Portland Community College | Portland, Oregon

This course follows the process of collecting and analyzing data as it would be done in a semiconductor manufacturing line to characterize process performance. The data will be used to examine effects of sampling", utilize methods of representation, and options for process control as would be done using process control charts. Additional analysis will be done using capability indices and examining opportunities for improvement. Additionally students will study the history and philosophy of managing quality in manufacturing.

This course is primarily offered in a web-based format.  Students should have access to a computer with data analysis software (spreadsheets)", word processing, and internet access (all are available on campus.) Students must be able to manipulate data mathematically, and communicate meaning in written form.

INTENDED OUTCOME(S) FOR THE COURSE:
On completion of this course the student should be able to:

• Understand the history and requirements for effective quality systems in modern manufacturing
• Understand and utilize the tools of quality systems
• Collect, analyze and plot variable and attribute data
• Determine and use capability indices to describe a process
• Create and react to control charts
• Understand the sources of costs for implementing (or not implementing) quality systems
• Describe various quality systems used in modern manufacturing

Assessment of student performance in this course will be based on students’ ability to demonstrate knowledge and understanding of the required competencies", as determined through homework assignments and class participation. Assignments will include problem sets and projects involving analysis of data sets, statistics, case studies, and evaluation methods. Class work can involve group work and presentation, as well as written examinations.

REQUIRED STUDENT COMPETENCIES:

• Understand contexts for defining quality
• Define quality in terms of processes
  • Requirements
  • Improvement
• Describe the evolution of quality systems in manufacturing
  • Artisan – Apprentice
  • Inspection
  • Quality Control
  • Statistical Quality Control
  • Statistical Process Control
  • Total Quality Management
  • Best Practices
• Describe continuous improvement requirements in manufacturing
  • Commitment
  • Motivation
  • Change - in the corporate culture
  • Responsibility
  • Training
  • Communication
• Setup and follow problem solving methodology using:
  • Cycle of steps (planning, acting, studying, doing)
  • Tools (charts, checksheets, diagrams, etc.)
• Collect, analyze and chart variable data parameters:
  • Using charts for decision making and problem solving
  • Understanding and monitoring sources of variation (with piece, piece-to-piece, time-to-time)
  • Constructing control charts (center line, spec limits, control limits, sample size)
  • Recognizing patterns of variation
  • Revising charts
• Measure and describe process capability
  • Control limits and spec limits
  • Six-sigma
  • Capability indices
• Setup and use various chart types
  • Xbar-R
  • Xbar-S
  • Moving range
  • Moving average
  • All values
  • Run charts
  • Charts for short runs
• Collect, analyze and chart attribute data parameters
  • Setup and use Conform/Non-conform charts
  • Setup and use Counts charts
• Define and understand costs associated with quality
  • Prevention costs
  • Appraisal costs
  • Costs of failure
• Understand and describe quality systems
  • ISO 9000
  • Supplier Certification
  • ISO 14000