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The operations function
Consists of all activities directly related to producing goods or providing services
The management of systems or processes
that create goods and/or provide services
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Inputs
Land
Labor
Capital
Transformation/
Conversion
process
Outputs
Goods
Services
Control
Feedback
Feedback
Feedback
Figure 1.4
Support Processes
Customer
Information
Product
Funds
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Global Competition
Rapid Technological Change
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Forecasting
Lean Systems-Characteristics
“Pull” method of work flow-a method in which customer demand activates production of the service or item.
Quality at the Source-one approach is to use “poka-yoke” or a mistake-proofing method aimed at designing fail-safe systems that minimize human error.
Small lot sizes/set up times.
Uniform workstation loads.-advance scheduling,differential pricing.
Standardized components and work methods-this increases repeatability..
Close supplier ties-frequent supplies,short lead time,high quality..
Flexible workforce-to help relieve bottlenecks as they arise without the need for inventory buffers.
Line flows-OWMM and Group Technology methods.
Automation-ex. bank ATMs.
Five “S”-Sort,Straighten,Shine,Standardize,Sustain.
Excess capacity or inventory hides underlying problems with processes that produce a service or a product (synonymous to water surface hiding the rocks).
Lean Systems provide the mechanism for management to reveal the problems by systematically lowering capacities or inventories till the problems are exposed.
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Lean Systems-Mechanisms
The “Kanban” System-A Japanese system used to control the flow of production through a factory.
Value Stream Mapping-A qualitative tool for eliminating waste or “muda” that involves a current state drawing,a future state drawing and an implementation plan.
JIT II-The supplier is brought into the plant to be an active member of the purchasing office of the customer by way of an “in-plant representative” of the supplier stationed full-time at the supplier’s expense..
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Waste
Definition
Overproduction
Inappropriate Processing
Using expensive high precision equipment when simpler machines would suffice.
Waiting
Wasteful time of people incurred when product is not being moved or processed.
Transportation
Motion
Unnecessary effort related to the ergonomics of bending, stretching, reaching, lifting, and walking.
6. Inventory
Excess inventory hides problems on the shop floor, consumes space, increases lead times, and inhibits communication.
Defects
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What is Operations Research?
Operations Research is the scientific approach to execute decision making, which consists of:
The art of mathematical modeling of complex situations
The science of the development of solution techniques used to solve these models
The ability to effectively communicate the results to the decision maker
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• Integer Programming • Queuing Theory (waiting lines)
• Nonlinear Programming • Decision Analysis
Inventory Models Game Theory
Used to help managers
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Types of products and services to offer
Facility and equipment levels
Generally involves short- and medium-range plans related to:
Inventory management
Workforce levels
Forecasts more accurate for
Common Features
Cost effective
Step 1 Determine purpose of forecast
Step 2 Establish a time horizon
Step 3 Select a forecasting technique
Step 4 Gather and analyze data
Step 5 Make the forecast
Step 6 Monitor the forecast
“The forecast”
Judgmental - uses subjective inputs (qualitative)
Time series - uses historical data assuming the future will be like the past (quantitative)
Associative models - uses explanatory variables to predict the future
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Sales force.
Seasonality - short-term regular variations in data
Cycle – wavelike variations of more than one year’s duration
Irregular variations - caused by unusual circumstances
Random variations (Stable)- caused by chance
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Naive Method
The forecast for any period equals the previous period’s actual value.
Uh, give me a minute....
We sold 250 wheels last
week.... Now, next week we should sell....
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Data analysis is nonexistent
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Seasonal variations
Next value in a series will equal the previous value in a comparable period
Data with trends
Moving Averages
Simple Moving average – A technique that averages a number of recent actual values, updated as new values become available.

t = Specified number of time periods
a = Value of Ft at t = 0
b = Slope of the line
0 1 2 3 4 5 t
Ft
Seasonality is the percentage of average (or trend) amount
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Simple Linear Regression – linear variation between the two variables
Correlation coefficient r gives an indication of the strength of relationship between the two
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Mean Absolute Deviation (MAD)
Average absolute percent error
Used to detect non-randomness in errors
Control limits:
UCL=0+z√MSE;LCL=0-z√MSE (z typically=2 or 3)
Forecasting errors are in control if
All errors are within the control limits
No patterns, such as trends are present
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Bias – Persistent tendency for forecasts to be
Greater or less than actual values.
Value of zero would be ideal for Tracking signal.
Limits of +/-4 or +/- 5are often used for a range of
acceptable values of the tracking signal.
Tracking signal
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Two most important factors
Historical data
Forecast horizon
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