This 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.
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.
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.
Design of Experiments is recommended.
SPC a basis for control Basic statistics Normal distribution Standard error of the mean Central limit theorem.
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
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
Management
Process engineer
Process control specialist
Supervisor
Operator