Statistical Process Control (SPC) and Statistical Quality Control (SQC) methodology is one of the most important analytical developments available to manufacturing in this century.

SPC has come to be known as an on-line tool providing close-up views of what's happening to a process at the moment.

SQC provides off-line tools to support analysis and decision making to help determine if a process is stable and predictable from shift to shift, day in and day out, and from supplier to supplier.

When SPC and SQC tools work together, users see the current and long-term picture about processing performance.

Before SPC, products were inspected after they were completed and defective products were discarded or reworked. The idea behind continuous improvement is to focus on designing, building, and controlling a process that makes the product correctly the first time (See CE, March '99, p.62).

Key to improving a process is removing as much variation as possible. When products and services are delivered with minimal variation, customer requirements and expectations are met.

Manufacturers applying SPC and SQC techniques rely on a variety of methods, charts, and graphs to measure, record, and analyze processes to reduce variations (See CE, March '99, p.87). In general, processes achieving the most benefit from SPC and SQC are products with:

• Highly repetitive manufacturing processes;
• High-volume production and low margins; or
• Narrow tolerances.

To make SPC and SQC work, key parameters indicating product variations are measured and recorded. For example, key parameters for a roll of cloth could include shrinkage, color, strength, and flaws per yard (meter).

SQC methods are used to analyze recorded data and establish which variations are a natural part of the process and which are unusual variations caused by external factors, such as variations in raw materials.

Control charts are a fundamental tool of SPC and SQC and provide visual representation of how a process varies over time or from unit to unit.

Control limits statistically separate natural variations from unusual variations. Points falling outside the control limits are considered out-of-control and indicate an unusual source of variation.

Performance improvements of personal computer hardware and software permit real-time data collection, number crunching, and graphing. Providing SPC information in real-time allows operators to make adjustments, or schedule maintenance on an as-needed basis.

SPC and SQC are an effective part of continuously improving a manufacturing process. When measurements are accurately collected and analyzed, improvements are identified and implemented, and controls established to ensure improvements are permanent, a process is well on its way to meeting quality requirements.