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• Class 5: (Feb 7): Chap 11 (Inventory Management , Forecasting, Chapter 10 – Just in Time/Lean/TOC)
• Class 6: (Feb 14): Research for Presentations• February 21 No Class• Class 7: (Feb 28) Supplemental Readings
(Reverse Logistics – need “The Forklifts Have Nothing To Do!” Available in the Lewis and Clark Bookstore); Supply Chain Security, Take home final exam
• Class 8: (Mar 7) Group presentations; Final Due
New Syllabus
How far into the future do you typically project when trying to forecast the health of your industry? ]less than 4 months 3%]4-6 months 12%
]7-12 months 28% ]> 12 months 57%
Forecasting Survey
Fortune Council survey, Nov 2005
Consumer price index 51%Consumer Confidence index 44%Durable goods orders 20%Gross Domestic Product 35%Manufacturing and trade inventories and
sales 27%Price of oil/barrel 34%Strength of US $ 46%Unemployment rate 53%Interest rates/fed funds 59%
Indices to forecast health of industry
Fortune Council survey, Nov 2005
Improving customer demand forecasting and sharing the information downstream will allow more efficient scheduling and inventory management
Boeing, 1987: $2.6 billion write down due to “raw material shortages, internal and supplier parts shortages” Wall Street Journal, Oct 23, 1987
Forecasting Importance
“Second Quarter sales at US Surgical Corporation decline 25%, resulting in a $22 mil loss…attributed to larger than anticipated inventories on shelves of hospitals.” US Surgical Quarterly, Jul 1993
“IBM sells out new Aetna PC; shortage may cost millions in potential revenue.” Wall Street Journal, Oct 7, 1994
Forecasting Importance
Forecasts are usually wrong every forecast should include an
estimate of error Forecasts are more accurate for
families or groups Forecasts are more accurate for nearer
periods.
Principles of Forecasting
• Record Data in the same terms as needed in the forecast – production data for production forecasts; time periods
• Record circumstances related to the data• Record the demand separately for different
customer groups
Important Factors to Improve Forecasting
• Extrinsic Techniques – projections based on indicators that relate to products – examples
• Intrinsic – historical data used to forecast (most common)
Forecast Techniques
Forecasting errors can increase the total cost of ownership for a product - inventory carrying costs
- obsolete inventory- lack of sufficient inventory- quality of products due to
accepting marginal products to prevent stockout
Forecasting
• Essential for smooth operations of business organizations
• Estimates of the occurrence, timing, or magnitude of uncertain future events
• Costs of forecasting: excess labor; excess materials; expediting costs; lost revenues
Forecasting
Forecasting• Predicting future events• Usually demand behavior
over a time frame• Qualitative methods
• Based on subjective methods
• Quantitative methods• Based on mathematical formulas
Time Frame• Short-range to medium-range
• Daily, weekly monthly forecasts of sales data
• Up to 2 years into the future
• Long-range• Strategic planning of goals,
products, markets• Planning beyond 2 years into
the future
Demand Behavior• Trend
• gradual, long-term up or down movement
• Cycle• up & down movement repeating over
long time frame• Seasonal pattern
• periodic oscillation in demand which repeats
• Random movements follow no pattern
Forms of Forecast Movement
TimeTime(a) Trend(a) Trend
TimeTime(d) Trend with seasonal pattern(d) Trend with seasonal pattern
TimeTime(c) Seasonal pattern(c) Seasonal pattern
TimeTime(b) Cycle(b) Cycle
Dem
and
Dem
and
Dem
and
Dem
and
Dem
and
Dem
and
Dem
and
Dem
and
Random Random movementmovement
Forecasting Methods
• Time series• Regression or causal modeling
• Qualitative methods• Management judgment, expertise,
opinion• Use management, marketing,
purchasing, engineering• Delphi method
• Solicit forecasts from experts
Time Series Methods• Statistical methods using historical data
