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14 – Advanced MRP Topics. Dr. Ron Tibben-Lembke pp. 478-. MRP Priorities. First: Get installed, part of ongoing managerial process, get users trained Understand critical linkages with other areas Achieve high levels of data integrity Link MRP with front end, engine, back end Then:

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14 – Advanced MRP Topics


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14 advanced mrp topics

14 – Advanced MRP Topics

Dr. Ron Tibben-Lembke

pp. 478-

mrp priorities
MRP Priorities
  • First:
    • Get installed, part of ongoing managerial process, get users trained
    • Understand critical linkages with other areas
    • Achieve high levels of data integrity
    • Link MRP with front end, engine, back end
  • Then:
    • Determine order quantities more exactly
    • Buffering concepts
    • Nervousness
ordering policies
Ordering Policies
  • Dependent Demand
    • Not independent demand
    • Discrete – not continuous
    • Lumpy – may have surges
  • Complexity
    • Reduces costs – ordering & holding
    • Anything other than lot-for-lot Increases lumpiness downstream
assumptions
Assumptions
  • All requirements must be available at start of period
  • All future requirements must be met, and can’t be backordered
  • System operated on periodic basis (e.g. weekly)
  • Requirements properly offset for LTs
  • Parts used uniformly through a period
    • Use average inventory levels for holding cost
example demands
Example Demands
  • Try several lot-sizing methods
    • Economic Order Quantity
    • Periodic Order Quantity
    • Part Period Balancing
    • Wagner Within
  • Order cost = $300 per order = CP
  • Inventory Carrying cost = $2 / unit/ week = CH
  • Avg Demand = 92.1 / wk = D
slide6
Minimizes total ordering & holding costs

Assumes demand same every period

Definitely not always true for this use

Avg. demand and holding cost need same time units (e.g. per week)

Economic Lot Size:

Where:

D = avg demand

CP = ordering cost

CH = holding cost

EOQ
slide7
EOQ
  • Sqrt( 2 * 300 * 92.1 / 2) = 166
slide8
EOQ
  • Ordering cost = 6 * 300 = $1,800
  • Inv carry cost = 1,532.5 * 2 = $3,065
  • Total $4,865
periodic order quantities
Periodic Order Quantities
  • EOQ
    • Gave good tradeoff between ordering & holding
    • resulted in a lot of leftovers.
  • Only order enough to get through a certain number of periods – no leftovers
  • How many? EOQ / avg. demand
    • 166 / 92.1 = 1.805 ~ 2 weeks’ worth
periodic order quantities10
Periodic Order Quantities
  • Ordering cost = 6 * 300 = $1,800
  • Inv carry cost =1,082.5 * 2 = $2,145
  • Total $3,945
part period balancing
Part Period Balancing
  • Increase the quantity until holding costs equal the ordering cost
  • Order 10 – holding = 10/2*2 = 10
  • Order 20 – holding = 10 + 10*1.5*2 = $40
  • Order 35 = 40 + 15*2.5*2 = $115
  • Order 55 = 115 + 20*3.5*2 = $255
  • Order 125 = 255 + 70*4.5*2 = $85
part period balancing12
Part Period Balancing
  • Week 5:
  • Order 70: Holding = 10*0.5*2 = $10
  • Order 250: 10 + 180*1.5*2 = $550
  • So I could:
    • Order 250 units, pay $300 in ordering and $540 holding, for a total of $840,
    • Order 70 now, 180 next week, and pay $600 in ordering and $10 + 180*0.5*2=180 in holding = $790
    • Seems like the second option is best.
part period balancing13
Part Period Balancing
  • When should we place a separate order? If 1.5*$2*D > 300. D>300/3 = 100
  • Whenever demand is >= 100, we might as well place a separate order.
  • What about week 9?
  • Order 230: holding = 230*0.5*2 = $230
  • Order 270: = 230 + 40*1.5*2 = $350
  • Order 280: = 350 + 10*3.5*2 = $420
wagner within
Wagner-Within
  • Mathematically optimal
  • Work back from planning period farthest in the future
  • Consider all possibilities:
    • Order for 5, 4 and 5, 3 and 4, then 5, etc.
    • Uses “dynamic programming” – similar to linear programming
simulation experiments
Simulation Experiments
  • What is best under real-world conditions?
    • Multiple levels to be concerned about
    • Real-time changes