Design and Analysis of Industrial and Production Experiments

At the end of this course, the students should be able to: 1. explain how to design experiments, carry them out, and analyse the data yielded; 2. state process involved in designing an experiment including factorial and fractional factorial designs; 3. State how a factorial design allows cost reduction, increases efficiency of experimentation and reveals the essential nature of a process; 4. evaluate the logic of hypothesis testing, including analysis of variance and the detailed analysis of experimental data; 5. formulate understanding of the subject using real examples, including experimentation in industrial and production engineering; 6. introduce Taguchi methods and compare and contrast them with more traditional techniques; and 7. discuss the roles of response surface methodology and its basic concepts. 8. describe how the analysis of experimental design data is carried out using the most common software packages.

Examples of experimental design problems in production planning and manufacturing. Basic principles of experimentation. Randomization. Replication and local control. Blocks and Latin square designs. Two level factorial design. Analysis of experimental data. Special problems of current interest. Applications in industrial and Production engineering. Confounding in a 2k experiment. Introduction to fractional replication. Introduction to response surface methodology. Introduction of Taguchi Method and its comparison other techniques