| Course | MT435 Operations Management |
|---|---|
| Unit | Unit 3 |
| Paper type | Bottleneck analysis |
| Length | About 890 words, 6 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Business Administration |
| Updated | October 2026 |
Free sample paper for MT435 Unit 3
The Booth Sets the Day at 30.6 Beds: An MT435 Unit 3 Bottleneck Analysis of Eight Stations
[Student Name]
Purdue University Global
MT435: Operations Management
Unit 3 Bottleneck Analysis
[Instructor Name]
[Date]
Pacolet Bunk & Loft, its stations and times are composite; capacities are computed for one 7.5-hour shift, and the sources cited are real.
How Each Station's Rate Is Computed
Every station's capacity is computed the same way, using the output-rate measure of capacity Slack and Brandon-Jones (2019) describe: available minutes in a shift, divided by the minutes each bed needs at that station, multiplied by the number of parallel machines or workers. The shift is 7.5 hours of productive time, 450 minutes, after breaks and the start-up check. Times per bed are averages over the last month's job tickets for a twin bunk bed, the shop's standard product.
The Capacity Table
The router needs 6 minutes a bed on one machine, 75 beds a shift. The shaper needs 7.5 minutes, 60 beds. Boring needs 5 minutes, 90 beds. Sanding needs 8 minutes a bed but has two stations, 112.5 beds. The spray booth needs 11 minutes a bed on its one booth, 40.9 beds. Test assembly needs 8 minutes at one bench team, 56.25 beds. Hardware kitting needs 6 minutes, 75 beds. Final check and boxing needs 7 minutes, 64.3 beds.
The booth's design rate of 40.9 is the lowest of the eight, so it is the constraint. Averaging the stations would give about 71.8 beds a shift, a figure the shop has never come close to, because a line cannot produce faster than its slowest station.
From Design Rate to Actual Rate
The booth's design rate assumes it sprays all 450 minutes. It does not. Each day the booth changes color about six times, from clear coat to stain to white paint and back, and each change takes about 15 minutes to flush the lines and clean the guns. Those 90 minutes leave 360 minutes of spraying, an effective rate of 360 divided by 11, about 32.7 beds.
About 7 percent of beds need a second pass because of runs, dust or thin spots found at inspection. Re-sprayed beds use booth time without adding output, so actual output is 32.7 divided by 1.07, about 30.6 beds a day.
The booth is rated for nearly 41 beds a day and delivers about 31; the difference is color changes and second coats.
The Shortfall
Against bookings of thirty-eight a day, the booth's 30.6 leaves a daily gap. The shop therefore falls about 7.4 beds short every day, roughly 1,850 beds over a 250-day year, which explains the growing backlog and the 16.5-hour wait for the booth recorded in the Unit 2 flow chart.
Utilization Elsewhere
At the booth's actual rate of 30.6 beds a day, every other station is far from busy. Sanding runs at about 27.2 percent of its capacity, boring at 34.0, the router and hardware kitting at 40.8, final check and boxing at 47.6, the shaper at 51.0 and test assembly at 54.4. A bar chart shows the pattern: one station near full, seven with large amounts of idle time.
That pattern matters for decisions. Goldratt and Cox (2004) made the point through a novel's plant manager: time lost at the one step that limits output cannot be made up, while time saved at steps with slack changes nothing the customer receives. Speeding up the router or adding a sander would not produce one more bed a day.
Why the Booth Wins Over the Router
The router is the station most people in the shop would name as the bottleneck, because it is loud, central and always running. At 75 beds a shift, though, it is busy less than half the time at the booth's pace. The booth sits in a separate building, works quietly and is often out of sight, which is why its queue had gone unnoticed until the Unit 2 flow chart recorded the 16.5-hour wait in front of it. Bottlenecks are found by measuring rates, not by watching which machine looks busiest.
Where the Constraint Moves Next
If the booth's output rose, the next constraint would be test assembly, at 56.25 beds a shift, followed by the shaper at 60. Any plan that raises booth output above about 56 beds a day would need to add assembly capacity too. Hopp and Spearman (2011) describe this as the constraint moving through the line, which is why improvement plans should look one station ahead.
What the Owner Should Stop Doing
The analysis also says what not to do. Overtime for the router crew, which the owner approved last month to catch up on the backlog, cannot help: the router already cuts more than twice what the booth can finish, and the extra cut parts only add to the stacks waiting in the finishing building. The same is true of any purchase for a station other than the booth.
