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Production
and Operations Management
MGT613
VU
Lesson
09
Time
Series Forecasts
·Trend
-
long-term upward or downward
movement in data often relates to
population shifts,
changing
incomes, and cultural changes.
·Seasonality
-
short-term fairly regular
variations in data related to
factors like weather,
festive
holidays
and vacations. Mostly experienced by
supermarkets, restaurants, theatres,
theme
parks.
·Cycle
wavelike variations of more
than one year's duration
these occurs because of
political,
economic
and even agricultural
conditions
·Irregular
variations -
caused by unusual circumstances
such as severe weathers,
earthquakes,
worker
strikes, or major change in product or
service. They do not capture
or reflect the true
behavior
of a variable and can distort the
overall picture. These should be
identified and
removed
from the data.
·Random
variations -
caused by chance and are in reality
are the residual variations
that remain
after
the other behaviors have
been identified and accounted
for.
Forecast
Variations
Techniques
for Averaging
·Moving
average
·Weighted
moving average
·Exponential
smoothing
·Moving
average A
technique that averages a
number of recent actual
values, updated as new
values
become available.
·Weighted
moving average
More recent values in a
series are given more
weight in
computing
the forecast.
Simple
Moving Average Formula
·The
simple moving average model
assumes an average is a good estimator of
future behavior
·The
formula for the simple
moving average is:
A
t-1 + A t-2
+ A t-3 +
... + A t-n
Ft =
n
Ft =
Forecast for the coming
period
N
= Number of periods to be
averaged
At-1 =
Actual occurrence in the past
period for up to "n"
periods
Simple
Moving Average Problem
(1)
Question:
What are the 3-week and
6-week moving average forecasts for
demand?
Assume
you only have 3 weeks and 6 weeks of
actual demand data for the
respective forecasts.
37
Production
and Operations Management
MGT613
VU
Week
Demand
1
650
2
678
3
720
4
785
5
859
6
920
7
850
8
758
9
892
10
920
11
789
12
844
Simple
Moving Average Solution
(1)
W
eek
Demand
3-W eek
6-W
eek
1
650
F4=(650+678+720)/
678
3
=682.67
2
3
720
F
=(650+678+720
4
785
682.67
7
+785+859+920)/6
5
859
727.67
=768.67
6
920
788.00
7
850
854.67
768.67
8
758
876.33
802.00
9
892
842.67
815.33
10
920
833.33
844.00
11
789
856.67
866.50
12
844
867.00
854.83
38
Production
and Operations Management
MGT613
VU
Simple
Moving Average Problem (2)
Data
Question:
What is the 3 week moving
average forecast for this
data?
Assume
you only have 3 weeks and 5 weeks of
actual demand data for the
respective forecasts.
Week
Demand
1
820
2
775
3
680
4
655
5
620
6
600
7
575
Simple
Moving Average Problem (2)
Solution
W
eek
Demand
3-W
eek
5-W
eek
1
820
F4=(820+775+680)/3
=758.33
2
775
F6=(820+775+680
3
680
+655+620)/5
=710.00
4
655
758.33
5
620
703.33
6
600
651.67
710.00
7
575
625.00
666.00
39
Table of Contents:
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:Decision Making
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:Strategy
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:Service Delivery System
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:Productivity
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:The Decision Process
- INTRODUCTION TO PRODUCTION AND OPERATIONS MANAGEMENT:Demand Management
- Roadmap to the Lecture:Fundamental Types of Forecasts, Finer Classification of Forecasts
- Time Series Forecasts:Techniques for Averaging, Simple Moving Average Solution
- The formula for the moving average is:Exponential Smoothing Model, Common Nonlinear Trends
- The formula for the moving average is:Major factors in design strategy
- The formula for the moving average is:Standardization, Mass Customization
- The formula for the moving average is:DESIGN STRATEGIES
- The formula for the moving average is:Measuring Reliability, AVAILABILITY
- The formula for the moving average is:Learning Objectives, Capacity Planning
- The formula for the moving average is:Efficiency and Utilization, Evaluating Alternatives
- The formula for the moving average is:Evaluating Alternatives, Financial Analysis
- PROCESS SELECTION:Types of Operation, Intermittent Processing
- PROCESS SELECTION:Basic Layout Types, Advantages of Product Layout
- PROCESS SELECTION:Cellular Layouts, Facilities Layouts, Importance of Layout Decisions
- DESIGN OF WORK SYSTEMS:Job Design, Specialization, Methods Analysis
- LOCATION PLANNING AND ANALYSIS:MANAGING GLOBAL OPERATIONS, Regional Factors
- MANAGEMENT OF QUALITY:Dimensions of Quality, Examples of Service Quality
- SERVICE QUALITY:Moments of Truth, Perceived Service Quality, Service Gap Analysis
- TOTAL QUALITY MANAGEMENT:Determinants of Quality, Responsibility for Quality
- TQM QUALITY:Six Sigma Team, PROCESS IMPROVEMENT
- QUALITY CONTROL & QUALITY ASSURANCE:INSPECTION, Control Chart
- ACCEPTANCE SAMPLING:CHOOSING A PLAN, CONSUMER’S AND PRODUCER’S RISK
- AGGREGATE PLANNING:Demand and Capacity Options
- AGGREGATE PLANNING:Aggregate Planning Relationships, Master Scheduling
- INVENTORY MANAGEMENT:Objective of Inventory Control, Inventory Counting Systems
- INVENTORY MANAGEMENT:ABC Classification System, Cycle Counting
- INVENTORY MANAGEMENT:Economic Production Quantity Assumptions
- INVENTORY MANAGEMENT:Independent and Dependent Demand
- INVENTORY MANAGEMENT:Capacity Planning, Manufacturing Resource Planning
- JUST IN TIME PRODUCTION SYSTEMS:Organizational and Operational Strategies
- JUST IN TIME PRODUCTION SYSTEMS:Operational Benefits, Kanban Formula
- JUST IN TIME PRODUCTION SYSTEMS:Secondary Goals, Tiered Supplier Network
- SUPPLY CHAIN MANAGEMENT:Logistics, Distribution Requirements Planning
- SUPPLY CHAIN MANAGEMENT:Supply Chain Benefits and Drawbacks
- SCHEDULING:High-Volume Systems, Load Chart, Hungarian Method
- SEQUENCING:Assumptions to Priority Rules, Scheduling Service Operations
- PROJECT MANAGEMENT:Project Life Cycle, Work Breakdown Structure
- PROJECT MANAGEMENT:Computing Algorithm, Project Crashing, Risk Management
- Waiting Lines:Queuing Analysis, System Characteristics, Priority Model