance from Baseline: Percentage point difference from 6-month median
  • Comparison to Previous Period: Change from last period (e.g., previous week)
  • Visual Indicator:
    • 🟢 Green up arrow = improvement
    • 🔴 Red down arrow = decline
    • ⚪ Gray = no significant change

Company Dashboard KPI card

Utilization​

Definition: Percentage of scheduled time that machines are actively producing.

Formula:

Utilization = (Active Time / Scheduled Time) × 100%

What This Tells You:

  • How effectively you're using available production time
  • Impact of downtime on overall productivity
  • Whether machines are idle during scheduled hours

Example:

  • Current: 75%
  • Baseline: 80%
  • Variance: -5 pp (5 percentage points below typical)
  • vs Previous Week: -2%

Interpretation: Utilization is down 5 points from historical average and dropped 2% from last week. Investigate causes of increased downtime or idle time.

OEE (Overall Equipment Effectiveness)​

Definition: Composite metric combining availability, performance, and quality.

Formula:

OEE = Availability × Performance × Quality

What This Tells You:

  • Overall manufacturing efficiency
  • Combined impact of downtime, speed losses, and quality issues
  • Industry benchmark comparison (world-class OEE ≥ 85%)

Example:

  • Current: 68%
  • Baseline: 72%
  • Variance: -4 pp
  • vs Previous Week: -1%

Interpretation: OEE declined slightly. Drill into Availability, Performance, and Quality widgets to identify root cause.

Availability​

Definition: Percentage of planned production time that equipment is available to operate.

Formula:

Availability = (Operating Time / Planned Production Time) × 100%

What This Tells You:

  • Impact of unplanned downtime
  • Equipment reliability
  • Maintenance effectiveness

Example:

  • Current: 92%
  • Baseline: 94%
  • Variance: -2 pp
  • vs Previous Week: +1%

Interpretation: Availability slightly below baseline but improving from last week. Monitor for sustained improvement.

Performance​

Definition: Ratio of actual production speed to ideal/target speed.

Formula:

Performance = (Actual Cycle Time / Ideal Cycle Time) × 100%

What This Tells You:

  • Whether machines are running at expected speed
  • Impact of minor stoppages and reduced speed
  • Process efficiency

Example:

  • Current: 85%
  • Baseline: 87%
  • Variance: -2 pp
  • vs Previous Week: 0%

Interpretation: Performance 2 points below baseline, stable vs last week. Check for cycle time increases in specific operations.

Production Volume Widget​

Overview​

The Production Volume widget displays total parts produced during the selected time range, broken down by quality.

Displayed Metrics:

  • Total Parts: All parts produced
  • Good Parts: Parts that passed quality checks
  • Scrap: Parts rejected/discarded
  • Non-Conforming: Parts that don't meet specifications (rework candidates)

Visual Display:

  • Large number showing total parts
  • Percentage change vs previous period
  • Stacked bar or pie chart showing breakdown
  • Variance from baseline (if available)

Understanding Production Volume​

Example:

Total Parts: 1,247 (+8% vs previous week)
├─ Good: 1,180 (94.6%)
├─ Scrap: 45 (3.6%)
└─ Non-Conforming: 22 (1.8%)

What This Tells You:

  • Overall production output
  • Quality performance (scrap/non-conforming rates)
  • Week-over-week production trends
  • Whether quality issues are increasing

Action Items:

  • High scrap rate → Investigate quality issues
  • Declining total → Check for downtime or speed losses
  • Non-conforming increase → Review tolerances or inspection

Live Machine Status Wheels​

Machines Active Wheel​

Purpose: Real-time breakdown of machines by execution state.

Categories:

  • Active (Green): Machine is currently cutting/processing
  • Idle (Yellow): Machine is powered on but not in cycle
  • Off (Gray): Machine is powered off or disconnected
  • Unknown (Dark Gray): Status cannot be determined

Display:

  • Donut chart with count in each category
  • Percentage of total machines
  • Updates in real-time (every few seconds)

Machines Active widget

Use Cases:

  • Quick floor status check
  • Identify idle machines for operator assignment
  • Verify machine connectivity
  • Monitor shift start-up (all machines coming online)

Example:

Total Machines: 24
├─ Active: 18 (75%)
├─ Idle: 4 (17%)
├─ Off: 1 (4%)
└─ Unknown: 1 (4%)

Machines in Production Wheel​

Purpose: Real-time breakdown by production status (vs execution state).

Categories:

  • In Production (Green): Active operation assigned and running
  • Ready: Machine ready but no operation started
  • Interrupted: Operation paused or stopped
  • No Operation: No operation assigned

Display:

  • Donut chart with count in each category
  • Percentage of total
  • Real-time updates

Machines in Production Wheel

Difference from Active Wheel:

  • Active wheel = physical machine state (cutting or not)
  • Production wheel = operational state (job/operation status)
  • Machine can be "Active" but "No Operation" if cutting air or test running

Use Cases:

  • Verify operations are properly assigned
  • Identify machines waiting for work
  • Track interrupted operations needing attention
  • Monitor production start-up process

Example:

Total Machines: 24
├─ In Production: 16 (67%)
├─ Ready: 5 (21%)
├─ Interrupted: 2 (8%)
└─ No Operation: 1 (4%)

Top 5 Downtime Pareto​

Overview​

The Top 5 Downtime Pareto widget displays the most common downtime reasons during the selected time range.

