Twinworks Bottleneck Analysis

How it works

Ranks the stations of a Twinworks factory model by how often they constrain the line (active-period method: sole and shifting bottleneck shares), explains the dominant loss (working, breakdowns, setups, waiting for operators) and simulates typical improvements of the top bottleneck — an extra server, a 10 % faster cycle, faster repairs, shorter setups, more operators or a bigger buffer — with paired confidence intervals.

• Each replication records, per station, every active period (uninterrupted time working, in setup, under repair/maintenance or waiting for an operator; starved and blocked times end a period).
• At every instant the station with the longest current active period is the bottleneck. Where the periods of consecutive bottlenecks overlap, both are shifting bottlenecks; otherwise the station is the sole bottleneck (Roser, Nakano & Tanaka 2001).
• Stations are ranked by sole + shifting share (averaged over the window of replication 1, votes = how often a station was the top bottleneck across replications); ties are broken by active percentage.
• What-if options for the top station are simulated with the same seeds as the baseline (common random numbers); the gain interval is a paired Student-t interval of the throughput differences.

Improvement options are illustrative single changes; real fixes have costs and side effects that the model may not capture.

Sources

• Law, A. M.: Simulation Modeling and Analysis, 5th ed. (McGraw-Hill, 2015) — event scheduling, replications, confidence intervals (McGraw-Hill)
• Roser, Nakano & Tanaka: A practical bottleneck detection method (Winter Simulation Conference 2001) (WSC)
• Hopp & Spearman: Factory Physics, 3rd ed. — Little’s law, VUT/Kingman equation, line throughput (Waveland Press)
• Nakajima, S.: Introduction to TPM — Overall Equipment Effectiveness = availability × performance × quality (Productivity Press)
• Little, J. D. C.: A proof for the queuing formula L = λW (Operations Research 9(3), 1961)