QSC 249 - Statistical Process Control

Description
This course covers simple statistical procedures for the control of manufacturing processes, including the study of data analysis and process improvement methodologies, product flow charts, cause-and-effect diagrams, Pareto charts, pie charts, histograms, and a variety of variable and attribute charts. Students learn to interpret SPC data, conduct process capability studies, and Repeatability and Reproducibility studies.

Credit Hours: 3
Contact Hours: 3
Prerequisites/Other Requirements: None
English Prerequisite(s): None
Math Prerequisite(s): None
Course Corequisite(s): None
Academic Program Prerequisite: None
Consent to Enroll in Course: No Department Consent Required
Dual Enrollment Allowed?: Yes
Course Fees: $15.00
Number of Times Course can be taken for credit:
Programs Where This Course is a Requirement:
Quality Science, Certificate

General Education Requirement:
None
General Education Learner Outcomes (GELO):
NA
Course Learning Outcomes:

Develop and analyze variable and attribute control charts.
Understand capability analysis and process improvement techniques.
Properly conduct and analyze data from manufacturing processes.
Discuss gage capability and lot traceability procedures.
Understand the importance of simple problem solving and a variety of techniques.
Discuss quality management principles.
Utilize a simple scientific calculator to find statistical information.
Discuss the importance of continuous improvement, auditing systems; ISO/QS/TS/GMP/MIL-STD and six sigma methodologies.
Discuss quality cost and reliability principles.
Understand capability analysis, calculate and interpret results and apply the appropriate process improvement techniques.
Use visual representations such as graphs, charts, or graphics to enhance the meaning of the message that is being communicated.
Identify quality sources for data and information pertinent to a problem or issue being examined.

Course Outline:
I. Introduction Quality Basics

II. Quality Advocates

III. Quality Improvement Techniques: Problem Solving

IV. Statistics and Probability

V. Variable and Attribute Control charts

VI. Process Capability

VII. Gage R & R studies

VIII. Reliability and Liability

IX. Quality Cost

X. Quality System: ISO9000, Malcolm Baldridge Award, and Six Sigma

XI. Benchmarking and Auditing

XII. Advanced Topics in Quality: DOE/FMEA/QFD

Approved for Online and Hybrid Delivery?:
Yes
Instructional Strategies:
Lecture: 60-80%

Discussion: 20-30%

Group work: 0-10%
Mandatory Course Components:
Use of Scientific calculators and Minitab software.
Name of Industry Recognize Credentials: None

Course-Specific Placement Test:
Course Aligned with ARW/IRW Pairing: N/A

Mandatory Department Assessment Measures:
None

Course Type:
Program Requirement- Offering designed to meet the learning needs of students in a specific GRCC program.
Course Format:
Lecture - 1:1
Total Lecture Hours Per Week: 3
People Soft Course ID Number: 101554
Course CIP Code: 48.9999
Maximum Course Enrollment:
General Room Request: None

School:
Department: Manufacturing
Discipline: MN
Faculty Credential Requirements:
Master’s Degree (GRCC general requirement), Professionally qualified through work experience in field (Perkins Act or Other) (list below)
Faculty Credential Requirement Details:
Minimum of 4000 hours required. Extensive knowledge of Manufacturing/Quality/Engineering/Statistics.

Major Course Revisions: Prefix
Last Revision Date Effective: 20240301T12:09:26
Course Review & Revision Year: 2028-2029