• Moving average• Exponential smoothing• Linear trend line
• Assume patterns will repeat• Naive forecasts
• Forecast = data from last period
Moving Average
Average several periods of data
Dampen, smooth out changes
Use when demand is stable with no trend or seasonal pattern
Sum of Demand In n Periods
n
Simple Moving Average
JanJan 120120FebFeb 9090MarMar 100100AprApr 7575MayMay 110110JuneJune 5050JulyJuly 7575AugAug 130130SeptSept 110110OctOct 9090
ORDERSORDERSMONTHMONTH PER MONTHPER MONTH
JanJan 120120FebFeb 9090MarMar 100100AprApr 7575MayMay 110110JuneJune 5050JulyJuly 7575AugAug 130130SeptSept 110110OctOct 9090
ORDERSORDERSMONTHMONTH PER MONTHPER MONTH
MAMAnovnov = = 33
==90 + 110 + 13090 + 110 + 130
33
= 110 orders for Nov
Simple Moving Average
Daug+Dsep+Doct
JanJan 120120 ––FebFeb 9090 – –MarMar 100100 – –AprApr 7575 103.3103.3MayMay 110110 88.388.3JuneJune 5050 95.095.0JulyJuly 7575 78.378.3AugAug 130130 78.378.3SeptSept 110110 85.085.0OctOct 9090 105.0105.0NovNov – – 110.0110.0
ORDERSORDERS THREE-MONTHTHREE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE
Simple Moving Average
JanJan 120120 ––FebFeb 9090 – –MarMar 100100 – –AprApr 7575 103.3103.3MayMay 110110 88.388.3JuneJune 5050 95.095.0JulyJuly 7575 78.378.3AugAug 130130 78.378.3SeptSept 110110 85.085.0OctOct 9090 105.0105.0NovNov – – 110.0110.0
ORDERSORDERS THREE-MONTHTHREE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE
==90 + 110 + 130 + 75 + 5090 + 110 + 130 + 75 + 5055
= 91 orders for Nov
Simple Moving Average
Simple Moving Average
JanJan 120120 –– – –FebFeb 9090 – – – –MarMar 100100 – – – –AprApr 7575 103.3103.3 – –MayMay 110110 88.388.3 – –JuneJune 5050 95.095.0 99.099.0JulyJuly 7575 78.378.3 85.085.0AugAug 130130 78.378.3 82.082.0SeptSept 110110 85.085.0 88.088.0OctOct 9090 105.0105.0 95.095.0NovNov – – 110.0110.0 91.091.0
ORDERSORDERS THREE-MONTHTHREE-MONTH FIVE-MONTHFIVE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE MOVING AVERAGEMOVING AVERAGE
Weighted Moving Average
WMAn = i = 1 Wi Di
where
Wi = the weight for period i, between 0
and 100 percent
Wi = 1.00
Adjusts moving average method to more closely reflect data fluctuations
Weighted Moving Average Example
MONTH WEIGHT DATA
August 17% 130September 33% 110October 50% 90
November forecast
WMA3 = 3
i = 1Wi Di
= (0.50)(90) + (0.33)(110) + (0.17)(130)
= 103.4 orders
3 Month = 110 5 month = 91
• Averaging method • Weights most recent data
more strongly• Reacts more to recent
changes• Widely used, accurate
method
Exponential Smoothing
Ft +1 = Dt + (1 - )Ft
where
Ft +1 =forecast for next period
Dt =actual demand for present period
Ft =previously determined forecast for present period
= weighting factor, smoothing constant
Averaging method
Weights most recent data more strongly
Reacts more to recent changes
Widely used, accurate method
Exponential Smoothing
Forecast = (weighting factor)x(actual demand for period)+(1-weighting factor)x(previously determined forecast for present period)
Forecast for Next Period
0 > <= 1Lesserreactionto recent demand
Greaterreactionto recent demand
Forecast Control
Reasons for out-of-control forecasts• Change in trend• Appearance of cycle• Weather changes• Promotions• Competition• Politics
JIT In Services
Competition on speed & qualityCompetition on speed & qualityMultifunctional department store Multifunctional department store
workersworkersWork cells at fast-food restaurantsWork cells at fast-food restaurantsJust-in-time publishing for Just-in-time publishing for
textbooks - on demand publishing textbooks - on demand publishing a growing industrya growing industry
Construction firms receiving Construction firms receiving material just as neededmaterial just as needed
Producing only what is needed, Producing only what is needed, when it is neededwhen it is needed
A philosophy A philosophy An integrated management systemAn integrated management systemJIT’s mandate: JIT’s mandate:
Eliminate all wasteEliminate all waste
What is JIT ?
