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Job Tracking Guide

Overview​

What is Job Tracking?​

Job Tracking provides real-time visibility and control over production jobs by connecting work orders, machines, operators, and parts in a unified system that delivers accurate, up-to-the-minute production intelligence.

Key Capabilities:

  • Track actual parts produced against work order quantities in real-time
  • Monitor job progress across all machines from a single dashboard
  • Automatically capture production counts directly from machine controls
  • Track setup and transition time between jobs
  • Document scrap with reason codes for quality analysis
  • Generate ERP-compatible labor records with actual production times
  • Create complete production genealogy (parts → machines → operators → time)

Who Uses Job Tracking:

  • Operators: Manage active jobs, report scrap, log issues via tablet
  • Supervisors: Monitor job progress, identify at-risk jobs, prioritize work
  • Production Managers: Analyze job performance, track efficiency, report completions
  • ERP Managers: Automate labor data entry, sync production with business systems
  • Quality Managers: Track quality issues by job, analyze scrap patterns
  • Customer Service: Provide accurate job status updates to customers
note

This guide covers job tracking generally. On MES-enabled machines, job selection, scrap reporting and job completion all happen through the labor ticket workflow in ShopPulse, which works differently from what's described here. See How to Use ShopPulse on MES-Enabled Machines for that workflow.

Key Features​

Real-Time Job Progress​

Track actual parts produced against work order quantities as production happens:

  • Parts Produced: Live count from machine
  • Target Quantity: Work order goal
  • Completion %: Real-time progress indicator
  • Estimated Time to Complete: Based on actual cycle times

Automated Part Counting​

Capture production counts directly from machine controls without manual entry:

  • Reads part count from CNC controller
  • Updates in real-time as parts complete
  • No operator data entry required
  • Accurate counts eliminate errors

Job Setup & Transition Tracking​

Monitor and optimize the critical time between jobs:

  • Setup Time: Time to prepare machine for new job
  • Transition Time: Time between last part of previous job and first part of new job
  • Comparison to Standard: Actual vs. expected setup time
  • Improvement Opportunities: Identify jobs with excessive setup

Operator Dashboard (ShopPulse)​

Tablet-based interface for operators to manage jobs:

  • Current Job Display: Part number, operation, target quantity
  • Parts Progress Bar: Visual completion indicator
  • Report Scrap: One-tap scrap logging with reason codes
  • Job Instructions: View work order details and routing information
  • Next Job Info: Upcoming work order details (part number, operation, target quantity) shown when starting a new job

Visual Progress Indicators​

Color-coded status shows job health at a glance:

  • Green: On track to meet target
  • Yellow: Behind schedule but recoverable
  • Red: At risk of missing deadline
  • Gray: Not started or paused

Job-Level Analytics​

Analyze performance metrics by specific job:

  • Cycle Time: Actual vs. target cycle time per part
  • OEE by Job: Availability, performance, quality for each job
  • Efficiency %: Overall job efficiency compared to standard
  • Quality %: Good parts vs. total parts for job
  • Scrap Rate: Rejected parts as percentage of total

For Operators: Using ShopPulse​

Accessing the Operator Dashboard​

Hardware:

  • Tablet mounted at machine (recommended: 10-13" tablet)
  • Touchscreen optimized interface
  • Access via web browser (no app install required)

Login:

  1. Open browser to MachineMetrics URL
  2. Enter operator credentials
  3. Dashboard loads with assigned machine(s)

Viewing Current Job​

Job Card Displays:

  • Part Number: What you're producing
  • Operation: Current operation (e.g., OP10, OP20)
  • Work Order: Customer order number
  • Target Quantity: How many parts needed
  • Parts Produced: Real-time count from machine
  • Progress Bar: Visual completion indicator
  • Cycle Time: Current cycle time vs. target

Starting a New Job​

Automatic Job Start (with APM — Auto Production Monitoring):

  1. Load new program on machine
  2. Machine starts running
  3. System detects program change
  4. New job automatically created
  5. Job details populate from ERP (if integrated)

Manual Job Start (ShopPulse):

  1. Tap "Start New Job" on tablet
  2. Select job from list (pulled from ERP)
    • Or scan barcode on work order
    • Or search by part number/work order
  3. Confirm operation and quantity
  4. Tap "Start"
  5. Job begins tracking
note

On MES-enabled machines, work is selected in Setup mode and the move into production happens through the setup labor ticket — the details differ depending on whether the machine runs one job at a time or several. See How to Use ShopPulse on MES-Enabled Machines.

