ISEN 315Spring 2011

Dr. Gary Gaukler

1. Master production schedule2. Bill of material (BOM)3. Inventory availability4. Purchase orders outstanding5. Lead times

Effective use of dependent demand inventory models requires the following

Dependent Demand

| | | | | | | |

1 2 3 4 5 6 7 8Time in weeks

F

2 weeks

3 weeks

1 week

A

2 weeks

1 weekD

E

2 weeks

D

G

1 week

1 week

2 weeks to produce

B

C

E

Start production of DMust have D and E completed here so

production can begin on B

Time-phased Product Structure

Lot Sizing For MRP Systems

Assumptions:• Consider only one item• Demand known and deterministic• Finite horizon• No shortages• No capacity constraints

Lot Sizing For MRP Systems

Problem formulation:

Lot Sizing: Silver-Meal Heuristic

In any given period, produce to cover demand in a future period as long as the average cost per period is reduced by doing so

Algorithm:1. Start in period 1. Calculate C(t): average per-period

cost if all units for next t periods produced in period 1.

2. Select lowest t such that C(t)<C(t+1): t*3. Produce enough in period 1 to cover t*4. Repeat, starting from period t*+1

Silver-Meal Example

Assume net requirements are 18, 30, 42, 5, 20Setup cost for production is $80Holding cost $2 per unit per period

Production Schedule Changes

• So far, the MRP examples we discussed were static• In reality, we need to update our production plans

as time passes, thus MRP plans become dynamic• The widest-used technique involves “rolling

horizons”:

Production Schedule Changes

• Using rolling horizons can lead to fluctuations in the production schedule

• As we include more and updated information (e.g., demand forecasts) in each period, our production schedule can change

• This is called “system nervousness”

Production Schedule Changes

• Results of fluctuations:– Planning for capacity utilization becomes difficult

• Fluctuations become larger when we re-run MRP more often

• But: re-running MRP is our only way of incorporating more information!

Shortcomings of MRP

Shortcomings of MRP

MRP II

Goal of Lean production: Supply the customer with their exact wants

when the customer wants it without waste

Method: JIT JIT is a philosophy of continuous and forced

problem solving JIT: continual improvement, pull system

Just-in-time and Lean Production

Waste is anything that does not add value from the customer point of view

Storage, inspection, delay, waiting in queues, and defective products do not add value and are 100% waste

Waste Reduction

Faster delivery, reduced work-in-process, and faster throughput all reduce waste

Reduced waste reduces room for errors emphasizing quality

Reduced inventory releases assets for other, productive purposes

Waste Reduction

JIT systems require managers to reduce variability

Variability is any deviation from the optimum process

Less variability = less waste Inventory hides variability

Variability Reduction

Inventory level

Process downtimeScrap

Setup time

Late deliveries

Quality problems

Reduce Variability

Inventory level

Scrap

Setup time

Late deliveries

Quality problems

Process downtime

Reduce Variability

A pull system uses signals to request production and delivery from upstream stations

Upstream stations only produce when signaled

System is used within the immediate production process and with suppliers

Enabling JIT: Pull System

Experiment

200 –

100 –

Inve

ntor

y

Time

Q2 When average order size = 100

average inventory is 50

Q1 When average order size = 200

average inventory is 100

Reduce Lot Sizes

High setup costs encourage large lot sizes Reducing setup costs reduces lot size and

reduces average inventory Setup time can be reduced through preparation

prior to shutdown and changeover

Reduce Setup Costs

Reduced space and inventory With reduced space, inventory must be in

very small lots Units are always moving because there is

no storage

Implications for Manufacturing