Top 5 Downtime Pareto

Display:

  • Horizontal bar chart
  • Top 5 downtime categories by duration
  • "All Other" rollup for remaining categories
  • "Uncategorized" for unclassified downtime
  • Total downtime hours for each category

Example:

1. Setup/Changeover         45.2 hrs  ████████████████░░░░
2. Waiting for Material     32.1 hrs  ██████████████░░░░░░
3. Tooling Issues           28.5 hrs  ████████████░░░░░░░░
4. Maintenance              22.3 hrs  ██████████░░░░░░░░░░
5. Operator Breaks          18.7 hrs  █████████░░░░░░░░░░░
   All Other                35.4 hrs  ██████████████░░░░░░
   Uncategorized            12.8 hrs  ██████░░░░░░░░░░░░░░

Understanding Downtime Data​

Total Downtime Includes:

  • Planned downtime (breaks, PM, changeovers)
  • Unplanned downtime (breakdowns, waiting)
  • Micro-events (< configured threshold)
  • Long events (> configured threshold)

Key Insights:

  • Which issues consume most production time
  • Whether downtime is planned or unplanned
  • Recurring vs one-time issues
  • Opportunities for improvement

Actions:

  • High setup time → Implement SMED (Single-Minute Exchange of Dies)
  • Waiting for material → Improve material flow/logistics
  • Tooling issues → Review tool management process
  • High uncategorized → Improve classification training

Accessing Downtime Report​

Quick Access:

  1. Click "View Report" link at top of widget
  2. Opens full Downtime Report filtered to current date range
  3. Drill into specific categories for detailed analysis

Performance Alerts​

Utilization: Lower than Expected​

Purpose: Automatically identify machines performing below their historical baseline.

What It Shows:

  • Machines with median utilization below 6-month baseline
  • Sorted by highest variance (worst performers first)
  • Only includes machines with "first active time" set

Display Format:

Machine Name          Current    Baseline    Variance
Mill #3               68%        78%         -10 pp
Lathe #7              71%        79%         -8 pp
VMC #12               75%        82%         -7 pp

How to Use:

  1. Review machines in list
  2. Click machine name → opens machine snapshot
  3. View timeline, recent downtime, and trends
  4. Click "Go to machine" → machine overview page
  5. Investigate root causes (downtime categories, cycle time issues, etc.)

Common Causes:

  • Increased downtime frequency
  • Longer downtime events
  • Reduced production speed
  • Shift changes affecting performance
  • New operators learning curve

Note: Machines without "first active time" configured are excluded from this widget. Set first active time in machine settings for accurate baseline calculation.

Cycle Times: Slower than Expected​

Purpose: Identify operations running slower than their historical baseline cycle time.

What It Shows:

  • Operations with median cycle time above 3-month baseline
  • Sorted by highest variance (slowest first)
  • Limited to selected time period (typically < 1 week)

Display Format:

Operation                Machine    Current    Baseline    Variance
Part #1234-A             Mill #3    125s       110s        +15s (13.6%)
Housing Rough            Lathe #7   98s        85s         +13s (15.3%)
Cover Finish             VMC #12    76s        70s         +6s (8.6%)

How to Use:

  1. Review operations in list
  2. Click operation → opens operation details
  3. View cycle time history, trending, and recent runs
  4. Compare to ideal/target cycle time
  5. Investigate causes (tool wear, process changes, etc.)

Common Causes:

  • Tool wear (need replacement)
  • Feed rate or spindle speed reduction
  • Program changes
  • Material hardness variation
  • Machine performance degradation

Actions:

  • Tool wear → Schedule tool changes
  • Process drift → Review and optimize program
  • Material variation → Check material specs
  • Equipment issue → Schedule maintenance

Understanding Baselines​

What is a Baseline?​

A baseline is a historical reference point representing typical performance over a defined period. MachineMetrics uses baselines to:

  • Compare current performance to historical norms
  • Detect performance degradation or improvement
  • Set expectations for machine/operation performance
  • Identify outliers

Company Dashboard Baselines​

Calculation Method:

  • Lookback Period: 6 months of historical data
  • Calculation: Median value per week
  • Result: Median of weekly medians = baseline

Metrics with Baselines:

  • Utilization
  • OEE
  • Availability
  • Performance
  • Production Volume (in some views)

Example Calculation:

Week 1: 78% utilization
Week 2: 82% utilization
Week 3: 75% utilization
...
Week 26: 80% utilization

Baseline = Median of all weekly values = 79%

Why Median (not Average)?