Reporting Scrap​

When to Report:

  • Part fails quality inspection
  • Machine error ruins part
  • Setup/first article rejection
  • Rework required

How to Report:

  1. Tap "Report Scrap" button on job card
  2. Enter quantity of scrapped parts
  3. Select reason code:
    • Machine Error
    • Tooling Issue
    • Material Defect
    • Programming Error
    • Operator Error
    • Quality Issue
    • Setup/First Article
    • Other (with notes)
  4. Add notes (optional but recommended)
  5. Tap "Submit"

What Happens:

  • Scrap count updates on dashboard
  • Part count adjusts (if "Remove Rejects from Part Count" enabled)
  • Quality report captures event
  • Supervisor notified (if alerts configured)
  • Data flows to ERP (if labor ticketing enabled)
note

On MES-enabled machines, rejects are reported on the labor ticket submission form — quantity plus a required reject reason — rather than through a separate scrap action. Reject counts do not reduce the parts-made figure there: every "made" number includes rejects, and only order progress counts good parts.

Viewing Next Job​

The next ("next up") job for a machine is shown when starting a new job. When an operator begins a new run and selects the operation, the upcoming work order details are presented so the operator can confirm what is next:

  • Part number
  • Operation
  • Target quantity
note

There is currently no swipe gesture or "Next Job" button to preview the next job while the current job is still running. Next-job information is only available when starting a new job — mid-run preview is not available in the current operator interface.

For Supervisors: Monitoring Job Progress​

Job Status Dashboard​

Real-Time View of All Jobs:

Access: Dashboards → Production → Job Status

Dashboard Shows:

  • All active jobs across shop floor
  • Machine assignment
  • Parts produced vs. target
  • Completion percentage
  • Job health indicator (color-coded)
  • Estimated time to complete

Sorting Options:

  • By machine
  • By due date
  • By completion %
  • By job health (red → yellow → green)

Use Cases:

  • Morning production meetings: Review overnight progress
  • Shift handovers: Communicate job status to incoming shift
  • Prioritization: Identify which jobs need immediate attention
  • Resource allocation: Reassign operators or machines as needed

Identifying At-Risk Jobs​

Red Status Indicators:

  • Job significantly behind schedule
  • Parts produced well below target
  • Excessive scrap rate
  • Setup time exceeding standard

Actions to Take:

  1. Investigate: Check machine timeline for downtime patterns
  2. Support: Send additional operator or maintenance support
  3. Expedite: Prioritize tooling, materials, or fixtures
  4. Communicate: Update customer service on revised ETA
  5. Escalate: Notify production manager if unrecoverable

Job Transition Monitoring​

Track Time Between Jobs:

  • Transition Start: Last part of previous job completes
  • Transition End: First part of new job starts
  • Duration: Total transition time
  • Comparison: Actual vs. expected setup time

Optimization Opportunities:

  • Jobs with consistently long transitions
  • Machines with excessive setup time
  • Operators needing additional training
  • Tooling or fixturing improvements

For Managers: Job Analytics​

Job Performance Reports​

Access: Reports → Job Performance

Metrics Available:

  • Job Duration: Total time from start to completion
  • Cycle Time Analysis: Actual vs. target by job
  • OEE by Job: Availability, performance, quality
  • Setup Efficiency: Setup time actual vs. standard
  • Quality Rate: Good parts % by job
  • On-Time Completion: Jobs completed by target date

