The BSIE (Bachelor of Science in Industrial Engineering) licensure exam and the FE (Fundamentals of Engineering) Industrial exam test mastery of operations research, manufacturing systems, work measurement, engineering economics, and supply chain management. Our free BSIE industrial engineering practice test PDF gives you a printable set of exam-style questions covering every major content domain so you can study offline at any time.
Download once and study anywhere — in the library, during commutes, or between review sessions. The PDF covers linear programming, process capability, work measurement calculations, EOQ, and queuing theory — the quantitative topics that appear on virtually every IE licensure and board exam. Print it out, work through the problems, and use it alongside your engineering reference handbook for a thorough exam preparation strategy.
Industrial engineering exams are heavily quantitative, with most questions requiring formula application and numerical calculation. Here is a detailed breakdown of every major content area you need to master.
Linear programming (LP) is one of the most tested OR topics. You must be able to solve two-variable problems graphically (identify feasible region, find corner points, evaluate objective function) and understand the simplex method conceptually. Sensitivity analysis questions test shadow price (the marginal value of relaxing a binding constraint) and ranging (how much an objective coefficient or RHS value can change without changing the optimal basis). Transportation and assignment problems are special LP structures solved by the northwest corner method, Vogel's approximation, or MODI method. Network models include CPM — you must calculate early start, early finish, late start, late finish, and total float for each activity; the critical path has zero total float. PERT uses three-time estimates (optimistic a, most likely m, pessimistic b) to calculate expected activity time t_e = (a + 4m + b)/6 and variance σ² = ((b−a)/6)². Queuing theory for the M/M/1 model: arrival rate λ, service rate μ, utilization ρ = λ/μ (must be less than 1 for stability), average number in system L = ρ/(1−ρ), average time in system W = L/λ, average number in queue L_q = ρ²/(1−ρ), average wait in queue W_q = L_q/λ. Monte Carlo simulation uses random numbers mapped to a probability distribution to simulate system behavior over time.
Statistical process control requires mastery of control chart types: X-bar and R charts for variable data (subgroup mean and range), p-charts for proportion nonconforming, and c-charts for count of defects per unit. Process capability indices: Cp = (USL − LSL) / 6σ measures the spread of the process relative to the specification width without regard to centering; Cpk = min[(USL − μ)/3σ, (μ − LSL)/3σ] adjusts for process mean offset. A Cp and Cpk both ≥ 1.33 is generally considered capable. OC (operating characteristic) curves display the probability of lot acceptance as a function of incoming quality. Acceptance sampling plans specify sample size n and acceptance number c; AQL (acceptable quality level) and LTPD (lot tolerance percent defective) define the producer's and consumer's risk points on the OC curve. FMEA (Failure Mode and Effects Analysis) assigns severity (1–10), occurrence (1–10), and detection (1–10) ratings to each failure mode; RPN = Severity × Occurrence × Detection, with higher RPN indicating higher priority for corrective action. Plant layout types: process layout groups similar equipment (flexible, high WIP); product layout arranges equipment in operation sequence (efficient, low flexibility); fixed position layout brings workers to the product (large/heavy items); cellular layout groups dissimilar machines to complete a family of parts (Group Technology). Material handling equipment selection considers unit load, path type, and throughput requirements.
Time study procedure: observe and time several cycles of each work element, apply a performance rating factor to get normal time (Normal Time = Observed Time × Rating Factor), then add allowances for personal needs, fatigue, and unavoidable delays to get standard time (Standard Time = Normal Time × (1 + Allowance Fraction)). Predetermined motion time systems (PMTS) such as MTM-1 (Methods-Time Measurement) assign standard times to fundamental hand motions without direct observation. Work sampling uses random-interval observations to estimate the proportion of time spent on various activities; required sample size is calculated from p (estimated proportion), z (confidence level z-score), and e (acceptable error). Learning curve theory: as cumulative production doubles, unit time decreases by a constant percentage. The unit time for the nth unit is T_n = T_1 × n^b, where b = log(learning rate) / log(2) and learning rate is expressed as a decimal (e.g., 0.80 for an 80% learning curve). Ergonomics applies anthropometric data to workstation design; the NIOSH lifting equation calculates the recommended weight limit (RWL) from load constant and six task multipliers, and the lifting index (LI = Actual Load / RWL) — LI > 1 indicates elevated musculoskeletal risk.
Present worth analysis converts all cash flows to time zero using P = F(P/F, i%, n) and P = A(P/A, i%, n) factors. Annual worth analysis converts all cash flows to a uniform annual series. Rate of return analysis finds the interest rate that sets NPW = 0. Payback period is the time to recover the initial investment from net cash flows, ignoring time value of money. Depreciation methods tested include straight-line (equal annual charge), MACRS (Modified Accelerated Cost Recovery System — used for US tax purposes, uses specified percentage tables), and double declining balance (accelerated: 2/n × book value each year). Break-even analysis finds the volume where total revenue equals total cost. Replacement analysis uses the annual cost method to compare keeping an existing asset versus replacing it with a new challenger.
Inventory management: EOQ = √(2DS/H) where D = annual demand (units/year), S = ordering cost per order, H = holding cost per unit per year. Reorder point ROP = d × L where d = daily demand rate and L = lead time in days. Safety stock is added to the reorder point to buffer against demand and lead time variability. ABC analysis classifies inventory items by annual dollar value: A items (top ~20% of items = ~80% of value) receive tight control; C items (~50% of items = ~5% of value) receive minimal control. JIT (Just-in-Time) and lean principles aim to eliminate waste (muda): the eight wastes are Transportation, Inventory, Motion, Waiting, Overproduction, Over-processing, Defects, and Skills underutilization (TIMWOOD+S). Value stream mapping is used to identify and eliminate waste in a production process. Demand forecasting: simple moving average averages the last n periods; exponential smoothing uses F_{t+1} = α × A_t + (1−α) × F_t where α is the smoothing constant. Forecast accuracy: MAD (mean absolute deviation) and MAPE (mean absolute percentage error) measure average forecast error magnitude.
The printable PDF is perfect for formula review and offline problem-solving practice, but our interactive BSIE industrial engineering practice test gives you immediate scoring and step-by-step answer explanations after every question. Work through the PDF to solidify your understanding of key formulas, then shift to timed online tests as your exam date approaches to build calculation speed and identify any remaining weak areas before test day.