A process is a combination of tools, materials, methods, and people to produce a measurable output. All process has some degree of variability, and process capability refers to such variability remaining within the specified statistical limits under normal conditions. For instance, a manufacturing line might produce automobile radiator caps with 1.99-inches to 2.01-inches in diameter under normal circumstances. If all the products fall within this diameter, the process has attained capability. If some units fall below 1.99-inches or more than 2.01-inches the unit becomes defective and the process inconsistent, not establishing process capability. This method, however, refers only to common cause variations, or variations in the normal course of events excluding variations owing to some special one-off or exceptional circumstances.
Any process has appropriate process controls to ensure output based on standard specifications. A control chart is a graphical illustration of data that plots specification limits or customer driven specifications and control limits or actual output values. This allows determining the extent of difference or variation of actual limits from specified limits, and thereby gauges the extent of process capability. If there is no significant difference between specification limits and control limits, the process remains in such statistical control and thereby, capable. When control charts denote variations, it also highlights the extent and frequency of variation, which helps in determining the stability of the process and pinpoints the sources of variation for remedial action.
Statistical Process Control
Statistical Process Control (SPC) is the process of using control charts and applying statistical techniques to monitor and control the process for compliance with specification limits. The application of SPC allows for an objective and quantitative basis of measurement, a marked improvement over the alternative method of making subjective and reactive assessments through inspection that detects and corrects problems after they occur.
Achieving process capability is not possible without understand the nature of variations in a process. Very often, the statistical tools applied remain complex, and the knowledge on how to apply such tools vague. This defeats its very purpose of using control charts and a statistical analysis.
Adopt a simple, direct, and straightforward statistical analysis to determine the extent to which the process deviates from the required parameters. Simple and straightforward tools lend clarity to the concept.
Implement measures to control the deviance from specifications, or ensure the range of control limits fall within specification limits. The way to approach the same is through a Corrective and Preventive Action (CAPA), a key element of a good manufacturing practice or (GMP), and a subsystem of the overall quality management system. This method entails a systematic investigation of the reasons for discrepancies or deviations from specifications using various analytical techniques such as a root cause analysis using the five-whys and fishbone diagrams and effecting remedial actions to resolve such root causes.
Statistical process control may unearth bottlenecks, wait times, and other sources of delays within the process that causes non-compliance with specification limits. Resolving such issues may require changes in design, and since the change involves work in process, the most viable approach is experimentation. At times experiments reveal bringing the process under statistical control requires fundamental changes such as redesigning and implementing a new process that eliminates the major sources of non-compliance.
The best approach to reduce deviances from the mean or ensuring control limits to stay within specification limits is improving quality. Select and apply from the wide range of quality initiatives. The most common quality initiatives include:
- Total Quality Management (TQM): Total Quality Management is a philosophy that aims to ingrain quality and thereby, eliminate defects at all levels by making employees aware of the specifications and inducing them to make a conscious effort to match such specifications every time. TQM also address issues such as streamlining supply chain management, modernizing equipment, and more aimed at the same purpose.
- Six Sigma: Six Sigma is standard deviation from the mean in a normal distribution, and Six Sigma aims to eliminate process defects to 3.4 per million opportunities. It uses a DMAIC (define, measure, analyze, improve and control) methodology to improve processes, which entails defining the problem, measuring the deviance from the desired state, analyzing the causes for such discrepancies through various methods such as brainstorming the root cause analysis, challenging assumptions, observations, implementing remedial measures that address the causes, and controlling the process to ensure that such changes stick.
- 5S Methodology: 5S is a workplace organization methodology based on five Japanese words “seiri,” “seiton,” “seiso,” “seiketsu” and “shitsuke," which mean "sort," "set in order," "shine," "standardize," and "sustain." The application of 5S automatically improves quality and eliminates process defects.
- Kaizen: Kaizen refers to the philosophy of continuous improvement, and entails a continuous cycle of defining specifications, innovating to meet such specifications, defining new specifications, and so on. The relentless quest for quality ensures specification limits and control limits usually match.
Establishing process capability allows the process to hold tolerance or meet customer requirements on a consistent basis.
- Lulea University of Technology. "Quality Improvement Strategies Based on Process Capability Studies."
- https://www.ltu.se/research/Forskningsamnen/Kvalitetsteknik/Projektarkiv/Kvalitetsforbattringsstrategier-baserade-pa-processduglighetsstudier-1.64496?l=en Retrieved June 19, 2011.
- University of Tennessee at Knoxville. "Practical Strategies for Process Improvement (PSPI)." https://bus.utk.edu/ise/documents/PSPIoutline.pdf. Retrieved June 19, 2011.
- Engineering Statistics Handbook. "What is Process Capability?" https://www.itl.nist.gov/div898/handbook/pmc/section1/pmc16.htm. Retrieved June 19, 2011.
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