Grouping Options:

  • By Part Number
  • By Machine
  • By Operator
  • By Work Order
  • By Customer
  • By Time Period (day, week, month)

Use Cases:

  • Identify most/least efficient jobs
  • Compare performance across similar parts
  • Justify process improvements
  • Customer-specific performance analysis
  • Operator performance evaluation

Cost Analysis by Job​

Job Costing Metrics:

  • Labor Cost: Actual labor hours × labor rate
  • Machine Time Cost: Machine hours × machine hourly rate
  • Material Cost: Parts produced × material cost per part
  • Scrap Cost: Rejected parts × material cost
  • Total Job Cost: Sum of all costs

Comparison:

  • Actual cost vs. estimated cost (from ERP)
  • Variance analysis (over/under budget)
  • Cost per good part

Use Cases:

  • Profitability analysis by customer or part
  • Quote accuracy evaluation
  • Process improvement ROI calculation
  • Pricing strategy adjustments

Job Lifecycle​

1. Job Creation​

Automated (ERP-Driven):

  • ERP releases work order
  • MachineMetrics imports work order data:
    • Work order number
    • Part number
    • Operation routing
    • Target quantity
    • Due date
    • Standard cycle time
  • Job appears in "Available Jobs" queue
  • Operator selects from list when ready

Manual (APM — Auto Production Monitoring):

  • Machine starts running new program
  • System detects program change
  • Creates new job automatically
  • Extracts part info from program header
  • Job tracking begins immediately

Manual (Operator-Initiated):

  • Operator taps "Start New Job"
  • Enters part number and quantity
  • Job begins tracking

2. Job In Progress​

Real-Time Tracking:

  • Parts count increments with each cycle
  • Cycle time calculated and compared to target
  • Downtime events linked to specific job
  • Scrap tracked with reason codes
  • Labor time automatically accumulated

Operator Actions:

  • View current progress
  • Report scrap as it occurs
  • Log quality issues
note

On MES-enabled machines, there is no mid-production "request inspection" or "pause job" action. First Article Inspection is offered when the operator submits a setup ticket as Complete, and only on machines that run one job at a time — see First Article Inspection. To step away from a job mid-run, submit the labor ticket as Incomplete, or pull the job off the machine.

3. Job Completion​

Automatic Completion:

  • Target quantity reached
  • System marks job complete
  • Labor ticket closes
  • Data syncs to ERP (if integrated)

Manual Completion:

  • Operator taps "Complete Job"
  • Confirms final quantity
  • System marks complete
note

On MES-enabled machines, completion is always operator-driven: the operator submits the labor ticket and marks the job Complete. Reaching the target quantity does not close a job on its own. If good parts are below the required quantity, the operator is asked to confirm before completing.

Completion Data Captured:

  • Total parts produced (good + scrap)
  • Total labor time
  • Total machine time
  • Average cycle time
  • OEE for job
  • All downtime events
  • All scrap events
  • Operator(s) who worked on job

4. Post-Job Analysis​

Available in Reports:

  • Job performance summary
  • Cycle time analysis
  • Downtime breakdown
  • Quality summary
  • Cost analysis
  • Comparison to standard

Automated Part Counting​

How It Works​

Controller Integration:

  • MachineMetrics reads part count directly from CNC controller
  • Part count increments automatically when machine completes cycle
  • No operator data entry required

Supported Signals:

  • M30 counter (Haas, Fanuc)
  • Part count register (Mazak, Okuma)
  • Cycle complete signal (MTConnect)
  • Custom part count variable (via adapter scripts)

Configuration​

Machine Settings:

  1. Navigate to Machine Settings → Data Mapping
  2. Ensure part count data item is mapped as "PartCount"
  3. Navigate to Machine Settings → Data Rules
  4. Select correct part counter in "Select Part Count Metric" dropdown
  5. For machines with multiple counters, select primary counter only

Validation:

