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Session 1a. Decision Models -- Prof. Juran2 Overview Web Site Tour Course Introduction.

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Presentation on theme: "Session 1a. Decision Models -- Prof. Juran2 Overview Web Site Tour Course Introduction."— Presentation transcript:

1 Session 1a

2 Decision Models -- Prof. Juran2 Overview Web Site Tour Course Introduction

3 Decision Models -- Prof. Juran3 2 Modules Module I: Optimization Module II: Spreadsheet Simulation

4 Decision Models -- Prof. Juran4 What is Decision Modeling? Formulation Real world System Decision Model Decision Modeling Process Real World Conclusions Model Conclusions Deduction Interpretation Implementation

5 Decision Models -- Prof. Juran5 Seven-step Process 1.Definition 2.Data Collection 3.Formulation 4.Model Verification 5.Selection of an Alternative 6.Presentation of Results 7.Implementation

6 Decision Models -- Prof. Juran6 Revised Process for This Course 0. Conclusions and Recommendations 1. Managerial Definition 2. Formulation 3. Solution Methodology 4. Discussion? Appendices?

7 Decision Models -- Prof. Juran7 Software Microsoft Excel –Data Table –Goal Seek –Solver –Premium Solver, SolverTable –Analysis Toolpack –Charts and Graphs

8 Decision Models -- Prof. Juran8 Software The Decision Tools Suite –@Risk –PrecisionTree –TopRank –BestFit –RiskView –StatPro

9 Decision Models -- Prof. Juran9 Software Other Software –Crystal Ball –Extend –Sigma

10 Decision Models -- Prof. Juran10 Descriptive Model Approximates how a real system works (or would work) given certain assumptions Does not give us the “right answer” Focus for Module 2

11 Decision Models -- Prof. Juran11 Prescriptive Model Identifies the “right answer” Focus of Module 1

12 Decision Models -- Prof. Juran12 What is Optimization? A model with a “best” solution Strict mathematical definition of “optimal” Usually unrealistic assumptions Useful for managerial intuition

13 Decision Models -- Prof. Juran13 Elements of an Optimization Model Formulation –Decision Variables –Objective –Constraints Solution –Algorithm or Heuristic Interpretation

14 Decision Models -- Prof. Juran14 Toomer Sporting Goods

15 Decision Models -- Prof. Juran15 Managerial Problem Definition Ishani Mukherjee must decide how many to produce of two products.

16 Decision Models -- Prof. Juran16 Managerial Problem Definition 2-piece Yellow Jacket 4-piece Sachin Special

17 Decision Models -- Prof. Juran17 Formulation a)Define the choices to be made by the manager (called decision variables ). b)Find a mathematical expression for the manager's goal (called the objective function ). c)Find expressions for the things that restrict the manager's range of choices (called constraints ).

18 Decision Models -- Prof. Juran18 Decision Variables

19 Decision Models -- Prof. Juran19

20 Decision Models -- Prof. Juran20

21 Decision Models -- Prof. Juran21 Objective Function A mathematical expression of the manager’s goal in terms of the decision variables.

22 Decision Models -- Prof. Juran22 What is the objective? Maximize or minimize?

23 Decision Models -- Prof. Juran23

24 Decision Models -- Prof. Juran24

25 Decision Models -- Prof. Juran25

26 Decision Models -- Prof. Juran26

27 Decision Models -- Prof. Juran27 Constraints Find expressions for the things that restrict the manager's range of choices, in terms of the decision variables.

28 Decision Models -- Prof. Juran28 Leather Constraint Each Yellow Jacket uses 4 ounces of leather and each Sachin Special uses 5 ounces. There are 6,000 ounces available.

29 Decision Models -- Prof. Juran29 Leather Constraint

30 Decision Models -- Prof. Juran30

31 Decision Models -- Prof. Juran31 Nylon Constraint Each Yellow Jacket uses 3 meters of nylon and each Sachin Special uses 6 meters. There are 5,400 meters available.

32 Decision Models -- Prof. Juran32 Nylon Constraint

33 Decision Models -- Prof. Juran33

34 Decision Models -- Prof. Juran34 Cork Constraint Each Yellow Jacket uses 2 ounces of cork and each Sachin Special uses 4 ounces. There are 4,000 ounces available.

35 Decision Models -- Prof. Juran35 Cork Constraint

36 Decision Models -- Prof. Juran36

37 Decision Models -- Prof. Juran37 Labor Constraint Each Yellow Jacket uses 2 minutes of general labor and each Sachin Special takes 2.5 minutes. There are 3,500 minutes available.

38 Decision Models -- Prof. Juran38 Labor Constraint

39 Decision Models -- Prof. Juran39

40 Decision Models -- Prof. Juran40 Stitching Constraint Each Yellow Jacket takes 1 minute of stitching time and each Sachin Special takes 1.6 minutes. There are 2,000 minutes available.

41 Decision Models -- Prof. Juran41 Stitching Constraint

42 Decision Models -- Prof. Juran42

43 Decision Models -- Prof. Juran43 Nonnegativity Constraints Each Yellow Jacket takes 1 minute of leather and each Sachin Special takes 1.6 minutes. There are 2,000 minutes available.

44 Decision Models -- Prof. Juran44 Nonegativity Constraints

45 Decision Models -- Prof. Juran45

46 Decision Models -- Prof. Juran46

47 Decision Models -- Prof. Juran47 Solution Methodology Use algebra to find the best solution. (Simplex algorithm)

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49 Decision Models -- Prof. Juran49

50 Decision Models -- Prof. Juran50

51 Decision Models -- Prof. Juran51

52 Decision Models -- Prof. Juran52 The Optimal Solution Make 1,000 Yellow Jackets and 400 Sachin Specials Earn 179,400

53 Decision Models -- Prof. Juran53

54 Decision Models -- Prof. Juran54


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