session 3 university of southern california ise514 september 1, 2015 geza p. bottlik page 1 outline...

Session 3University of Southern California

ISE514 September 1, 2015

Geza P. Bottlik

Outline

• Questions?

• Sales and Operations Planning Examples

• Qualifiers and Winners

• Describe assignment 2



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Process Types

Continuous

Repetitive

Batch

Job Shop

Project



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Hayes-Wheelwright



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Order qualifiers – Order winners

On what basis do you buy a particular product?

Milk

Laptop

Car

Toothpaste



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Forecasting

Why did we skip it?



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Operations Planning

Long term determined by lead time of capacity

Make to Stock

Make to Order

Assemble to order

Engineer to order

make to order

Project



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Aggregate Planning

Demand enters as units of products

We convert these to common units such as machine hours, labor hours, earned hours, pounds of material, etc. to create an aggregate schedule

The master schedule details how many of each product are to be built in each period

The major variables are the costs of changing the level of resources such as:

• labor

• machinery

• inventory

• impact of lot sizes



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Example 1

See spreadsheet from Chapman Chapter 3



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Example 2

Note that definitions of variables are different in each book.

Our objective is to minimize the total cost by:

Varying labor levels

Varying Inventory

Varying lot sizes

t periods (length of the horizon)

n products

m resources

Inventory carrying cost

Hiring and layoff costs

Off loading (subcontracting) costs

Overtime costs



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Example (continued)

We are usually subject to a number of constraints:

Hours or shifts per day (a shift is usually 8 hours)

Workdays per month (range from 19 to 31, usually use 20)

Machine capacities (units made per hour)

Overtime limits (how long can a person work per day?)

Hours required per product (x.xxxx hrs/unit)

Non-negativity constraints (all variables >=0)



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Methods for solving Aggregate Planning Problems

• Spreadsheet trial end error

• Linear Programming (Simplex method, Dantzig 1947 –

see the link on the links page)

– Excel Solver

– Other LP programs

• Non linear optimization methods (ISE520)



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LP example



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LP Example (see spreadsheet)



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Using the Solver in Excel

The solver is located under the “Tools” menu. The dialog box looks like this:



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Using the Solver in Excel (continued)

The dialog box for the constraints look like this:



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Master Production Scheduling

Generated from the aggregate plan or directly from the demand - how many products will be produced and when they will be produced

There are three main types:

Make to stock

Make to order

Assemble to order - MPS and a FAS (Final Assembly Schedule)



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Master Production Scheduling (continued)

• The planning horizon must cover the period required

to accomplish it

– Usually 3 to 6 months

– Redo every month or more frequently

– Time fences to control decision making (inside lead

time protection)

• Length of lead time determines level of

authority required to accept orders



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Creating a Master Production Schedule

– Select items to be included (levels)

– Select planning horizon

– Select method for available to promise (ATP)

• ATP = the uncommitted portion of a company’s

inventory or planned production (one method is

called “cumulative with lookahead” )

– Combine inventory, orders, forecasts etc.



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Available to Promise with look ahead



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Creating a Master Production Schedule (continued)

– Draft, check rough cut capacity, “final’’ version

– Track daily

– Check ATP against incoming orders

– Check projected on hand against future orders

– Revise capacity as needed



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Capacity Planning

Evaluated at

MPS level - Rough cut capacity planning (RCCP)

MRP level - Capacity requirements planning (CRP)

“..capacity planning is somewhat misleading. Both RCCP and CRP are information tools rather than decision making tools. They indicate which capacity constraints are violated, but they do not provide guidance for resolving the conflict… They ignore actual lead times”

from Sipper and Bulfin



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Bill of materials

• List of All Items Required to Build a Product

– Description

– Part Number

– Quantity (With Unit of Measure)

– Revision

– Many Optional Items



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Bill of materials (continued)

• Structured or indented (levels) to signify

subassemblies

– Can be represented as a tree

– Starts with level zero (final product), lowest level =

purchased



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Lot sizing and Lead time

There are many methods to determine how much of a material item to buy in each period

Lot for Lot

Economic Order Quantity

Part Period Balancing

Least Unit Cost

Least Total Cost

Period Order Quantity

Lead time - time from knowing need to receiving it



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Lot Sizing Methods

Lot for Lot (LOL) – order the amount you need in each period

Economic Order Quantity (EOQ) – Balances Inventory holding cost against set-up cost

Q – Quantity to buy at one time, or to produce

OP – Order point = level of inventory at which we decide to order

A – cost of ordering or setting up a production lot

K – interest rate

C – value of each unit

L – lead time – time from ordering to receiving the lot

D – Annual demand



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Order Quantity and time



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Lot Sizing Methods (continued)

kC

ADQ

2



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Least Unit Cost - keep adding quantities from successive periods until the least unit cost is reached



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• Part Period Balancing – keep adding quantities from successive periods until inventory holding cost exceeds set-up cost

• Least Total Cost - keep adding quantities from successive periods until the least total cost is reached

• Period Order Quantity – determine the number of periods’ worth of material to order a priori



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Shop Floor Control

Many MRP packages include Shop Floor Control modules

These are designed to track the progress of products through a factory

The best of them, especially when tied to real time data gathering are very good at letting managers now where things are. They are very dependent on timely input of data

The newer ones will often include scheduling software as well. It is, however, more common to have the scheduling software in a separate module



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Benefits and shortcomingsBenefits:

Ability to evaluate the feasibility and requirements

Material plan

Identifying shortages

Shortcomings

Infinite capacity assumption

Uncertainty - deterministic system

Lead time discrepancies

Yield estimates

System nervousness due to rolling horizon

Integrity of data

session 3 university of southern california ise514 september 1, 2015 geza p. bottlik page 1 outline...

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