SCM 3

Functions of Inventory

• Buffer against uncertainty (e.g., demand spikes)

• Decouple operations (e.g., allow one part of production to continue if another is delayed)

• Economies of scale (buying/storing in bulk reduces cost)

• Speculative purposes (buying ahead of price increases)

• In transit (pipeline inventory)

Purpose of ABC Classification System

• A: High-value, low-quantity (tight control)

• B: Medium value and quantity

• C: Low-value, high-quantity (less monitoring)

• Helps prioritize management efforts.

Types of Inventory Costs:

• Ordering Cost: Cost to place an order (e.g., paperwork, shipping)

• Carrying Cost: Cost to store items (e.g., rent, insurance, spoilage)

• Stockout Cost: Cost when demand can't be met (lost sales)

• Item Cost: Actual purchase cost of the item

EOQ (Economic Order Quantity) Assumptions:

• Demand is constant and known.

• Lead time is fixed.

• No stockouts.

• Instantaneous replenishment.

• Only ordering and holding costs matter.

Why Product Cost is Included in Quantity Discount Model:

• Because total cost is affected by price breaks.

• In basic EOQ, price is constant, so it doesn’t change the optimal order size.

Safety Stock:

• Extra inventory held to prevent stockouts due to demand variability or delivery delays.

• Calculated based on desired service level.

What is Simulation Modeling?, why use it

Imitates real-world systems using computer models to predict outcomes.

• To experiment without real-world risk

• Useful when analytical models are too complex

Pros/Cons of simulation modeling

• Pros: Flexible, visual, adaptable

• Cons: Requires data, can be complex, no guaranteed optimal solution

Monte Carlo Simulation:

• Developed by: John von Neumann & Stanislaw Ulam (1940s)

• Theory: Uses random sampling to understand probabilistic systems

Monte Carlo Simulation Steps

• Define problem

• Generate probability distribution

• Assign cumulative probabilities

• Generate random numbers

• Simulate outcomes

• Analyze results

Six Steps in Decision Process:

• Define problem

• Identify alternatives

• Determine criteria

• Evaluate alternatives

• Make decision

• Implement & monitor

Decision-Making Types:

• Certainty: One known outcome

• Risk: Probabilities known

• Uncertainty: Outcomes unknown

Decision Tree

Graphical tool showing decisions & outcomes.

Expected Monetary Value (EMV):

• EMV=∑(payoff×probability)EMV = \sum (\text{payoff} \times \text{probability})EMV=∑(payoff×probability)

• Picks option with highest average return.

EVPI:

• Value of eliminating uncertainty.

• EVPI=EVwPI−EMVbestEVPI = EVwPI - EMV_{\text{best}}EVPI=EVwPI−EMVbest​

EVwPI:

• Expected value if you had perfect information.

• Pick best payoff in each state × state probability.

Maximax

Choose alternative with best best-case (optimist).

Maximin

Choose alternative with best worst-case (pessimist).