Chemical & Biological Engineering · 150-Question Exam

Data Analytics in Chemical Engineering Exam

150 questions centered on shared plant, laboratory, and validation datasets — applying statistical modeling, machine learning, Python-style programming, process optimization, scale-up judgment, and smart manufacturing workflows for Chemical & Biological Engineering study

150 Questions 4 Options Each 1 Mark per Question Total: 150 Marks Exam Mode: 4 hr timer

Dataset Appendix for This Exam

Unless a question states otherwise, use the following shared synthetic plant, laboratory, and validation datasets. Quality_fail = 1 means the run failed final quality release.

Plant Dataset A — continuous reactor production runs

Run	Temp_C	tau_min	C_A0	pH	Agit_rpm	Cooling_kW	Conv_%	Byprod_%	Energy_MJ/kg	Quality_fail
1	68	14	1.20	6.8	410	80	78	3.9	5.6	1
2	72	16	1.18	7.1	430	92	82	3.2	5.2	0
3	76	18	1.15	7.3	450	108	86	2.7	4.9	0
4	80	18	1.16	7.6	460	125	89	2.5	5.1	0
5	84	20	1.14	7.7	480	146	91	2.8	5.5	1
6	88	20	1.12	7.9	500	170	92	3.4	6.2	1
7	74	22	1.22	7.0	420	100	85	3.1	4.8	0
8	79	24	1.19	7.4	440	122	90	2.4	4.7	0
9	83	26	1.17	7.5	470	150	93	2.6	4.9	0
10	87	26	1.13	8.1	500	178	94	3.6	6.6	1
11	78	15	1.21	7.2	390	105	84	2.9	5.0	0
12	82	21	1.18	7.4	450	140	91	2.5	4.8	0

Lab Dataset B — 2³ membrane-separation design of experiments

Run	Temp code	Pressure code	pH code	Flux_LMH	Rejection_%	Fouling_Index
1	−1	−1	−1	28	94	0.35
2	+1	−1	−1	34	92	0.42
3	−1	+1	−1	39	90	0.50
4	+1	+1	−1	47	87	0.62
5	−1	−1	+1	25	96	0.30
6	+1	−1	+1	31	94	0.36
7	−1	+1	+1	35	93	0.44
8	+1	+1	+1	43	91	0.55

Validation Dataset C — soft sensor and quality-classifier summaries

Soft sensor validation: Model A linear regression RMSE 2.8, MAE 2.1, R² 0.74. Model B random forest RMSE 1.9, MAE 1.4, R² 0.86. Model C gradient boosting train RMSE 0.7, validation RMSE 2.4, MAE 1.6, R² 0.80.

Quality classifier, positive class = failure: threshold 0.50 gives TP 18, FP 7, TN 63, FN 12. Threshold 0.35 gives TP 25, FP 20, TN 50, FN 5.

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Dataset Appendix for This Exam

Plant Dataset A — continuous reactor production runs

Lab Dataset B — 2³ membrane-separation design of experiments

Validation Dataset C — soft sensor and quality-classifier summaries

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