BUS FPX 4014 Assessment 5 Inventory and Ordering Decisions

BUS FPX 4014 Assessment 5 Inventory and Ordering Decisions

Student Name

Capella University

BUS-FPX4014 Operations Management for Competitive Advantage

Prof. Name

Date

Question #1

Calculate and provide the numeric monthly aggregate production rate rounded to a whole number. The level production rate is the total units per period. The formula for the Aggregate Production Rate (APR) is:

APR=M(D1+D2+D3+D4+D5+D6−SI+EI)​

Given:

• Six-Month Demand (= 1,535)
• Period 1 (= 240)
• Period 2 (= 225)
• Period 3 (= 265)
• Period 4 (= 270)
• Period 5 (= 260)
• Period 6 (= 275)

Net Requirement (= 1,535 + 50 – 150 = 1,435)

Monthly APR =(240+225+265+270+260+275−150+50)6=239=6(240+225+265+270+260+

275−150+50)​=239 (rounded).

Question #2

What is the equation for the number of workers needed to meet the aggregate production rate?

168​=48 units per month per worker. 4831=1.6 units a day per worker.3148​=1.6 units a day per worker. 23131=7.45 units a day.31231​=7.45 units a day. 7.451.6=4.66 daily workers.1.67.45​=4.66 daily workers. 4.66×31=145 $4.66\times 31=145$

$\text{workers needed to produce 231 units in one month.}$

Question #3

Provide the algebraic equation for the economic order quantity rounded to the closest whole number.

EOQ=(2×OC×UHCAQ​) ���=(2×10×54002)=54,000EOQ=(2×10×25400​)=54,000 54,000=23254,000​=232

Question #4

Provide the algebraic equation for the reorder point.

$RP=DQ\times LT$ $RP=22\times 5$ $RP=110$

Question #5

Describe the below forecasting methods and the math associated with each method, along with the pros and cons of using it.

• Naïve

  • Estimating technique used as a comparison without adjusting.
  • Pro: Easy, quick, benchmarking.
  • Con: Accuracy, cannot forecast turning points.

• Simple Mean

  • An average of all available data.
  • Pro: Easy to calculate, easy to use for patterns.
  • Con: No actual value, as only averages provided.

• Simple Moving Average

  • Takes recent actual values and then averages them.
  • Pro: Easy to calculate and understand.
  • Con: All values are calculated equally.

• Weighted Moving Average

  • Recent values are given more weight in calculating the forecast.
  • Pro: Reflective upon updated data.
  • Con: Complex calculations required.

• Exponential Smoothing

  • Recent data with more weight.
  • Pro: More weight within updated data.
  • Con: Data includes potentially unnecessary data impacting total forecast.

• Linear Trend Line

  • Straight line through a set of data through time series.
  • Pro: Multiple statistics can be added.
  • Con: Too much data with one independent variable.