Production time must connect work performed with the order, operation, resource, and cost

Time is operational data before it is cost

Manufacturing time can include setup, run, indirect work, pause, rework, and downtime. Recording only a start and finish may overstate productive hours when work stopped for material, maintenance, inspection, or scheduling. Recording every second without usable categories creates noise.

The model should fit the floor: manual entry, start-stop events, supervisor confirmation, device capture, or integration. The result needs a clear link to employee or resource, work order, operation, date, quantity, and status.

Simor ERP Time Logs

Simor ERP records actual Work Order time and allows it to influence production cost. It connects with Routing, Work Centers, resources, Production Orders, Cost Analysis, and permissions. Forms and approval can be customized to the operating environment.

Rates require care. Logged hours may drive labour cost, machine cost, or both; payroll pay rates and manufacturing cost rates are not always identical and should not be exposed to every production user.

Common data-quality problems

• An operator forgets to stop a running event.
• Two open sessions claim the same person or machine.
• Setup time is spread across the wrong quantity.
• Rework time is mixed into normal production.
• Completed work has no reported good or scrap quantity.
• A correction changes cost without approval history.

Reasonable validations can identify impossible overlaps, extreme duration, missing order context, and completion without required fields.

Example: setup and run variance

A routing expects one hour of setup and ten minutes per unit for a batch of 30. Actual setup takes two hours because tooling requires correction, while run time matches the standard. Separating setup from run time shows the cause and avoids changing the standard run rate based on the wrong evidence.

If only 20 good units are completed and two are scrapped, managers can review time per good unit, remaining work, scrap impact, and forecast completion.

Acceptance tests and analysis

Test overnight work, time zones, breaks, concurrent operations, partial completion, rework, scrap, employee reassignment, rate changes, corrections, and closed orders. Confirm that approved history remains stable when a current resource rate changes.

Useful measures include setup variance, run-time variance, labour efficiency, machine utilization, downtime by reason, rework hours, time per good unit, and unapproved logs. These metrics should support improvement rather than encourage rushed or inaccurate reporting.

Reference concepts: Microsoft guidance on time and attendance registrations.

Compare plan with reality

Continue with cost rollups, scrap control, and manufacturing capabilities.

Who owns production time and rate data

Reliable shop-floor labour recording depends on a defined record and named responsibility. Its minimum evidence includes employee or resource, production order, work order, operation, setup start and stop, run duration, pause reason, good quantity, scrap quantity, rate context, approval, and correction. Information for shop-floor labour recording should originate in the business transaction where possible instead of being reconstructed at month-end.

Responsibility for shop-floor labour recording crosses operators, supervisors, production planning, payroll administration, and cost accounting. Workshops for shop-floor labour recording should identify who creates, reviews, approves, corrects, and closes each record, then establish materiality, tolerance, timing, retention, and escalation rules. Simor ERP can enforce an agreed shop-floor labour recording policy, but software cannot resolve a policy the organization has not defined.

Decisions to document

• allow simultaneous work or prevent overlap
• separate setup, run, and downtime
• assign rework time
• apply labour or machine rates
• approve an extreme duration
• correct time after order completion

Every decision in this labour-capture workflow affects another module or report, so downstream consequences belong in the approved design. Acceptance tests should trace each configured labour record to its source, authorized role, costing effect, and retained evidence.

Time-entry cases to prove on the shop floor

A happy path proves little about shop-floor labour recording. Build test data covering overnight shift, forgotten stop event, parallel operations, partial completion, rate change, closed-order correction. For every labour-recording scenario, record expected status, balance, operational or journal impact, authorized role, correction route, and report result.

Test shop-floor labour recording with realistic volume and multiple users. Check concurrency, duplicate prevention, date and period control, precision, and integration retry behaviour. Reverse or correct selected shop-floor labour recording records and verify that their original history remains available.

Measures worth reviewing

• setup variance
• run-time variance
• time per good unit
• downtime by reason
• unapproved hours
• labour efficiency

Each shop-floor labour recording measure needs an owner, formula, source, refresh expectation, and action threshold. Its dashboard should drill into underlying transactions so managers can explain change. Measurement of shop-floor labour recording should guide correction and improvement rather than encourage convenient status choices.

Turning approved time into cost and learning

shop-floor labour recording does not end when one screen shows Complete. The team receiving shop-floor labour recording needs a trusted status, stable identifiers, dates, quantities or amounts, and a route back to the source. Interfaces should exchange business references that people can investigate, not only technical keys.

Define what happens when shop-floor labour recording fails after an earlier step succeeded. A retry of shop-floor labour recording must not create a duplicate; its timeout must not be interpreted automatically as failure; and its correction must not erase the first attempt. Queued, rejected, partially completed, reversed, and closed shop-floor labour recording states need meanings shared by users and integrations.

Reporting cut-off also matters for shop-floor labour recording. Operational work related to shop-floor effort recording may continue while finance prepares a period result, so posting date, event date, approval time, and effective date should not be treated as interchangeable. Late activity needs a controlled destination and an explanation visible in later review.

Documentation for shop-floor labour recording should include the normal flow, exception ownership, permissions, field definitions, integration dependencies, reports, and recovery steps. Training for shop-floor labour recording should use the same realistic exceptions tested before launch, because users rarely need help only when every input is perfect.