ISE 2220 Applied Statistics for Process Control & Improvement
Application of statistics as they apply to process control and improvement. Topics covered include Descriptive Statistics, Control Charts, Histograms, and Process Capability Indexes. Advanced statistical topics for process optimization and problem solving include Analysis of Variance (ANOVA), Design of Experiments, Measurement System Analysis, and Hypothesis Testing. Two classroom, two lab hours per week.
Division: Science, Mathematics and Engineering
Department: Industrial & Systems Engineering Technology
Repeatable Credit: No
Offered Online: No
- Apply the laws of reliability to test, determine, evaluate and predict the reliability of systems and components and devise ways for reliability improvement.
- Apply statistical techniques to determine process performance (CpK, Natural Process Limits).
- Apply hypothesis testing to verify differences in means, variance and standard deviations of data from designed experiments.
- Define the correct control chart to analyze and control a process to reduce variation.
- Apply the concepts of Measurement Systems Analysis and select appropriate techniques used to evaluate, control and reduce variation.
- Acquire, analyze and interpret data from a process to determine if that process data is normally distributed, is in statistical control and capable of meeting customer requirements.
- Apply problem-solving techniques to the development of an improvement plan for processes that are not in statistical control and/or not capable of meeting customer requirements.
Credit Hours: 3
Classroom Hours: 2
Lab Hours: 2