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23-Ind-A6 Systems Simulation: May 2018

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

  1. Question 1 Valid PDF, Inverse Transform, MCG Variates
  2. Question 2 Chi-Squared Goodness-of-Fit and Generator Diagnosis
  3. Question 3 Acceptance–Rejection and LCG Period
  4. Question 4 Variate Generation Across Five Distribution Families
  5. Question 5 Transient Behaviour and Welch's Warm-Up Method
  6. Question 6 Replication Length, Run Strategy
  7. Question 7 Sample Size, Vendor Comparison, Validation Test
  8. Question 8 Comparing Five Scenarios by ANOVA
  9. Question 9 2 3 Screening Experiment for Warehouse Throughput

Start with Question 1 →

National Exams — May 2018 — 17-Ind-A6 Systems Simulation. Three-hour, closed-book exam; one of two permitted calculators (Sharp or Casio), one 8.5″×11.0″ aid sheet (both sides). Format: three sections — Section A (four concept questions, candidates choose any two, 10 marks each, 20 marks total), Section B (three methods questions built around one continuing warehouse-simulation case study, candidates choose any two, 15 marks each, 30 marks total), Section C (two applications questions, candidates choose any one, 20 marks each). All nine questions are solved below for completeness. Two source anomalies are flagged where they occur: the front-page summary table states Section A is "Do 2 of 3," while Section A's own instructions and its four printed question sets read "two of the following four" — the printed four-question section is answered in full here; and Part C Question 2's sub-parts (a)–(c) are never printed anywhere in the paper, even though the results text for (d)–(f) explicitly refers back to "the factorial design matrix in (a)." Two-page Normal-distribution tables were supplied with the exam; the values below are the same table values obtained by direct computation.

Reference texts: Banks, Carson, Nelson & Nicol, Discrete-Event System Simulation (5th ed., Pearson) — random-number/random-variate generation, input modeling and goodness-of-fit testing, output analysis (warm-up, replication length, batch means vs. replication/deletion), and comparing alternative systems; Montgomery, Design and Analysis of Experiments (current ed., Wiley) — single-factor ANOVA, multiple comparisons, and 2k factorial designs with interaction analysis (Part C).