Dec 03, 2020  
Official Course Syllabi 2020-2021 
    
Official Course Syllabi 2020-2021
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ATQT 1030 - Applied Statistical Process Control

Credit Hours: 2.00


Prerequisites: None

This course covers basic statistical methods as applied to manufacturing quality assurance, including frequency distributions (histograms, etc.), attribute and variable control charts (X-R, P, NP, etc.), capability analysis (Cp, Cpk), measurement system analysis, pareto analysis, brainstorming, cause and effect diagraming, and the 8-D problem solving approach.

Contact Hours: 2
Billable Contact Hours: 2
OUTCOMES AND OBJECTIVES
Outcome 1: Upon completion of this course, the student will be able to understand variable versus attribute data, the concept of and types of variation, applying Statistical Process Control tools to identify chance versus assignable causes, and the normal curve and deviations from the normal curve.

Objectives:

  1. List and describe the statistical tools used for SPC and list and describe the types of variation found in manufacturing.
  2. List and describe the statistical tools used for determining chance versus assignable causes of variation found in manufacturing. Accuracy using the material presented on chance versus assignable causes..
  3. Identify and describe the statistical tools used for evaluating manufacturing processes with attribute and variable data.
  4. Identify and analyze the statistical elements of a normal curve to determine capable manufacturing processes.

Outcome 2: Upon completion of this course, the student will be able to construct and analyze variable and attribute control charts.

Objectives:

  1. Construct and explain average and range charts and individuals and moving range charts.
  2. Identify out-of-control situations and assignable causes for applied manufacturing processes.
  3. Construct percent defective number defective, and defects per unit control charts.
  4. Identify out-of-control situations and assignable causes for applied manufacturing processes.

Outcome 3: Upon completion of this course, the student will be able to describe manufacturing process and machine capability, capability index and ratio, cause and effect diagrams, Gage R & R analysis, Pareto charts, root cause analysis, and other quality problem‐solving tools.

Objectives:

  1. Apply capability index and ratio, apply the SPC tools to calculate and analyze machine capability, capability index and ratio for manufacturing processes.
  2. Construct and evaluate cause and effect diagrams.
  3. Explain the concepts of Gage Reproducibility and Gage Repeatability, and describe what constitutes an acceptable gaging process.
  4. Calculate and construct Pareto diagrams for a manufacturing process.
  5. Describe and apply the tools and steps used in manufacturing problem solving.

COMMON DEGREE OUTCOMES
(Bulleted outcomes apply to the course)

  • 1. The graduate can integrate the knowledge and technological skills necessary to be a successful learner.
  • 2. The graduate can demonstrate how to think competently.
  • 3. The graduate can demonstrate how to employ mathematical knowledge.
  • 4. The graduate can demonstrate how to communicate competently.
  • 5. The graduate is sensitive to issues relating to a diverse, global society.

COURSE CONTENT OUTLINE
  1. Orientation & Introduction to the Course; Review of First Day Handout and Course Policies;
    1. Introduction to SPC; History of SPC; Causes and types of variation; Glossary; Math Practice Handout
  2. Tools of Applied SPC (Overview), Chance vs. Assignable Causes, Attribute vs. Variable Data; the Normal Curve;
    1. Use of a statistical calculator
  3. Frequency Histograms: Variation, Coding of Data, Histogram Construction
  4. Frequency Histograms Continued; Manufacturing Situations and Practice Problems
  5. Variable Control Charts (X‐Bar and R)
  6. Variable Control Charts Continued, Identifying assignable causes
  7. Variable Control Charts continued; Median and Range Charts, Individual and Range Charts
  8. Attribute Control Charts: P (Percent Defective) Charts.
  9. Attribute Control Charts: NP (number Defective) and C (number of defects)
  10. Machine and Process Capability
  11. Process Capability Index, Calculation of Cp and Cpk, Overview of Gage R & R Analysis
  12. Brainstorming, Cause and Effect Diagrams
  13. Pareto Analysis, Process Flow Charts, Scatter Diagrams
  14. Elements of a Total Quality Management System
  15. Review for Final Exam
  16. Final Exam: Cumulative, covers all eight textbook Modules

Primary Faculty
Walters, Gary
Secondary Faculty

Associate Dean
Pawlowski, Timothy
Dean
Hutchison, Donald



Official Course Syllabus - Macomb Community College, 14500 E 12 Mile Road, Warren, MI 48088



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