  • Median is more robust to outliers
  • Extreme good/bad weeks don't skew baseline
  • Represents "typical" performance better
  • Less sensitive to seasonal variations

Variance from Baseline​

Displayed As:

  • Percentage points (pp) for percentage-based metrics
  • Absolute values for counts/durations
  • Color-coded indicators (green/red/gray)

Interpreting Variance:

  • Positive variance (green): Current > baseline (good for utilization, OEE, parts)
  • Negative variance (red): Current < baseline (needs investigation)
  • No significant variance (gray): Within normal range

Example:

Current Utilization: 75%
Baseline: 80%
Variance: -5 pp

Interpretation: Utilization is 5 percentage points below typical performance

Machines Page Baselines​

Different Calculation for Cycle Times:

  • Lookback Period: 3 months (vs 6 for company dashboard)
  • Applied To: Individual operations
  • Purpose: Detect process drift at operation level

Why 3 Months?

  • Operations change more frequently than company-wide metrics
  • Shorter window captures recent process improvements
  • More responsive to process changes

How Comparison Works​

Comparison Logic: MachineMetrics compares current period data to the immediately preceding period of equal length.

Examples:

  • Today → compares to previous 24-hour shop day (yesterday)
  • Last 7 Days → compares to prior 7 days (days 8-14 ago)
  • Week to Date → compares to previous week
  • Month to Date → compares to previous month

Displayed As:

  • Percentage change (e.g., "+5%" or "-3%")
  • Arrow indicator (up = increase, down = decrease)
  • Color (green for improvement, red for decline)

Trend Indicators​

Understanding Trends:

Utilization: 78% ↑ +3% vs Previous Week
├─ Current period: 78%
├─ Previous period: 75.7%
└─ Change: +2.3 pp = +3% increase

Interpretation:

  • ↑ +% (green) = Metric improved
  • ↓ -% (red) = Metric declined
  • ⟷ ±0% (gray) = No significant change

What Metrics Show Trends:

  • All main KPI cards (Utilization, OEE, Availability, Performance)
  • Production Volume
  • Downtime totals

Use Cases:

  • Track week-over-week improvement
  • Identify sudden drops requiring immediate attention
  • Validate continuous improvement efforts
  • Communicate progress to stakeholders

Best Practices​

Daily Review Routine​

Morning Review:

  1. Open Company Dashboard
  2. Set date range to "Today"
  3. Check live status wheels:
    • Are machines starting up properly?
    • Any unexpected "Off" or "Unknown" machines?
  4. Review yesterday's performance:
    • Set to "Yesterday"
    • Check main KPIs vs baseline
    • Note any significant variances
  5. Review "Utilization: Lower than expected"
    • Identify machines needing attention
    • Assign follow-up tasks

Weekly Review (30 minutes):

  1. Set date range to "Last 7 Days"
  2. Compare to previous week
  3. Review Top 5 Downtime Pareto:
    • Are top reasons consistent?
    • Any new issues emerging?
  4. Check "Cycle Times: Slower than expected"
    • Schedule tool changes or process reviews
  5. Filter by machine groups:
    • Compare department performance
    • Identify best practices to share
  6. Filter by shifts:
    • Compare shift performance
    • Address shift-specific issues

Filter Strategies​

Department Analysis:

  1. Select single machine group (e.g., "CNC Mills")
  2. Review all KPIs for that group
  3. Compare to company baseline
  4. Identify group-specific improvement opportunities
  5. Repeat for each department

Shift Comparison:

  1. Set date range (e.g., "Last 7 Days")
  2. Select "First Shift" only
  3. Note all KPI values
  4. Switch to "Second Shift"
  5. Compare metrics
  6. Investigate differences (training, staffing, etc.)

Targeted Analysis:

Example: "Why is second shift lathe performance low?"
1. Machine Groups → Lathes
2. Shifts → Second Shift
3. Date Range → Last 7 Days
4. Review KPIs and downtime
5. Click underperforming machines
6. Drill into timeline for root causes

Setting Expectations​

Baseline Interpretation:

  • Baseline = typical performance, not target
  • Being below baseline doesn't mean failure
  • Focus on trends more than absolute values
  • Baseline adjusts over time as performance improves

Realistic Goals:

  • Short term: Return to baseline (if below)
  • Medium term: Exceed baseline by 5-10%
  • Long term: Continuous improvement, baseline rises

Communicating Results:

  • Use variance from baseline to show progress
  • Highlight positive trends (even if below baseline)
  • Provide context for declines (e.g., major maintenance, new products)
  • Celebrate improvements in specific areas

Getting Help​

Before Contacting Support​

Verify:

  1. Date range is correct
  2. Shift/machine group filters are set as intended
  3. Machines have "first active time" configured (for baseline calculations)
  4. Data is appearing for selected time range (not blank widgets)

Check:

  • Machine connectivity (green status in Machines page)
  • Recent system updates or changes
  • Whether issue affects all machines or specific ones

Contact Options​

MachineMetrics Support:

  • Email: MachineMetrics Support
  • Include:
    • Screenshot of Company Dashboard
    • Date range and filters applied
    • Specific question or issue
    • What you expected vs what you're seeing

For Training:

  • Request dashboard walkthrough session
  • Ask about best practices for your industry
  • Schedule advanced analytics training

Next Steps:

Questions? Contact MachineMetrics Support