CH 12 Inventory Management Summary

Inventory Management

• Objective: Balance inventory investment and customer service to optimize costs and meet customer needs.

• Inventory represents a significant asset, often comprising up to 50% of invested capital, requiring careful management.

Functions of Inventory

• Meet demand: Satisfy normal and unexpected customer demand efficiently.

• Buffer against demand fluctuations: Protect against variability in customer demand.

• Decouple parts of the production process: Allow different stages of production to operate independently.

• Take advantage of quantity discounts: Reduce costs by purchasing in bulk.

• Hedge against inflation: Protect against rising costs by stocking up on inventory.

Types of Inventory

• Raw material: Purchased but not yet processed, serving as the foundation for production.

• Work-in-process (WIP): Partially completed products undergoing transformation; its volume is cycle time-dependent, indicating production efficiency.

• Maintenance/repair/operating (MRO): Essential for maintaining productive machinery, ensuring smooth operations and minimizing downtime.

• Finished goods: Completed items awaiting shipment to customers, representing the culmination of the production process.

Managing Inventory

• ABC analysis for classification: Categorizing inventory based on value and importance.

• Maintaining accurate inventory records: Ensuring data integrity for effective decision-making.

ABC Analysis

• Divides inventory into three classes:

  • Class A: High dollar volume, requiring close monitoring.

  • Class B: Medium dollar volume, needing moderate attention.

  • Class C: Low dollar volume, managed with simpler controls.

• Focuses on critical parts over trivial ones: Prioritizing resources on high-value items.

• Policies:

  • Emphasis on supplier development for A items: Building strong relationships with suppliers.

  • Tighter control for A items: Implementing rigorous monitoring and security measures.

  • Careful forecasting of A items: Ensuring precise demand predictions.

Record Accuracy

• Critical for production and inventory systems: Accurate records are essential for efficient operations.

• Periodic systems need regular checks (Two-bin system): Regular audits are necessary to maintain accuracy.

• Perpetual inventory tracks continuously: Real-time tracking provides up-to-date information.

• Accurate incoming and outgoing records are essential: Precise tracking of inventory movement is vital.

Cycle Counting

• Items counted and records updated periodically: Regular counts and updates ensure accuracy.

• Advantages:

  • No shutdowns: Continuous operation without disruptions.

  • No annual inventory adjustment: Eliminates the need for large-scale adjustments.

  • Trained personnel for accuracy: Expertise ensures reliable counts.

  • Error cause identification and correction: Addressing the root causes of errors.

  • Maintains accurate records: Promotes reliable data management.

Control of Service Inventories

• Critical for profitability: Minimizing losses and maximizing revenue.

• Losses from shrinkage or pilferage: Preventing theft and damage.

• Techniques:

  • Good personnel: Hiring trustworthy employees.

  • Tight control of shipments: Monitoring incoming and outgoing goods.

  • Effective control of goods leaving: Preventing unauthorized removal.

Inventory Models

• Independent demand: Demand for an item is unrelated to others, managed using models like EOQ.

• Dependent demand: Demand is directly related to another item, managed through MRP systems.

• Holding costs: Costs of carrying inventory, including storage, insurance, and obsolescence.

• Ordering costs: Costs of placing and receiving orders, such as administrative and transportation expenses.

• Setup costs: Costs to prepare for manufacturing an order, including machine setup and labor.

Inventory Models for Independent Demand

• Basic economic order quantity (EOQ) model: Determines the optimal order quantity to minimize costs.

• Production order quantity model: Adjusts EOQ for items produced internally.

• Quantity discount model: Evaluates cost savings from bulk purchases.

Basic EOQ Model Assumptions

• Demand is known, constant, and independent: Stable and predictable demand.

• Lead time is known and constant: Consistent delivery times.

• Receipt of inventory is instantaneous and complete: Orders arrive in full and immediately.

• No quantity discounts: Prices remain constant regardless of order size.

• Only variable costs are setup and holding: Focus on relevant cost factors.

• No stockouts: Sufficient inventory to meet all demand.

Minimizing Costs

• Objective: Minimize total costs by balancing setup and holding costs.

• Optimal order size $Q^*$ minimizes total cost across the inventory cycle.

• Optimal quantity occurs when holding cost equals setup cost: Balancing these costs optimizes inventory levels.

• Annual setup cost = $\frac{D}{Q}S$

• Annual holding cost = $\\frac{Q}{2}H$

• $Q^* = \sqrt{\frac{2DS}{H}}$

Reorder Points (ROP)

• ROP tells "when" to order to avoid stockouts.

• $ROP = d \times L$

• where $d = \frac{D}{\text{Number of working days in a year}}$

EOQ Model - Total Cost

• $TC = \frac{D}{Q} S + \frac{Q}{2} H + PD$

Production Order Quantity Model

• Inventory builds up over time after an order is placed: gradual accumulation of inventory.

• Used when units are produced and sold simultaneously: balancing production and sales.

• Annual inventory holding cost = $\frac{1}{2}HQ\bigg[1-\frac{d}{p}\bigg]$

• $Q_p^* = \sqrt{\frac{2DS}{H\bigg[1-\frac{d}{p}\bigg]}}$

Quantity Discount Models

• Reduced prices for larger quantities: incentivizing bulk purchases.

• $Q^* = \sqrt{\frac{2DS}{IP}}$

• $TC = \frac{D}{Q} S + \frac{Q}{2} H + PD$

Single-Period Model

• One order is placed for a product: Suitable for seasonal or unique items.

• $C_s$ = Cost of shortage = Sales price/unit – Cost/unit

• $C_o$ = Cost of overage = Cost/unit – Salvage value

• Service level = $\frac{C<em>s}{C</em>s + C_o}$

Probabilistic Models and Safety Stock (ss)

• Used when demand is not constant or certain: Addressing demand variability.

• Use safety stock to achieve desired service level: Protecting against stockouts.

• $ROP = d \times L + ss$

Probabilistic Demand

• $ROP = \text{demand during lead time} + Z\sigma_{dLT}$

Other Probabilistic Models

• Demand variable, lead time constant: $ROP = (\text{Avg daily demand} \times \text{Lead time}) + Z\sigma_d\sqrt{\text{Lead time}}$

• Lead time variable, demand constant: $ROP = (\text{Daily demand} \times \text{Avg lead time}) + Z \times (\text{Daily demand}) \times \sigma_{LT}$

• Both demand and lead time variable: $ROP = (\text{Avg daily demand} \times \text{Avg lead time}) + Z\sigma_{dLT}$

  • $\sigma<em>{dLT} = \sqrt{(\text{Avg lead time} \times \sigma</em>d^2) + (\text{Avg daily demand})^2 \sigma_{LT}^2}$

Fixed-Period (P) Systems

• Orders placed at the end of a fixed period: Consistent timing for inventory replenishment.

• Inventory counted only at the end of the period: Periodic assessment of stock levels.

• Order brings inventory up to a target level: Ensuring