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•Assess long-term capacity needs •Develop budgets, hiring plans, etc. •Plan production or order materials •Get agreement within firm and acrosssupply chain partners |
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•Almost always wrong by some amount •More accurate for groupsor families •More accurate for shortertime periods •No substitute for calculated demand. |
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Quantitative Methods qualitative |
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Executive opinions •Sales force composite •Consumer surveys •Outside opinions •Delphi method |
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Basic time series models •Linear regression –For time series orcausal modeling •Measuring forecast accuracy •Mini-case: Northcutt Bikes (A) |
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•Sophisticated weight averaging model •Needs only three numbers: Ft= Forecast for the current period tDt= Actual demand for the current period ta= Weight between 0 and 1 |
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Time series assume that demand is a function of time. This is not always true.1. Pounds of BBQ eaten at party. 2. Dollars spent on drought relief. 3. Lumber sales. Linear regression can be used in these situations as well. |
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Measures of Forecast Accuracy
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Error = Actual demand –Forecast |
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Process Choice & Layout Decisions
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•Manufacturing Processes –Expensive –Have different strength & Weaknesses –Include people, equipment, facilities, physical layout, & information systems •Layout Decisions |
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Classic Engineering Viewpoint
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Four Transformation Processes Conversion Fabrication AssemblyTesting“Advances in Engineering increase and improve the alternatives available” |
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•What conversion steps must be done? •What are the productionvolumes like? •How similar are the various products we make (can we standardize)? •If the product is customized, how late in the process does it occur? |
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Classic Manufacturing Processes
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Line Flow –Continuous Flow –Production Line (Assembly Line) •Intermittent Processing –Batch Flow –Flow (Job) Shop •Project Classic Manufacturing Processes |
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