  1. Start production run
  2. Monitor part count on operator tablet
  3. Verify count increments with each cycle
  4. Compare to machine's counter display (should match)

Virtual Part Counter (VPC)​

For machines without reliable part counters:

Labor Ticketing​

What is Labor Ticketing?​

Labor Ticketing automatically generates labor records from actual production times, eliminating manual time entry.

note

Labor ticketing works both with and without a live ERP integration. On ERP-connected accounts, labor tickets are written to your ERP. On accounts without a live ERP integration, work orders are imported via CSV/file and labor tickets close in MachineMetrics only — there is no write-back to an external system.

Data Captured:

  • Work order number
  • Operation number
  • Machine ID
  • Operator ID
  • Start time
  • End time
  • Duration (hours)
  • Parts produced (good + scrap)

Integration with ERP​

Supported ERP Systems:

  • Epicor Kinetic
  • Infor Visual
  • Infor XA
  • Infor Syteline
  • JobBoss²
  • Other ERPs via API

Data Flow:

  1. Job starts in MachineMetrics (manual or ERP-driven)
  2. Labor time accumulates as job runs
  3. The operator submits the labor ticket
  4. The ticket is closed out in the ERP with actual times and parts
  5. ERP updates with actual labor hours and parts produced
note

On MES-enabled machines, an unsubmitted labor ticket is freely correctable by the operator. Matching a program to a job, verifying that match, reassigning a job, splitting or merging tickets all happen in MachineMetrics. Once submitted, a ticket is closed in the ERP, read-only in MachineMetrics, and corrections must be made ERP-side. When the ticket opens in the ERP depends on how the machine selects jobs: where the operator selects the job, starting it opens the ticket; where the program selects the job, the ticket is opened and closed at submission.

Manual Labor Ticket Adjustments​

When Needed:

  • Operator forgot to log out
  • Job interrupted by unplanned downtime
  • Split shift (two operators)
  • Correction required

How to Adjust:

  1. Navigate to My Apps → ERP Data Studio (New) → Labor Tickets
  2. Find the labor ticket for the job
  3. Click Edit to modify:
    • Start/end times
    • Duration
    • Operator assignment
    • Parts produced
  4. Add notes explaining the adjustment
  5. Click Save — the adjusted ticket re-syncs to ERP

Deleting a Labor Ticket:

MachineMetrics and the ERP (Infor Visual) do not cascade deletes:

  • Deleting a labor ticket in MM does not delete it in Visual
  • Deleting a ticket in Visual does not delete it in MM
  • To fully delete a ticket: delete it in MM and then in Visual
note

In practice, deleting the ticket in Visual alone is usually sufficient. Only a change to that labor ticket's data (for example, updating the clock-in time) would cause it to resync back into MM.

Confirming Sync:

A labor ticket has synced to Visual when its Ticket ID column in ERP Data Studio is populated. The Ticket ID is the unique identifier returned from Visual.

Access Required: Manager or Executive role

Scrap Tracking​

Scrap Reason Codes​

Default Reason Codes:

  • Machine Error
  • Tooling Issue
  • Material Defect
  • Programming Error
  • Operator Error
  • Quality Issue
  • Setup/First Article
  • Other

Custom Reason Codes:

  • Create company-specific codes in Settings → Quality → Reject Reasons
  • Examples:
    • "Tool Wear"
    • "Coolant Issue"
    • "Fixture Problem"
    • "Inspection Failure"

Scrap Reporting Workflow​

Operator Reports Scrap:

  1. Tap "Report Scrap" on job card
  2. Enter quantity (e.g., 5 parts)
  3. Select reason code
  4. Add notes (optional)
  5. Tap "Submit"

Data Captured:

  • Timestamp
  • Machine
  • Job/work order
  • Operator
  • Quantity scrapped
  • Reason code
  • Notes
  • Part number
  • Operation

Scrap Data Used In:

