Math Problem Statement

The Hastings Company is a nation-wide wholesaler for small electronic devices. One of its most popular items is a new GPS unit called the WAMI-1000. The company operates 365 days (52 weeks) in a year. Hastings has gathered the following information:

Average demand = 1000 units/year

Standard deviation of weekly demand = 200 units

Average lead time = 5 weeks

Standard deviation of lead time= 1 week

Z (service level) =1.04

What is the optimal amount of reorder point for the company?

1139.27

1157.27

Solution

To determine the optimal reorder point, we use the formula for reorder point that incorporates both lead time demand and safety stock:

Formula:

R=DL+ZσDLR = D_L + Z \cdot \sigma_{DL}

Where:

  • RR = Reorder point
  • DLD_L = Average demand during lead time
  • ZZ = Service level factor (given as 1.04 here)
  • σDL\sigma_{DL} = Standard deviation of demand during lead time (capturing demand variability and lead time variability)

Step 1: Calculate DLD_L:

DL=Average demand per week×Lead time in weeksD_L = \text{Average demand per week} \times \text{Lead time in weeks} Average weekly demand: Weekly demand=Annual demand52=10005219.23units/week\text{Weekly demand} = \frac{\text{Annual demand}}{52} = \frac{1000}{52} \approx 19.23 \, \text{units/week} So, DLD_L becomes: DL=19.23×5=96.15D_L = 19.23 \times 5 = 96.15


Step 2: Calculate σDL\sigma_{DL}:

The standard deviation of lead time demand is calculated as: σDL=(Lead timeσd2)+(Dˉ2σLead Time2)\sigma_{DL} = \sqrt{ (\text{Lead time} \cdot \sigma_d^2) + ( \bar{D}^2 \cdot \sigma_{\text{Lead Time}}^2 ) } Where:

  • σd\sigma_d = Standard deviation of weekly demand = 200
  • Dˉ\bar{D} = Average weekly demand = 19.23
  • σLead Time\sigma_{\text{Lead Time}} = Standard deviation of lead time = 1

Now compute step-by-step:

  1. Variability due to demand: Demand term=Lead timeσd2=5(200)2=540,000=200,000\text{Demand term} = \text{Lead time} \cdot \sigma_d^2 = 5 \cdot (200)^2 = 5 \cdot 40,000 = 200,000
  2. Variability due to lead time: Lead time term=Dˉ2σLead Time2=(19.23)21=369.12\text{Lead time term} = \bar{D}^2 \cdot \sigma_{\text{Lead Time}}^2 = (19.23)^2 \cdot 1 = 369.12
  3. Total variability: σDL2=200,000+369.12    σDL=200,369.12447.63\sigma_{DL}^2 = 200,000 + 369.12 \implies \sigma_{DL} = \sqrt{200,369.12} \approx 447.63

Step 3: Calculate reorder point RR:

R=DL+ZσDLR = D_L + Z \cdot \sigma_{DL} Substitute: R=96.15+1.04447.63R = 96.15 + 1.04 \cdot 447.63 R=96.15+465.53=561.68unitsR = 96.15 + 465.53 = 561.68 \, \text{units}


Your answer of 1139.27 or 1157.27 must have been a miscalculation since the above steps validate a reorder point of approximately 561.68 units.

Would you like a detailed comparison of approaches or a deeper explanation?


Related Questions:

  1. How do changes in the service level (Z-score) affect reorder points?
  2. Why is safety stock important in inventory management?
  3. How would reducing the standard deviation of lead time affect reorder points?
  4. How can the reorder point model incorporate real-time inventory data?
  5. What alternative methods exist for determining safety stock in uncertain demand conditions?

Tip:

Always double-check units when working with lead time and demand. Mismatched units (weekly vs annual) often lead to incorrect results.

Ask a new question for Free

By Image

Drop file here or Click Here to upload

Math Problem Analysis

Mathematical Concepts

Inventory Management
Statistics
Probability

Formulas

Reorder Point Formula: R = D_L + Z * σ_DL
Average Lead Time Demand: D_L = Weekly Demand * Lead Time
Standard Deviation of Lead Time Demand: σ_DL = sqrt((Lead Time * σ_d^2) + (Average Demand^2 * σ_LeadTime^2))

Theorems

Central Limit Theorem (implicit in variability calculations)
Z-score application for service level determination

Suitable Grade Level

Undergraduate Level (Business, Operations Management, or Applied Mathematics)