Recovering hidden capacity, preparing for rate increases

A complete plant performance assessment with discrete-event simulation, built in full on a six-operation fabrication area and shown end to end. Everything here, from inputs to validated model to sequenced moves, is what an engagement delivers on your area.

Representative case study based on real production work. Identifying details and selected inputs have been adjusted.

00 · The answer

Problem. The area misses its current commitment despite recurring overtime. A rate increase is approaching.

Constraint. The area has one governing constraint at a time, but it does not stay in one place. It begins at Op 10, moves to Op 40 after the first recovery move, and then reaches Op 30's type-specific capacity and flow. Repeat quality load is the final barrier to meeting demand at straight time. The simulation reveals that sequence before the floor commits.

Result. Current demand is met at straight time. Under the same overtime allowance, the operating ceiling rises 46 percent, from about 80 to about 117 parts per day. About $1.1M in annual waste is removed. A separate lean second shift carries the area to about 157 parts per day as demand rises.

Method. Four sequenced moves. No new production equipment or added headcount in the recovery. Each move addresses the current constraint and anticipates the next.

01 · The problem

Missing demand while paying overtime

The area commits to 90 parts a day and ships about 80, missing roughly 11 percent of demand while already running 2 hours of overtime every shift. The premium is paid and the area still falls short. Before it is a cost problem, it is an on-time-delivery problem.

80 of 90 good parts a day against committed demand, on 2 hours of overtime every shift
~$637K a year of overtime spend while still falling short of demand
~$742K a year of quality waste, the scrap and rework line items combined
92.4% of a part's lead time is waiting, 1134 minutes of a 1228 minute total

02 · The diagnosis

The constraint today, and why it will move

Every production system has one operation or policy that governs its pace, the constraint, sometimes called the drum. Today it is Op 10, the one station running slower than demand requires while every station after it has pace to spare. The cart ahead confirms it, nearly two hundred parts deep and still building. Relieving Op 10 will not finish the work: the constraint moves, and the sequence below follows it.

6.0 Op 10 3.0 Op 20 3.5 Op 30 4.0 Op 40 1.4 Op 50 3.3 Op 60 demand takt 4.5 min/part 11 min/part Rework (offline)
Each station's pace in minutes per part against the straight-shift pace needed to meet demand, with only Op 10 above it, today's governing constraint.

Mapped end to end, the same story runs through the flow.

PRODUCTION CONTROL Master Schedule (MRP) daily release Component Supplier feeds Op 30 component ⇒ Op 30 Upstream Area one cart per shift PUSH 95/d: 90 demand + scrap replacements CART BUILDUP filled by push, emptied by Op 10 avg 193 · max 282 parts still climbing, not settled ▲ building +10.3/day in 95/d push ▸ out 85/d pull PULL Op 10 2 stations · 2 people ◀ DRUM, system constraint Utilization 100% Op 20 2 stations · 1 person Utilization 50% Op 30 17 machines · 3 people wait 93 min Utilization 71% Op 40 3 stations · 2 people Utilization 78% Op 50 5 stations · 5 people Utilization 27% Op 60 1 station · 1 person quality loss Utilization 65% avg 0 (0–1) ≈ 0/day avg 18 (12–25) ≈ 0/day avg 1 (0–6) ≈ 0/day avg 0 (0–0) ≈ 0/day avg 0 (0–1) ≈ 0/day ship Complete GOOD OUTPUT 79.8/day ✗ 10/day SHORT of 90 CUSTOMER 90/day demand 15% fail REWORK. OFFLINE (2 quick-fix bays) cap 47/d · in 14/d backlog avg 0 · keeps up (WIP +0.0/day) utilization 30% rejoins the Op 30 queue Utilization gauge (bar fill = % of capacity in use, full bar = 100%): healthy warm at capacity parts waiting between stations, shown avg (range) and change per day
The current state at a glance: the drum at Op 10 caps good output at 79.8 a day against 90 committed. View technical VSM

03 · The moves

Four moves, in the order the system requires

The moves themselves are practical. The difficult part is knowing their order. Each change alters the operating system, so the next move is chosen against the new constraint rather than the original one.

