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Unit 3

Unit 3. Planning Modern Green Manufacturing Systems: Forecasting. On Planning for Future. If a man take no thought about what is distant, he will find sorrow near at hand (Confucius). Forecasting Defined. The process of estimation in unknown situations The process of prediction

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Unit 3

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  1. Unit 3 Planning Modern Green Manufacturing Systems: Forecasting

  2. On Planning for Future If a man take no thought about what is distant, he will find sorrow near at hand (Confucius)

  3. Forecasting Defined • The process of estimation in unknown situations • The process of prediction • The practice of demand planning

  4. 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

  5. Jacobs Et Al Chapter 3: 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

  6. Demand Management in the MPC System

  7. 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

  8. 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)

  9. Communications with Other MPC Modules and Customers • Sales and operations planning • Master production scheduling • Dealing with the customer on a day-to-day basis

  10. Information Use in Demand Management • Make-to-Knowledge • Data capture and monitoring • Customer relationship management • Outbound product flow

  11. Managing Demand • Organizing for demand management • Monitoring the demand management system • Balancing supply and demand

  12. Jacobs et all: Chapter 4 Forecasting

  13. 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.

  14. Providing appropriate Forecast Information • Forecasting for strategic business planning • Forecasting for sales and operation planning • Forecasting for master production scheduling and control

  15. Basic Forecasting Techniques • Causal/econometric methods • Time (trend) series • Judgmental methods • Other methods

  16. Causal/Econometric Methods • Regression analysis using linear regression or non-linear regression • Autoregressive moving average (ARMA) • Autoregressive integrated moving average (ARIMA) • Econometrics

  17. 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

  18. Regression Analysis

  19. Judgmental methods • Composite forecasts • Surveys • Delphi method • Scenario building • Technology forecasting • Forecast by analogy

  20. 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

  21. Time Series

  22. Forecasted Monthly Sales

  23. 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.

  24. 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

  25. Moving Average Example Sales for period 7 would be the average of the previous six periods: Or 10000+12000+9000+11000+9600+12100 = $10617

  26. 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.

  27. Trend enhancement of the basic exponential smoothing

  28. Trend enhancement of the basic exponential smoothing New Forecast = Old Forecast + α (Actual - Old Forecast)

  29. Trend enhancement of the basic exponential smoothing ESFt-1 + (actual demandt - ESFt-1)

  30. 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

  31. Other forecasting methods • Simulation • Prediction market • Probabilistic forecasting

  32. 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: Requires knowledge of theorems of probability

  33. Inventory Models • Economic order quantity (EOQ) • Computerized inventory control systems • Manual inventory system

  34. 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 = Interestrate  

  35. Obi, Chapter 3 Worker-Orienetd Values: Honesty, Self-Control, and Self-Respect

  36. Honesty Truthfulness Sincerity Upright conduct Upright disposition Publishers Clearing House example

  37. Ramifications of Workplace Honesty

  38. Areas of Workplace Dishonesty

  39. 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

  40. Common Areas of Self-Control

  41. Some Consequences of Lack of Self-Control in the Workplace

  42. Self-Respect • Having proper regard for one’s own person, character, or reputation. • Due respect for oneself.

  43. Some Areas of Self-Respect

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