Statistical Process Control
What is Statistical Process Control?
- Assessing variation in process and product characteristics.
- Collecting data (measuring process and product characteristics).
- Analyzing data (using statistics and exploratory data analysis).
- Making decisions based on statistical output.
- Acting on data-based decisions (knowing how processes work).
What is Quality?
Quality is defined by customers. Customers seek products and services which are
fairly priced, reliable, and for the life of these products and services, capable
of satisfying the customers needs and expectations. To know whether its products
and services are of high quality, a company must listen to both 'the voices of its
processes' and 'the voices of its customers'.
To achieve high quality products and services, pro-active companies must...
- Pay attention to the input from their customers.
- Focus attention on defect prevention, not on defect detection.
- Practice process control, rather than product control.
- Continuously reduce the variation of manufacturing and service delivery processes.
SPC is necessitated by the following:
- ISO 9000
- QS 9000
- QS 9000 TE Supplement
- QS 9000 Semiconductor Supplement
- ISO 14001:2004 Environment Management System
- ISO Guide17025 Laboratory Quality System
- Quality Operating System (QOS)
- Total Quality Management (TQM)
- Continuous Improvement Strategy
Salient Features of SPC
- Provides a structure for continuous improvement.
- Creates a process with predictable performance levels & spots the impact of uncertainty
in data collection.
- Imparts directions to conduct Statistical Process Management.
- Aids decision making in process management.
- Extremely beneficial to manufacturing, non-manufacturing, and service industries.
The Role of Statistics
- Statistical Tools
- Statistical Process Control (SPC)
- Design of Experiments (DOE)
- Quality Function Deployment (QFD)
- Regression Analysis
Uses of Statistics
- Process Control
- Process Optimization
- Inventory Control
- Market Research and Analysis
- Customer Satisfaction Research
The participants are given an easy introduction to the Basic Statistics used in
Manufacturing Process Control.
Processes, on account of their very nature, cannot produce exactly the same output.
The variation in the process is estimated by observing the variation in the products
produced. This is normally captured using Standard Deviation or Range. The course
explains the practical significance of these measures of variation.
Due to the inherent variation present in the process, the individual product's characteristics
values do not have any significance in controlling the process. Their use is limited
to acceptance or otherwise to the respective product inspected. To estimate the
center of the process, the Average is used.
The course includes explanation on data collection, construction and operation of
the X-R chart, in controlling the process. Real Time data are used for explaining
Interpreting Control Charts
The power of the Control Charts in controlling a manufacturing process is grossly
under utilized in the industries, principally due to non-interpretation/interpretation
of the Control Charts. The exact interpretations and the actions that might be required
based on the indications in the Control Charts are detailed with real time pictorial
The Calculation, Interpretation and Actions required on the Capability indices are
explained. Special emphasis is given to the requirements of QS 9000 on the Process
Advanced Statistical Process
More often than not, the real operational benefits of SPC are not realized on the
shop-floor, primarily because of:
- Improper sampling
- Inadequate customization of the statistical technique for a given process.
While X-R charts serve a very useful and easy introduction to the concepts of SPC,
by themselves, they cannot yield the benefits expected.
Advanced SPC is designed to provide knowledge inputs for helping organizations implement
SPC by customizing the basic concepts to cater to the needs of a particular process.
The course on advanced
- The sampling methodology selection for effective implementation of SPC
- Other special Control Charts and their applications, viz.
- Modified Control Charts.
- Sloping Control Charts, including regression analysis
- WSUM Charts
- High tool wear Control Charts.
- X-MR Chart
- Median-Range Charts
The course also covers Control Test Methods for verifying the normality of the processes
as well as the Control Charts utilized for controlling attribute characteristics.
While the initial SPC course is an introductory course for all users of Control
Charts, the advanced SPC is a course strongly recommended for designers of SPC applications
for Process Control.