The Value Stream That Looks Efficient
Cascade Millwork makes custom commercial cabinetry in a 180,000 sq ft plant. A current-state value stream map for the most profitable product family shows: order processing 2 days; engineering 3 days; CNC 45 minutes cycle time, 85% uptime, 2,400 units WIP; edge banding 30 minutes, 70% uptime; assembly 4 hours, 3,200 units WIP; finishing 6 hours, 1,100 units WIP; shipping 1 day. Total lead time is 19 days; value-added time is 7.1 hours. First-pass yield is 82%, and the top defect is edge chip-out after changeovers. Changeover on the edge bander averages 95 minutes, and the plant runs it in batches of 300 to protect uptime. The plant manager wants to buy a second CNC and add a finished-goods warehouse to improve delivery. Sales promises 10-day lead times. The map shows departments are measured on machine utilization and purchase-price variance.
1. Calculate process cycle efficiency (PCE) and interpret it. What does the gap between 19 days and 7.1 hours tell you, and what does it not tell you?
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Calculation. PCE = value-added time / lead time. Assuming an 8-hour working day, 19 days = 152 hours, so PCE = 7.1 / 152 = 4.7%. If lead time is measured around the clock, 19 days = 456 hours, giving 1.6%. State the assumption explicitly.
Interpretation. Either way, most of the lead time is queue and waiting, not processing. That points to flow, batch, and reliability problems rather than insufficient machining hours. The 2,400 units at CNC and 3,200 at assembly are the biggest visible queues. The 82% first-pass yield also means rework and hidden work are extending lead time.
What it does not tell you. PCE alone does not identify the constraint or the cause. It does not tell whether the edge bander's 70% uptime and 95-minute changeover are creating the queues, whether engineering releases work in bursts, or whether the 300-unit batch policy is driving WIP. It also says nothing about customer-required lead time. The 19-day lead time and 10-day promise explain the delivery gap, but not yet the countermeasure. That requires process-level analysis.
2. The plant manager proposes a second CNC and a finished-goods warehouse. Evaluate this against the VSM and propose a better future-state sequence. Include at least two calculations or quantitative comparisons.
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Evaluation. The second CNC adds capacity at a resource that is not the obvious constraint: CNC uptime is 85%, while the edge bander is 70% with 95-minute changeovers. The warehouse would hide lead time and add inventory, not improve flow. Both proposals treat symptoms with capital rather than address batch, uptime, and yield.
Calculations.
- Uptime improvement: raising edge-bander uptime from 70% to 85% gives 0.85 / 0.70 = 1.21, roughly 21% more effective capacity, potentially delaying or avoiding CNC purchase.
- Changeover reduction: cutting changeover from 95 to 30 minutes reduces the batch penalty by about 68%. If the batch falls from 300 to 100, edge-band WIP could fall by roughly two-thirds at equal throughput, shortening queue time.
Future-state sequence. (1) SMED on the edge bander; (2) TPM and defect containment for chip-out, especially after changeovers; (3) pull a small supermarket before assembly; (4) level the release of engineering and order processing so work does not arrive in bursts. Buy capacity only after the constraint is genuinely protected.
3. How would you change the measurement system to support the future state? Name specific metrics and the behavioral risk of each.
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Change the local-efficiency logic. Machine utilization encourages overproduction and large batches; purchase-price variance encourages cheap material and large buys, even when quality and flow suffer. Replace them with value-stream measures: dock-to-dock lead time, on-time delivery, WIP turns, first-pass yield, changeover time, and schedule adherence.
Behavioral risks.
- Dock-to-dock lead time can be gamed by shipping early or rejecting difficult orders, so pair it with OTD and mix compliance.
- WIP turns can be improved by starving the constraint, so monitor constraint uptime and customer service.
- First-pass yield can be improved by hiding defects or reclassifying rework, so use external escape and customer ppm data.
- Changeover time can be gamed by poor-quality setups, so audit first-piece approval after changeover.
Use a balanced scorecard reviewed at the value-stream level, not department by department. The plant manager should own flow and delivery, not just machine utilization.