Quality work starts in parallel with the first recovery move. Root-cause investigation, corrective actions, and validation take longer than the scheduling and labor changes. Quality is shown fourth because its measurable result appears last, not because the work begins last.

1. Relieve the drum

A processing-time study found Op 10 running each part longer than the qualified requirement. The shorter cycle was validated with operators and quality, then incorporated into standard work with no loss of quality. Overtime roughly halved, and the constraint moved to Op 40.

The same map, one move later. Watch the red border: it leaves Op 10, now at 75 percent with the cart stable behind it, and lands on Op 40.

AFTER MOVE 1 constraint now at Op 40 Upstream Area one cart per shift PUSH release ~96/d CART BUILDUP now stable avg 35 · max 95 ≈ +0.0/day (was building) Op 10 2 stations · 2 people was drum → relieved Utilization 75% Op 20 2 stations · 1 person Utilization 63% Op 30 17 machines · 3 people Utilization 90% Op 40 3 stations · 2 people ◀ NEW DRUM, constraint wait 20m · needs OT Utilization 98% Op 50 5 stations · 5 people Utilization 34% Op 60 1 station · 1 person Utilization 82% Complete GOOD OUTPUT 90/day ✓ 90/day with the OT Overtime ≈55 min a shift was 2 hours ceiling ≈95 a day PULL avg 0 (0–1) avg 31 (14–48) avg 5 (0–13) avg 0 (0–2) Utilization gauge (bar fill = % of capacity in use, full bar = 100%): healthy warm at capacity parts waiting between stations, shown avg (range)
What changed: Op 10 is relieved, output increases, and overtime falls from two hours to about 55 minutes. The governing constraint moves to Op 40, where labor allocation now limits further recovery. View technical VSM

2. Balance the line

One operator moved from Op 50, which has slack, to Op 40, the new drum. No new headcount. Overtime fell to about 30 minutes a shift, and the constraint moved to Op 30.

3. Stabilize flow through Op 30

A repeating release sequence matched to demand mix prevents one part type from overwhelming its dedicated machine pool. It does not increase theoretical capacity. It reduces queues, WIP, and lead time while making the remaining limit visible and controllable.

4. Root-cause the quality loss

Rework sends parts back through stations that are already busy, and scrap consumes parts along with the capacity that built them. Focused root-cause sprints start alongside move 1: defects are stratified, causes confirmed, and corrective actions validated on the floor. The analysis sets the target, 8 percent rework and 2 percent scrap against today's 15 and 5, and the sprints close the gap to it.

The constraint moves as the system improves

MOVE 1 Op 10 processing time MOVE 2 Op 40 labor allocation MOVE 3 Op 30 type-specific capacity and flow MOVE 4 Repeat quality load RESULT Demand met at straight time
The governing constraint hands forward four times before demand is met at straight time.

The value is not only finding the first bottleneck. It is predicting where the constraint will move next and sequencing the recovery correctly.

Where quality loss is a major constraint, a focused quality sprint can be scoped around defect stratification, root-cause analysis, corrective actions, validation, and control.

04 · The operating result

Demand met at straight time

With the same crew and no new production equipment, maximum deliverable output rises from about 80 to about 117 parts per day under the same two-hour overtime allowance. That is a 46 percent increase in operating ceiling. The immediate 90-a-day requirement is met at straight time, leaving headroom for variation and future growth.

