Process Control Design using SPC/PAT
Biotech, Pharmaceutical and Medical Device
This course is specifically designed to meet the analytical needs of those individuals working within FDA regulated industries. Course covers the basic concepts and methodologies associated with designing closed loop process controls using statistical process control for variables and attributes data. Variation assessment, subgroup formation, sample size selection, SPC control chart selection, out of control action plan generation are presented along with measures of process capability. The course requires 16 hours of instruction.

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Biotech, Pharmaceutical & Medical Device Courses

Systematic product development, Quality by Design courses, consulting services and analytical training for biotechnology, pharmaceutical and medical device industries. QbD provides guidance to facilitate design of products and processes that maximize the product’s efficacy and safety profile while enhancing product manufacturability and control.

Lean Six Sigma

Complete curriculum for new product development, manufacturing and business process performance optimization.

Tools & Templates

Development tools and templates created by Thomas A. Little Consulting have been used by numerous companies to aid and support various aspects of product development, problem solving, data analysis and risk assessment.

This course is required for all scientists, engineers and quality professionals who actively work on all aspects of discovery, product and process development where the goal is to characterize, optimize and improve product and process performance.
ESDA and DOE are recommended courses prior to taking PCD-SPC.
Course Objectives
  1. Understand the language and compute the basic statistics associated with SPC.
  2. Apply the ten process control requirements to achieve process control.
  3. Determine rational subgroup formation, sample size and frequency.
  4. Select appropriate control chart for process control requirements.
  5. Compute appropriate control limits.
  6. Develop appropriate SPC Charts and associated OCAPs.
  7. Determine process capability.
  8. Describe the roles and responsibilities for using SPC.
  9. Use JMP to analyze process variation patterns, generate SPC charts and determine process capability.
Detailed Course Outline
Section I: Introduction and Basic Statistics
SPC a basis for control
Basic statistics
Normal distribution
Standard error of the mean
Central limit theorem
Section II: Ten Requirements for Designing Effective Process Control
  1. Clear product specifications
  2. Effective metrology
  3. Process characterization
  4. Sampling plan
  5. Control chart selection (variables and attributes)
  6. Alarms, closing the loop and out-of-control action plans (OCAP)
  7. Process documentation
  8. Operator and engineering training
  9. Database
  10. Routine line audits
Section III: Process Capability
Determining process stability prior to computation of capability
Cp and Cpk
Sigma and z as measures of process capability
Tests for normality
Distribution fitting for nonnormal parameters
Section IV: Process Control Implementation Roles and Responsibilities
Process engineer
Process control specialist