  • Quality reports (Pareto analysis)
  • Job performance analysis
  • OEE quality component
  • Cost analysis (scrap cost)
  • Continuous improvement initiatives

Quality Reports​

Access: Reports → Quality Report

Scrap Analysis:

  • Pareto Chart: Top scrap reasons by quantity
  • Trend Analysis: Scrap over time
  • By Machine: Which machines have highest scrap
  • By Part: Which parts have highest reject rate
  • By Reason: Root cause analysis

Use Cases:

  • Identify chronic quality issues
  • Justify tooling or process improvements
  • Track scrap reduction initiatives
  • Operator training needs identification

Production Genealogy​

What is Production Genealogy?​

Production Genealogy creates complete traceability by connecting:

  • Specific parts produced
  • Machine that produced them
  • Operator who ran the job
  • Time period of production
  • Work order and customer
  • Materials used (if tracked)
  • Tooling used (if tracked)
  • Quality results (good vs. scrap)

Use Cases​

Quality Traceability:

  • Customer reports defect
  • Trace back to specific production run
  • Identify machine, operator, time period
  • Check for patterns (same machine, same operator, same time)
  • Investigate root cause

Recall Management:

  • Material supplier issues recall
  • Query: Which parts used recalled material?
  • Identify all affected work orders
  • Notify customers
  • Provide documentation for audit

Process Validation:

  • Regulatory requirement to prove process control
  • Show complete history for sample parts
  • Document machine, operator, times, inspections
  • Demonstrate traceability for audit

Continuous Improvement:

  • Identify best-performing operator-machine combinations
  • Analyze: Why does Operator A produce fewer rejects on Machine 1?
  • Replicate best practices across team

Accessing Genealogy Data​

Reports → Production Report:

  • Filter by work order or date range
  • Group by machine, operator, part
  • Export to CSV for detailed analysis

Job Details View:

  • Navigate to Production → Jobs
  • Click specific job
  • View complete history:
    • Start/end times
    • Operators assigned
    • Machine used
    • Parts produced (good + scrap)
    • Downtime events
    • Quality events
    • Cycle times

Integration with ERP​

Work Order Import​

From ERP to MachineMetrics:

  • Work order number
  • Part number and description
  • Operation routing (OP10, OP20, etc.)
  • Target quantity
  • Due date
  • Standard cycle time
  • Standard setup time
  • Customer information

Frequency:

  • Scheduled sync (typically every 5-15 minutes, configurable)

Operator Experience:

  • Opens ShopPulse on tablet
  • Sees list of available work orders
  • Selects work order to start
  • All details pre-populated (no manual entry)

Production Completion Sync​

From MachineMetrics to ERP:

  • Work order number
  • Operation completed
  • Quantity completed (good parts)
  • Quantity scrapped
  • Labor hours (actual)
  • Completion timestamp
  • Machine ID
  • Operator ID

Frequency:

  • Scheduled sync (typically every 5-15 minutes)
  • Or batch (end of shift, daily)

ERP Updates:

  • Work order status advances
  • Inventory updated with completed parts
  • Labor costs posted
  • Work order closed (if final operation)

Bi-Directional Benefits​

For Operations:

  • Single source of truth (ERP drives shop floor)
  • Eliminates duplicate data entry
  • Real-time production visibility in ERP
  • Accurate labor costing

For Finance:

  • Actual costs replace standard costs
  • Improved job costing accuracy
  • Faster month-end close
  • Better project profitability analysis

For Planning:

  • Real-time capacity visibility
  • Accurate lead time estimation
  • Better promise dates to customers
  • Data-driven scheduling

Best Practices​

For Operators​

  1. Report scrap immediately: Don't wait until end of shift
  2. Use reason codes accurately: Helps identify root causes
  3. Add notes for unusual events: Context helps troubleshooting
  4. Start jobs promptly: Minimize transition time
  5. Prepare for the next job at job start: Review upcoming work order details when beginning each new run
  6. On MES machines, review before submitting: Submission is the only step that can't be undone from ShopPulse

