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Planning Modern Green Manufacturing Systems: Forecasting
Tech 147: Unit 3 Planning Modern Green Manufacturing Systems: Forecasting
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On Planning for Future If a man take no thought about what is distant, he will find sorrow near at hand (Confucius)
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Forecasting Defined The process of estimation in unknown situations
The process of prediction The practice of demand planning
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Definitions Exponential smoothing Trend (e.g. seasonal)
Forecast Prediction Growth analysis Qualitative forecast Horizon Quantitative forecast MRP Time-series forecast Lead time Regression forecast Model-forecast Moving average Kanban JIT Planning period Gross/net requirements Inventory item Scheduled receipts
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Jacobs Et Al Chapter 2: Demand Management
Through demand management all potential demands on manufacturing capacity are collected and coordinated This activity manages day-to-day interactions between customers and the company
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Demand Management in the MPC System
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Demand Management and the MPC Environment
Forecasts of end items, spare parts, and other items in demand should be a part of the front-end modules of the MPC system
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Demand Management Techniques
Aggregating and disaggregating forecasts Make to stock demand management Assemble-to-order demand management Make-to-order demand management (engineer-to-order)
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Managing Demand Organizing for demand management
Monitoring the demand management system Balancing supply and demand
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Jacobs et al: Chapter 3 Forecasting
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Forecasting Defined Forecasting is the process of making statements, estimation, or predictions about events or some variable of interest at some specified future date whose actual outcomes have not yet been observed.
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Providing appropriate Forecast Information
Forecasting for strategic business planning Forecasting for sales and operation planning Forecasting for master production scheduling and control
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Basic Forecasting Techniques
Causal/econometric methods Time (trend) series Judgmental methods Other methods
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Causal/Econometric Methods
Regression analysis using linear regression or non-linear regression Autoregressive moving average (ARMA) Autoregressive integrated moving average (ARIMA) Econometrics
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Regression analysis includes any techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. Regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed
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Regression Analysis
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Time series Moving average Basic exponential smoothing model
Trend enhancement of the basic exponential smoothing Seasonal enhancement of the basic exponential smoothing Extrapolation Linear prediction Trend estimation Growth curve
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Time Series Elapsed Time (s) "Speed" (ms−1) 1 3 2 7 12 4 20 5 30 6 45
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Forecasted Monthly Sales
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Judgmental methods Composite forecasts Surveys Delphi method
Scenario building Technology forecasting Forecast by analogy
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Moving Average A moving average is a set of numbers, each of which is the average of the corresponding subset of a larger set of data points.
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Moving Average Example
For sales during six periods: Period 1 = $10000 Period 2 = $12000 Period 3 = $9000 Period 4 = $11000 Period 5 = $9600 Period 6 = $12100
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Moving Average Example
Sales for period 7 would be the average of the previous six periods: Or = $10617
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Trend enhancement of the basic exponential smoothing
Forecasting technique that uses a weighted moving average of past data as the basis for a forecast. The procedure gives heaviest weight to more recent information and smaller weight to observations in the more distant past. The reason for this is that the future may be more dependent upon the recent past than on the distant past. The method is effective when there is random demand and no seasonal fluctuations in the data.
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Trend enhancement of the basic exponential smoothing
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Trend enhancement of the basic exponential smoothing
New Forecast = Old Forecast + α (Actual - Old Forecast)
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Trend enhancement of the basic exponential smoothing
ESFt-1 + (actual demandt - ESFt-1)
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Trend enhancement of the basic exponential smoothing
TEFt = Base valuet-1 + Trendt-1 Base value = (actual demandt) +(1 – ) (Base valuet-1 + Trendt-1) Trendt = (base valuet – base valuet-1) + (1 – )(Trendt-1) = Base value smoothing constant = trend smoothing constant t = current time
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Other forecasting methods
Simulation Prediction market Probabilistic forecasting
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Probabilistic Forecasting
The probability of event A is the number of ways event A can occur divided by the total number of possible outcomes. It is expressed as: P(A) = The Number of Ways Event A Can Occur The Total Number of Possible Outcomes Requires knowledge of theorems of probability
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Inventory Models Economic order quantity (EOQ)
Computerized inventory control systems Manual inventory system
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EOQ An inventory-related equation that determines the optimum order quantity that a company should hold in its inventory given a set cost of production, demand rate and other variables. This is done to minimize variable inventory costs. The full equation is as follows: Where : S = Setup costs D = Demand rate P = Production cost I = Interest rate
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Worker-Orienetd Values: Honesty, Self-Control, and Self-Respect
Obi, Chapter 3 Worker-Orienetd Values: Honesty, Self-Control, and Self-Respect
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Honesty Truthfulness Sincerity Upright conduct Upright disposition
Publishers Clearing House example
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Ramifications of Workplace Honesty
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Areas of Workplace Dishonesty
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Self-Control Self-control = Self-restraint
A worker’s ability to manage his or her own actions, desires, or motions. Ability to hold back one’s self from some actions, desires or emotions that are most often experienced in the work place
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Common Areas of Self-Control
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Some Consequences of Lack of Self-Control in the Workplace
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Self-Respect Having proper regard for one’s own person, character, or reputation. Due respect for oneself.
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Some Areas of Self-Respect
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