What the Analysis Suggests
The constraint is the booth, and its actual output, not its design rate, is the figure to plan around. Two levers act directly on it: fewer or faster color changes, and fewer re-sprays. A third, more booth time through a second shift or a second booth, is a capacity decision for Unit 4. Changes anywhere else would leave output where it is.
References
Goldratt, E. M., & Cox, J. (2004). The goal: A process of ongoing improvement (3rd rev. ed.). North River Press.
Hopp, W. J., & Spearman, M. L. (2011). Factory physics (3rd ed.). Waveland Press.
Slack, N., & Brandon-Jones, A. (2019). Operations management (9th ed.). Pearson.
MT435 Unit 3 instructions, in plain terms
The third unit asks students to find the station that limits a process's output and compute its real rate. Instructors expect every station's capacity computed the same way, available time divided by time per unit, multiplied by parallel units. The constraint is the station with the lowest rate, not an average of the stations. Its design rate should then be reduced by the losses that occur in practice, such as setups and rework, to give the actual rate. The shortfall against demand should be stated per day and per year. Utilization at the other stations, measured at the constraint's actual rate, shows where capacity sits idle. The analysis should say where the constraint moves next and which levers act on it.
How the MT 435 Unit 3 example is put together
This example opens by stating the method for every station's rate. A capacity table gives all eight. The booth is identified as the constraint, and a short calculation takes it from design to effective to actual output, under a highlighted line on the two losses. The shortfall is stated per day and per year and linked to the Unit 2 wait. Utilization elsewhere is reported station by station, with Goldratt and Cox on why time at non-constraints does not add output. A section explains why the router looks like the bottleneck and is not. Another shows the next constraint, citing Hopp and Spearman, and the paper closes on the levers that act on the booth and the purchases that would not help.
Where the points sit in the MT435 Unit 3 rubric
Averaging station speeds is the mistake bottleneck papers make most often, and it yields a shop capacity no single day has ever reached. Identifying the constraint correctly and then reporting its design rate instead of its actual rate costs nearly as much, since setups and rework at the constraint are where output is lost. Rubrics reward consistent capacity calculations for every station. Credit goes to computing the shortfall against demand. Reporting utilization at the other stations shows the analysis understands what the constraint means for the rest of the line. Naming where the constraint moves next shows foresight. A capacity table, a short constraint calculation and a utilization chart make the reasoning easy to verify.
Common MT435 Unit 3 mistakes, and how to avoid them
The most frequent weak bottleneck analysis picks the station with the longest time per unit and stops, ignoring parallel machines that change its rate. Another common error averages the stations or adds their capacities. Students often report the booth's design rate as its output, leaving out setups and rework. Utilization at other stations is rarely computed, so the paper cannot say where extra capacity sits. Many recommend improvements at stations that are not the constraint. Before submitting, check that the output you report for the whole process equals the actual rate of your constraint, not its design rate. If it is higher than any day's real output, a loss is missing.
Get an MT435 Unit 3 example written to your instructions
Station times, staffing and demand, as the Unit 3 problem states them, are what a composite analysis needs, alongside the rubric. The version returned computes every station's rate the same way, separating design from actual output at the constraint, and naming where the limit moves next. First custom sample free, back inside 24-48h. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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MT435 Unit 3 questions, answered
Why does inventory pile up somewhere other than the bottleneck?
Usually because of batching or release rules. A station processing work in large lots, or fed faster than the next step needs, builds a queue even with spare capacity. Utilization is the better evidence: a station busy well under half the day cannot be limiting output, however crowded the floor around it looks.
Should setup time count against the bottleneck's capacity?
Yes, at the constraint it should. Every minute spent on setups or changeovers there is a minute of output lost for the whole operation. At stations with spare capacity, setups matter far less because idle time absorbs them. Most MT435 problems that give setup times expect you to subtract them at the bottleneck and explain why.
What if two stations have almost the same capacity?
Report both and say which is lower under the case's figures, then note that small changes in product mix, staffing or rework could swap them. Operations with two near-equal constraints behave less predictably, and pointing that out shows judgment. A recommendation relieving one of them should say what happens at the other.
Where can I find a free MT435 Unit 3 sample paper?
The full MT435 Unit 3 analysis is here, computing eight stations' capacities and the spray booth's actual rate of 30.6 beds a day.
Why is the booth's actual output lower than its design rate in the MT435 Unit 3 sample?
Six fifteen-minute color changes take 90 minutes a day, and 7 percent of beds need a second pass, so 40.9 becomes about 30.6.