....
TPS is a production management system that aims for the “ideal” through continuous improvement
Includes, but goes way beyond JIT. Pillars: Synchronization
Reduce transfer batch sizes Level load production Pull production control systems (vs. push): Kanban Quality at source Layout: Cellular operations
Continuous Improvement (Kaizen): through visibility & empowerment
Lean Operations:Best Implementation is Toyota Production System
1. Overproduction
2. Waiting
3. Inessential handling
4. Non-value adding processing
5. Inventory in excess of immediate needs
6. Inessential motion
7. Correction necessitated by defects
Toyota’s waste elimination in Operations
Flexible Resources
Multifunctional workersMultifunctional workersGeneral purpose machinesGeneral purpose machinesStudy operators & improve Study operators & improve
operationsoperations
Pre-planned issues of supplies/merchandise regardless of customer demand criteria
Creates excess and shortages not efficient over the long run
The Push System
The Pull System
Material is pulled through the system when needed
Reversal of traditional push system where material is pushed according to a schedule
Forces cooperationPrevent over and
underproduction
Kanban Production Control System
Kanban card indicates standard quantity of production
Derived from two-bin inventory system
Kanban maintains discipline of pull production
Production kanban authorizes production
Withdrawal kanban authorizes movement of goods
Types of Kanbans Bin Kanban - when bin is empty
replenish Kanban Square
Marked area designed to hold items Signal Kanban
Triangular kanban used to signal production at the previous workstation
Material KanbanUsed to order material in advance of
a process Supplier Kanbans
Rotate between the factory and suppliers
Components of Lead Time
Processing time Reduce number of items or
improve efficiencyMove time
Reduce distances, simplify movements, standardize routings
Waiting time Better scheduling, sufficient
capacitySetup time
Generally the biggest bottleneck
Preset Buttons/settings Quick fasteners Reduce tool requirements Locator pins Guides to prevent misalignment Standardization Easier movement
Common Techniques for Reducing Setup Time
Uniform Production
Results from smoothing production Results from smoothing production requirementsrequirements
Kanban systems can handle +/- 10% Kanban systems can handle +/- 10% demand changesdemand changes
Smooths demand across planning Smooths demand across planning horizonhorizon
Mixed-model assembly steadies Mixed-model assembly steadies component productioncomponent production
Quality at the Source
Jidoka is authority to stop production Jidoka is authority to stop production lineline
Andon lights signal quality problemsAndon lights signal quality problemsUndercapacity scheduling allows for Undercapacity scheduling allows for
planning, problem solving & planning, problem solving & maintenancemaintenance
Visual control makes problems visibleVisual control makes problems visiblePoka-yoke prevents defects (mistake Poka-yoke prevents defects (mistake
proof the system)proof the system)
Kaizen
Continuous improvementContinuous improvementRequires total employment Requires total employment
involvementinvolvementEssence of JIT is willingness of Essence of JIT is willingness of
workers toworkers toSpot quality problemsSpot quality problemsHalt production when necessaryHalt production when necessaryGenerate ideas for improvementGenerate ideas for improvementAnalyze problemsAnalyze problemsPerform different functionsPerform different functions
Goals of JIT
1. Reduced inventory - where?
2. Improved quality3. Lower costs4. Reduced space
requirements5. Shorter lead
time6. Increased
productivity7. Greater
flexibility
8. Better relations with suppliers
9. Simplified scheduling and control activities
10.Increased capacity11.Better use of
human resources12.More product
variety13.Continuous
Process Improvement
Use JIT to finely tune an operating system
Somewhat different in USA than Japan
JIT is still evolving JIT as an inventory reduction
program isn’t for everyone - JIT as a CPI program is!
