PPT-Process Analysis II Operations -- Prof. Juran

2 Outline Types of Processes Kristin Benihana Scientific Management Operations Prof Juran 3 IV Continuous Flow III Assembly Line II Batch I Job Shop Low Volume One of a. Operations -- Prof. Juran. 2. Overview. Basic definitions and metrics. Examples of some theoretical models. Operations -- Prof. Juran. 3. Basic Queueing Theory. A set of mathematical tools for the analysis of probabilistic systems of customers and servers. . Applied Regression -- Prof. Juran. 2. Outline for Session 2. More Simple Regression. Bottom Part of the Output . Hypothesis Testing. Significance of the slope and intercept parameters . Interval Estimation. Applied Regression -- Prof. Juran. 2. Outline for Session 4. Summary Measures for the Full Model . Top Section of the Output. Interval Estimation . More Multiple Regression. Movers. Nonlinear Regression. Decision Models -- Prof. Juran. 2. Overview. More Sensitivity Analysis. Solver Sensitivity Report. More Malcolm. Multi-period Models. Distillery Example. Project Funding Example. Decision Models -- Prof. Juran. Decision Models -- Prof. Juran. 2. Overview. More Network Flow Models . Assignment Model. Traveling Salesman Model. Decision Models -- Prof. Juran. 3. Professor Scheduling Example. Three professors must be assigned to teach six sections of finance. . Operations Management -- Prof. Juran. 2. Outline. Optimization Extensions . Multiperiod Models. Operations Planning: Sailboats. Ne. twork Flow Models . Transportation Model: Beer Distribution. Assignment Model: Contract Bidding. Decision Models -- Prof. Juran. 2. Overview. Multiperiod Models. Data Processing at the IRS . Arbitrage with Bonds. Transportation Models. Gribbin Brewing . Decision Models -- Prof. Juran. 3. IRS Example. Decision Models -- Prof. Juran. 2. Example: Preventive Maintenance. At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. . The weekly revenue earned by a machine in state 1, 2, 3, or 4 is $100, $90, $50, or $10, respectively. . Decision Models -- Prof. Juran. 2. Overview. Evolutionary Solver. (Genetic Algorithm). Advertising Example. Product Design Example. Conjoint Analysis. Decision Models -- Prof. Juran. 3. Nonlinear Problems. 2. Overview. Basic definitions and metrics. Examples of some theoretical models. Operations -- Prof. Juran. 3. Basic Queueing Theory. A set of mathematical tools for the analysis of probabilistic systems of customers and servers. . 2. Overview. Finance Simulation Models. Securities Pricing. Black-Scholes. Electricity Option. Miscellaneous. Monte . Carlo vs. Latin Hypercube. Review of Binomial. Decision Models -- Prof. Juran. 2. Overview. Sensitivity Analysis. Goal Seek and Data Table. Marketing and Finance examples. Call Center LP. More Sensitivity Analysis. SolverTable. Decision Models -- Prof. Juran. 3. Sensitivity Analysis. 2. Overview. Monte Carlo Simulation. Basic concepts and history. Excel Tricks. RAND(), IF, Boolean. Crystal Ball. Probability Distributions . Normal, Gamma, Uniform, Triangular. Assumption and Forecast cells. Session 10b Decision Models -- Prof. Juran 2 Overview Marketing Simulation Models New Product Development Decision Uncertainty about competitor behavior Uncertainty about customer behavior Market Shares