2. Production Planning
Production planning is a statement to the production
plans in the aggregate.
Production planning associated with the
determination of the volume, timeliness of
completion, capacity utilization and load balancing.
Production planning is a means of communication
between the top management and manufacturing.
3. Purpose
As an initial step to determine the production activity
as a reference more detailed planning of the
aggregate plan item in the master production
schedule.
As input resource plan planning resource that can be
developed to support production planning.
Stability of production and labor to fluctuations in
demand.
4. Aggregate Planning
Aggregate planning is the planning that was made to
determine the total demand of all elements of production
and the amount of labor required Combines appropriate
resources into general terms
If the products are similar, an “average” item can represent
the aggregate unit
If there are variety of products then the aggregate unit may
be
Weight (tons of steel)
Volume (gallons of gasoline)
Amount of work required (hours of labor)
Dollar value (value of the inventory in dollar)
5. Aggregate Planning
Benefits of Using Aggregate Planning:
Ease of data processing
Accuracy results obtained
Easy to see and understand the mechanisms of
production systems that occur in the implementation of
the plan.
6. Forecasting
The process of predicting the values of a certain
quantity, over a certain time horizon, based on past
trends and/or a number of relevant factors.
An estimate of future demand & provides the basis
for planning decisions
7. Forecasting Techniques
• based on opinion and
intuition
Qualitative
forecasting
• uses mathematical
models and historical
data to make forecasts.
Quantitative
forecasting
8. Qualitative Methods
Delphi method
Management Estimate or Panel Consensus
Market Research
Structured Group Method
Historical Analogy
9. Quantitative Methods
The use of qualitative methods:
Does not require quantitative data
Element of subjectivity very big influence in
forecasting results
Good for long-term forecasting
10. Quantitative Methods
• based on assumption that the
future is an extention of the
past. Historical data is used to
predict future demand.
Time
series
forecasting
• assumes that one or more
factors (dependent variables)
predict future demand.
Causal
11. Time Series Forecasting
Time Series
Regresion
Konstant
Linier
Cyclic
Quadratic
Smoothing
Average
Moving
Average
Single
Double
Centred
Exponential
Smoothing
Single
Double/Trend
Winter
13. Forecast Error Analysis
The forecast error at time period is the difference
between the actual data value and the forecast value
for that period.
Notes:
e= error
)(')()( tdtdte
14. Forecast Error Analysis (Cont.)
Mean Absolute Error (MAE)/Mean Absolute Deviation
(MAD)
Sum Square Error (SSE)
Mean Square Error (MSE)
15. Precentage Error (PE)
Mean Absolute Precentage Error (MAPE)
Standar Error Estimation (SSE)