Upstream Area one cart per shift release ~92/d sequenced to demand mix CART BUILDUP now stable avg 36 · max 90 ≈ +0.0/day (was building) PULL Op 10 2 stations · 2 people was drum → relieved Utilization 81% Op 20 2 stations · 1 person Utilization 68% Op 30 17 machines · 3 people wait 21m · headroom ◀ tightest (next lever) Utilization 90% Op 40 3 stations · 3 people Utilization 65% Op 50 5 stations · 4 people Utilization 43% Op 60 1 station · 1 person QUALITY ROOT-CAUSE Utilization 81% avg 0 (0–1) avg 5 (0–15) avg 0 (0–3) avg 1 (0–4) ship Complete GOOD OUTPUT 90/day ✓ meets 90/day demand CUSTOMER 90/day demand 8% fail REWORK. OFFLINE (2 quick-fix bays) cap 47/d was 15% fail rejoins the Op 30 queue AFTER ALL FOUR MOVES demand met, no overtime Utilization gauge (bar fill = % of capacity in use, full bar = 100%): healthy warm at capacity parts waiting between stations, shown avg (range) and change per day
What changed: the cart is stable, every station holds headroom, and demand ships at straight time with the overtime gone. View technical VSM

Move by move, the same recovery stacks up to the straight-time ceiling.

Demand 90/day straight time 64 80 2 h OT Baseline Crew 14 (12 needed) max 95 straight time 82 90 ~55 min OT Move 1, Op 10 relieved 14 (12 needed) max 104 straight time 87 90 ~30 min OT Move 2, balanced 14 (12 needed) max 104 straight time 87 90 ~30 min OT Move 3, flow stabilized 14 (12 needed) max 117 straight time 90, no OT 90 no overtime Move 4, quality fixed 14 (12 needed) max 170, second shift on 2 h OT straight time 157, no OT 157 no overtime Rate step, two shifts 18 (12 + 6)
Together, the moves increase output, stabilize flow, and remove repeat load until demand is met at straight time. The final bar previews the separately counted rate step.

05 · The economic result

What the recovery is worth

The recoverable annual waste falls from about $1.4M to about $0.3M, subject to validation against a client's actual labor, material, quality, and inventory costs.

~$1.1M a year of recoverable waste removed by the four moves
IDENTIFIED WASTE ~$1.4M A YEAR RECOVERED BY THE FOUR MOVES ~$1.4M Identified ~$1.4M a year −$0.64M Overtime all of it no overtime −$0.40M Scrap of $0.67M 5% → 2% −$0.03M Rework of $0.07M 15% → 8% −$0.02M WIP carry of $0.03M cart 193 → 36 ~$0.3M Remains at the target rates Crew floor ~$1.6M straight time stays, outside this picture
From ~$1.4M identified down to ~$0.3M remaining at the target rates: about $1.1M a year leaves the ledger and the crew floor stays.

06 · The rate path

Rate-readiness, counted separately

When demand moves beyond what the recovered shift can hold, a lean second shift raises straight-time output to about 157 parts per day on the same production equipment. The design requires four net new hires, with two existing operators redeployed from capacity released by the recovery.

Op 10 2 stations · 2 people ◀ shift-1 drum Utilization 100% Op 20 2 stations · 1 person Utilization 82% Op 30 17 machines · 3 people changeover operators 16% Utilization 75% Op 40 3 stations · 3 people Utilization 81% Op 50 5 stations · 2 people Utilization 90% Op 60 1 station · 1 person Utilization 96% 23→57 ▼ clears 36 → 0 queue ahead of Op 40 ship RATE STEP · SHIFT 1 first half of the day RELEASE CART AHEAD OF OP 10 150 → 53 staged 150 at day start OP 30 BUFFER ▲ builds 23 → 57 handoff, feeds shift 2 Shift 1 of 2 FULL CREW 12 people 2 redeployed to shift 2 from today's crew of 14 Shift 1 ships THIS SHIFT ≈103/day Two-shift total BOTH SHIFTS ≈157/day counted separately Utilization gauge (bar fill = % of capacity in use, full bar = 100%): healthy warm at capacity parts waiting between stations · empty triangle = no queue builds this shift
The first shift of the two-shift day, 12 people on the full area, Op 10 its drum, building the Op 30 buffer that shift 2 draws down. View technical VSM

The second shift adds only labor on the same equipment, so it is counted separately and never summed into the recovery.