For Supervisors​

  1. Monitor job status dashboard frequently: Catch issues early
  2. Investigate red status jobs immediately: Don't wait for crisis
  3. Track transition times: Identify setup improvement opportunities
  4. Review scrap reports weekly: Look for patterns
  5. Communicate with incoming shift: Use job status as handover tool

For Managers​

  1. Set realistic cycle time targets: Based on actual data, not guesses
  2. Review job performance monthly: Identify trends and outliers
  3. Use data for continuous improvement: Focus on biggest opportunities
  4. Standardize on best practices: Replicate high-performing approaches
  5. Track on-time completion rate: Key metric for customer satisfaction

Data Quality​

To Ensure Accurate Job Tracking:

  1. Configure APM properly:

    • Use program header or custom data item
    • Test with several jobs before full rollout
    • Adjust regex patterns as needed

  2. Train operators thoroughly:

    • How to start jobs
    • How to report scrap
    • When to pause jobs
    • How to log issues

  3. Validate part counts:

    • Spot-check against manual counts
    • Ensure correct counter selected in Data Rules
    • Use Virtual Part Counter if controller counts unreliable

  4. Audit labor tickets:

    • Review for unusual durations
    • Correct operator login/logout mistakes
    • Adjust as needed before ERP sync

  5. Review job completion data:

    • Check for jobs stuck "In Progress"
    • Ensure jobs close when complete
    • Investigate incomplete data

Troubleshooting​

Jobs Not Appearing for Operators​

Possible Causes:

  • ERP integration not configured
  • Work orders not released in ERP
  • Work orders not imported via CSV/file (on no-ERP accounts)
  • Machine not assigned to machine group
  • Operator doesn't have permission

Solutions:

  1. Check ERP connector status (Settings → Integrations)
  2. Verify work orders exist in ERP
  3. On no-ERP / MES-only accounts: confirm work orders were imported via CSV/file; contact your SDM if you need to configure the file-import path
  4. Confirm machine assignment in Assets → Machines
  5. Check operator role permissions

Parts Not Counting​

Possible Causes:

  • Part count data item not mapped
  • Wrong counter selected in Data Rules
  • Machine connectivity issue
  • Part count metric set incorrectly

Solutions:

  1. Navigate to Machine Settings → Data Mapping
    • Verify part count data item mapped as "PartCount"
  2. Navigate to Machine Settings → Data Rules
    • Verify correct counter selected
  3. Check Machine Timeline for data gaps
  4. Consider enabling Virtual Part Counter if controller unreliable

Labor Tickets Not Reaching the ERP​

Possible Causes:

  • The ticket hasn't been submitted yet (labor lands in the ERP when the operator submits, not while the work is in progress)
  • ERP connector not configured for labor tickets
  • Labor ticket data incomplete
  • ERP field mapping issue
  • ERP credentials expired

Solutions:

  1. On MES machines, confirm the operator has submitted the ticket
  2. Check ERP connector configuration (Settings → Integrations)
  3. Verify labor ticket has all required fields
  4. Review field mapping in ERP Data Studio
  5. Test ERP connection credentials

Scrap Not Appearing in Reports​

Possible Causes:

  • Scrap reported to wrong job
  • Date filter excluding scrap events
  • Scrap reason code not configured
  • Report permissions issue

Solutions:

  1. Check job details to verify scrap recorded
  2. Adjust report date range
  3. Verify scrap reason codes exist (Settings → Quality → Reject Reasons)
  4. Confirm user has Manager or Executive role

Jobs Stuck "In Progress"​

Possible Causes:

  • Operator didn't complete job
  • Machine connectivity lost before completion
  • Target quantity never reached
  • Job manually paused and forgotten

Solutions:

  1. Manually complete job (Production → Jobs → Complete)
  2. Adjust final quantity if needed
  3. Add notes explaining why completion required
  4. Train operators on proper job completion

Questions? Contact support@machinemetrics.com