Some systems need Just-in-Case inventory
JIT Implementation
The average manufacturing organization spends 53.2% of every sales dollar on raw materials, components, and maintenance repair parts
Inventory Control – how many parts, pieces, components, raw materials and finished goods
Why is Inventory Important to Operations Management?
Accounting – zero inventory Production – surplus inventory or “just in
case” safety stocks Marketing – full warehouses of finished
product Purchasing – caught in the middle trying to
please 3 masters
Inventory Conflict
InventoryStock of items held to meet
future demand Insurance against stock outCoverage for inefficiencies in
systems Inventory management answers
two questions How much to order When to order
Types of Inventory
Raw materials Purchased parts and supplies In-process (partially completed) products Component parts Working capital Tools, machinery, and equipment Safety stock Just-in-case
Transportation Problems
Poor Quality
InventoryAccuracy
Policies
Training
Inventory Hides Inventory Hides ProblemsProblems
1. How much do we have now?2. How much do we want?3. What will be the output?4. What input must we get?
Correctly answering the question about when to order is far more important than determining how much to order.
Aggregate Inventory Management
Inventory Costs
Carrying Cost Cost of holding an item in inventory As high as 25-35% of value Insurance, maintenance, physical inventory, pilferage,
obsolete, damaged, lost Ordering Cost
Cost of replenishing inventory Shortage Cost
Temporary or permanent loss of sales when demand cannot be met
ABC Classification System
Demand volume and value of items vary Classify inventory into 3 categories,
typically on the basis of the dollar value to the firm
PERCENTAGEPERCENTAGE PERCENTAGEPERCENTAGECLASSCLASS OF UNITSOF UNITS OF DOLLARSOF DOLLARS
AA 5 - 155 - 15 70 - 8070 - 80BB 3030 1515CC 50 - 6050 - 60 5 - 105 - 10
Assumptions of Basic EOQ Model
Demand is known with certainty and is constant over time
No shortages are allowedLead time for the receipt of orders
is constantThe order quantity is received all
at once
Customer specifies quantity Production run is not limited by equipment
constraints Product shelf life is short Tool/die life limits production runs Raw material batches limit order quantity
No reason to use EOQ if:
EOQ Formula
EOQEOQ = =22CCooDD
CCcc
Co = Ordering costs
D= Annual Demand
Cc = Carrying Costs
Cost per order can increase if size of orders decreases
Most companies have no ideaof actual carrying costs
When to Order
Reorder Point is the level of inventory Reorder Point is the level of inventory at which a new order is placed at which a new order is placed
RR = = dLdL
wherewhere
dd = demand rate per period = demand rate per periodLL = lead time = lead time
Accurate Demand Forecast Length of Lead Time Size of order quantities Service level
Why Safety Stock
Vendor-Managed Inventory
Not a new concept – same process used by bread deliveries to stores for decades
Reduces need for warehousing Increased speed, reduced errors, and improved
service Onus is on the supplier to keep the shelves full or
assembly lines running variation of JIT Proctor&Gamble - Wal-Mart DLA – moving from a manager of supplies to a
manager of suppliers Direct Vendor Deliveries – loss of visibility
Defining stock-keeping units (SKUs) Increase in number of SKUs – 15% over past 3
years Dead inventory Deals Substitute items Complementary items Informal arrangements outside the distribution
channel Repair/replacement parts Reverse logistics
Inventory Management: Special Concerns