Page 207 - DMGT524_TOTAL_QUALITY_MANAGEMENT

Total Quality Management

Notes By interpreting data and graph trends, forecasting of critical quality attributes, sigma
process capability, and stability of process were studied. The overall study contributes to
an assessment of process at the sigma level with respect to out-of-specification attributes
produced. Finally, the study will point to an area where the application of quality
improvement and quality risk assessment principles for achievement of six sigma-capable
processes is possible.
Statistical process control is the most advantageous tool for determination of the quality
of any production process. This tool is new for the pharmaceutical tablet production
process. In the case of pharmaceutical tablet production processes, the quality control
parameters act as quality assessment parameters. Application of risk assessment provides
selection of critical quality attributes among quality control parameters. Sequential
application of normality distributions, control charts, and capability analyses provides a
valid statistical process control study on process. Interpretation of such a study provides
information about stability, process variability, changing of trends, and quantification of
process ability against defective production. Comparative evaluation of critical quality
attributes by Pareto charts provides the least capable and most variable process that is
liable for improvement. Statistical process control thus proves to be an important tool for
six sigma-capable process development and continuous quality improvement.
Source: http://journal.pda.org/content/66/2/98.abstract

14.2 Statistical Quality Control (SQC)

The application of statistical techniques to control quality often used interchangeably with the
term “statistical process control,” although statistical quality control includes acceptance sampling,
which statistical process control does not. It provides the methods and tools for the manufacturing
manager to improve quality, increase productivity, and enhance the competitive position of the
manufacturing line. SQC proposes potentially controversial methods of performance appraisals,
operation certification, line qualification, vendor certification and just-in-time manufacturing.

Figure 14.1: Statistical Quality Control

Process
Quality Functional Product Comp. Process Variance
Deployment – Tolerancing – Capability
Customer’s (Assembly) Component Tolerance
Tolerances
requirements to Tolerance
technical specifications.

Loss Function-
Quantifying Variance
Design of Experiments –
Problem Identification,
Variance reduction, etc.
Optimum
Process
Level
Measurement Error

Process
Process Control –
Component Mean
Control Charts, Process
Dispatch
Design of Control Setting
Product Charts

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