Practice FE-style Industrial & Systems questions through interactive engineering problems with guided reasoning and detailed solutions.
A 5% defective process did not imply a 95% lot-acceptance probability. Under an n=20, c=1 plan, acceptance required observing zero or one defective item.
Solve This Question โ The full solution unlocks after the investigation.Each topic groups questions around a specific FE knowledge area. Topic pages become indexable only after they contain a meaningful practice set.
Choose a question and solve it before reading the final engineering verdict.
A 5% defective process did not imply a 95% lot-acceptance probability. Under an n=20, c=1 plan, acceptance required observing zero or one defective item.
Quality loss did not grow linearly with deviation from target. Under the Taguchi quadratic model, a 3-unit deviation caused a $45 loss.
The process spread fit comfortably inside the specification width, but the mean had shifted toward the USL. Cp looked strong while Cpk exposed the centering problem.
The individual-process spread looked wide enough to contain 53.5, but an xฬ chart uses the standard error of the sample mean. The upper control limit was 53.0.
Site A had the higher simple average freight rate, but most demand was on its low-cost lane. Demand-weighted annual cost made Site A $10,000 cheaper.
Three machines looked sufficient at 100% theoretical availability. At the planned 80% utilization, the cell required four machines.
Layout A had the shorter average distance, but its busiest material-flow pair was much farther apart. Weighted load-distance made Layout B the better design.
Ordering the full annual demand once minimized ordering frequency, not total inventory cost. The EOQ was about 707 units.
The latest actual demand was 130 units, but exponential smoothing with ฮฑ=0.30 did not replace the forecast with 130. The next forecast became 109.
The arithmetic produced 3.6 stations, but a production line cannot operate with a fraction of a station. The theoretical minimum was 4.
Choose a topic, solve the problem before seeing the conclusion, and use the final reasoning trail to identify where your original assumption was supported or needed revision. The goal is not only to reach the answer, but to understand the engineering check behind it.