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MQM 227 – Operations Management | 100 Exam Questions on Forecasting, Scheduling, Capacity Planning, Project Management | Illinois State University

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This document includes 100 fully answered multiple-choice and true/false questions from Exam 2 of MQM 227 – Operations Management at Illinois State University. It provides comprehensive coverage of quantitative and qualitative forecasting techniques, including moving averages, weighted averages, exponential smoothing, Delphi method, regression, CPFR, and forecasting accuracy. The material emphasizes demand planning, sales forecasting, and decision-making based on predictive analytics. Beyond forecasting, the questions assess in-depth knowledge of capacity planning and utilization strategies, including types of capacity (effective vs. design), bottlenecks, facilities planning, economies of scale, and chase vs. level strategies. The document also explores aggregate planning processes, workforce and inventory planning, and demand management techniques. A major portion is dedicated to scheduling theory, job sequencing, Gantt charts, finite capacity scheduling (FCS), and the Theory of Constraints (TOC). The final section focuses on project management frameworks including PERT/CPM, crashing, project phases (planning, scheduling, control), network diagrams, and project performance evaluation metrics. This resource is highly recommended for students in operations management, industrial engineering, supply chain management, project management, and business strategy courses. It is tailored for both exam preparation and practical application in managing operational systems. Keywords: operations management, MQM 227, forecasting, scheduling, capacity planning, project management, moving average, exponential smoothing, CPFR, regression forecasting, chase strategy, level strategy, bottleneck, utilization, Gantt chart, PERT, CPM, crashing, aggregate planning, service operations, job sequencing

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MQM 227 Exam 2 Questions and
Answers 100% Correct

Regarding types of time-series components, which of the following

statements is incorrect? - 🧠 ANSWER ✔✔B. Seasonality is represented by

an irregular pattern of demand.

What is the August forecasted demand using a 4-month moving average

for the following actual demand values: January - 300 units, February - 200

units, March - 400 units, April - 500 units, May - 600 units, June - 600 units,

July - 700 units. (Round answer to nearest whole number.) - 🧠 ANSWER

✔✔A. 4 month = 600


What is the August forecasted demand using a 4-month weighted moving

average for the following past actual demand: January - 300 units,

February - 200 units, March - 400 units, April - 500 units, May - 600 units,

,June - 600 units, July - 700 units. P1 = 0.4, P2 = 0.3, P3 = 0.2, P4 = 0.1

(Round answer to nearest whole number.) - 🧠 ANSWER ✔✔630


What is the August forecasted demand using a 6-month as well as a 6-

month moving average for the following actual demand values: January -

300 units, February - 200 units, March - 400 units, April - 500 units, May -

600 units, June - 600 units, July - 700 units. (Round answer to nearest

whole number.) - 🧠 ANSWER ✔✔B. 6 month = 500


A. The qualitative type of forecasting utilizes time-series and causal

approaches.

B. There is no universal forecasting method for all situations.

C. In organizations, managers are usually most interested in predicting

future demand.

D. In CPFR, a long-term, mutually beneficial, collaborative relationship is

needed.

E. In a regular moving average calculation, all of the months included in

the calculation are weighted equally. - 🧠 ANSWER ✔✔A. The qualitative

type of forecasting utilizes time-series and causal approaches.

, A. Short-range forecasts are good for procuring materials and work

scheduling.

B. Short-range forecasts are usually less than 6 months in the future.

C. Casual forecasting methods are great for predicting turning points in

demand.

D. Medium-range forecasts are usually 6 months to two years in the future.

E. Causal forecasting methods are usually more accurate than time-series

models for medium- to long-range forecasts. - 🧠 ANSWER ✔✔C. Casual

forecasting methods are great for predicting turning points in demand.

A. An essential forecast number is the forecasting error (e.g., standard

deviation or range).

B. Weighted moving average is the simplest method of time-series

forecasting.

C. For the weighted moving average, the sum of coefficients always

equals to 1.0.

D. Qualitative forecasting methods rely on managerial judgment.

E. In a weighted moving average calculation, demand in more recent

months is often given a higher coefficient so the moving average

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