Op 10 1 station · 1 person Utilization 82% Op 20 1 station · 1 person Utilization 36% Op 30 17 machines · 1 person changeover operator 52% Utilization 83% Op 40 1 station · 1 person ◀ shift-2 drum Utilization 97% Op 50 1 station · 1 person Utilization 89% Op 60 1 station · 1 person Utilization 53% 57→23 ▲ builds behind Op 40 avg 17 (0–41) queue at the shift-2 drum ship RATE STEP · SHIFT 2 second half of the day RELEASE CART AHEAD OF OP 10 53 → 0 drains to zero this shift OP 30 BUFFER ▼ draws down 57 → 23 handoff, built on shift 1 Shift 2 of 2 LEAN CREW 6 people 2 redeployed from shift 1 4 net new hires Shift 2 ships THIS SHIFT ≈53/day Two-shift total BOTH SHIFTS ≈157/day ≈103 + ≈53 Utilization gauge (bar fill = % of capacity in use, full bar = 100%): healthy warm at capacity parts waiting between stations · empty triangle = no queue builds this shift
The lean second shift, 6 operators on the same equipment, Op 40 its drum, running down the Op 30 buffer that shift 1 builds. View technical VSM

What each configuration holds as the build rate climbs, from the rate ramp analysis.

Configuration90/day (today)110/day120/day150/day
Current state~80 ceiling~80 ceiling~80 ceiling~80 ceiling
Move 1, relieve the drum~55 min OT~95 ceiling~95 ceiling~95 ceiling
Move 2, balance the line~30 min OT~104 ceiling~104 ceiling~104 ceiling
Move 3, stabilize flow through Op 30~30 min OT~104 ceiling~104 ceiling~104 ceiling
Move 4, root-cause the quality lossno overtime~1.4 h OT~117 ceiling~117 ceiling
Rate step, two shiftsNot requiredno overtimeno overtimeno overtime

Overtime entries are what it takes to meet that rate. Ceiling entries are the most that configuration can ship even on full overtime.

07 · The method

How an engagement runs

  1. The study starts on the floor. Walking the line, talking with operators, and measuring cycle times, yields, staffing, and the shift pattern. The constraint is found here, not in software.
  2. The line is then modeled in discrete-event simulation from its own measured inputs, and the model is validated against the line's measured behavior before any conclusion is drawn.
  3. Improvement moves come from floor experience. Each one is tested in the model before anything changes on the floor, so the costly decisions are made on evidence.
  4. The model also shows where the constraint migrates after each move, so the full sequence is known in advance and the next bottleneck is never a surprise.
  5. Findings land as a costed, sequenced recommendation the client's team can execute, with the evidence behind every step.

Each engagement includes the data work required to make the operating picture reliable: extracting and combining production records, cleaning and validating inconsistent fields, transforming ERP and manually collected data, analyzing cycle time, throughput, and quality loss, and building the visualizations and simulation-ready inputs behind every figure in this study.

Floor observation shows where to look. Data analysis quantifies the loss. Simulation tests the decision.

08 · The proof

How the model is validated

A model is only worth what it can prove, so this one has to earn trust twice. First against the area. The model is built from the area's own measured cycle times, yields, staffing, and shift pattern, tuned to match one measure, throughput, and then required to reproduce WIP and lead time on its own, measures it was never tuned to.

Second against itself. An accounting check confirms every part released is either shipped, scrapped, or still in process, so the model neither creates nor loses work. Every figure in the study is the average of 30 replications with a 95 percent confidence interval. In an engagement the same validation runs against the client's measured line before any future-state move is tested.

09 · The ask

Recover the operation before adding capacity

The first answer is often not more equipment. The real limit may sit in handoffs, scheduling, labor allocation, release logic, quality loss, or the interaction between them. Recovering existing capacity first shows what the operation can hold and what genuinely needs to be added.

If your operation is meeting demand on overtime, falling behind with overtime not closing the gap, or facing a rate increase it may not hold, the locked-up capacity is likely already on your floor. I find it the same way it was found here.

This is the work a Plant Performance Assessment with a Simulation and Decision Study delivers, fixed fee and time-boxed, on your area.

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