Inspection queue capacity
CJ Ackley | Industrial | Project brief

STATUS
Capacity brief; time-study data needed. Detailed design and analysis pending.

THE PROBLEM
An inspection station may keep up on average and still build a queue during short arrival bursts or rework. This study compares staffing, buffer space, and routing rules using a discrete-event model of one inspection cell.

DESIGN QUESTION
Which operating change reduces waiting without moving the bottleneck elsewhere?

SCOPE
- Represent arrivals, inspection times, shift breaks, and a rework loop.
- Compare one or two inspectors, finite buffers, and dispatch rules.
- Report throughput, waiting-time distributions, work in process, and utilization.

CONSTRAINTS
System: One bounded inspection cell with an explicit upstream interface
Inputs: Observed timing data or clearly labeled hypothetical scenarios
Routing: Defined acceptance and rework rules
Resources: Available staff, breaks, and physical queue space

ENGINEERING DECISIONS (PROPOSED)
Waiting-time distributions and unfinished work
Compare staffing and dispatch policies using matched arrival scenarios, multiple seeds, and tail waiting times. Track unfinished work at shift end so a policy cannot look good merely by deferring difficult items.

ALTERNATIVE
An average-rate capacity calculation is quick and useful as a reference, but misses bursts, finite buffers, breaks, and rework.

TRADEOFF
More detailed inputs increase the uncertainty in the model. Keep hypothetical timing distributions visible and test whether the recommendation changes when they vary.

PROPOSED TOOLS AND METHODS
Queue simulation, Seeded replications, Confidence intervals

VERIFICATION SCENARIO (NOT YET RUN)
A burst arrives just before a scheduled break
Replay the same arrival streams under one and two inspectors, including rework and a finite queue. Carry or account for every job remaining at shift end.

PASS CONDITION
Arrivals reconcile with completed, rejected, and remaining work. Compare throughput and waiting-time distributions without silently dropping unfinished jobs.

EVIDENCE TO RETAIN
A reproducible seed set, simple reference cases, paired policy comparisons with uncertainty intervals, and a job-level event trace.

MEASUREMENT AND LIMITS
Define warm-up, run horizon, and shift-boundary treatment before collecting outputs. An operational recommendation remains conditional on the input data and physical staffing constraints.

COMPLETION CRITERIA (PLANNED)
- Conservation and deterministic reference cases pass.
- Policy comparisons include replication uncertainty and input sensitivity.
- The recommendation explains both the queue effect and the staffing or buffer cost.

VERIFICATION PLAN
Conservation
Reconcile arrivals, completions, rework, and remaining work.

Reference cases
Check deterministic and simple queue cases against hand calculations.

Replication
Use multiple random seeds and confidence intervals; test input sensitivity.

PLANNED DELIVERABLES
- Reproducible discrete-event model and input-data template
- Scenario comparison with capacity and buffer recommendations
- Assumption register and a time-study collection plan

SCOPE NOTE
Hypothetical scenarios will be labeled. Staffing savings and measured throughput improvements require operational data and a trial.

NEXT STEP
Define the cell boundary and collect arrival, inspection, and rework timestamps.
