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Work in progress cycle time recording

Tracking time products spend moving through each production stage.
Work-in-progress (WIP) cycle time recording is the practice of tracking how long a product or job spends in the production process from start to completion. It captures timestamps at each process step to measure delays, processing time, and waiting time. This data helps identify bottlenecks, improve workflow efficiency, reduce lead time, and support better production planning and performance monitoring.

Introduction
Work‑in‑progress (WIP) cycle time recording is a fundamental practice in manufacturing and operations management used to measure how long items take to move through a production process while they are still incomplete. It involves capturing time data at key stages—from when work begins on a product until it exits the process or reaches completion. This may include processing time, waiting time between steps, inspections, rework, and transport delays.
By recording WIP cycle time, organizations gain visibility into how work actually flows through their operations, rather than how it is planned to flow. The data helps identify bottlenecks, inefficiencies, and sources of delay that increase lead time and operating costs. It also enables teams to compare actual performance against targets, balance workloads, and prioritize improvement initiatives.
Accurate WIP cycle time recording supports better production planning, capacity utilization, and delivery reliability. Over time, it provides a factual basis for continuous improvement efforts such as Lean manufacturing, Six Sigma, and throughput optimization. Ultimately, understanding WIP cycle time helps organizations improve responsiveness, reduce inventory, and deliver products to customers faster and more predictably.

Feature
Start and end time capture for each process step
Real‑time or event‑based timestamp recording
Tracking of processing, waiting, and transfer time
Visibility of WIP status across production stages
Bottleneck and delay identification
Comparison of actual vs standard cycle time
Historical data for trend and performance analysis
Support for continuous improvement initiatives

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