OVERVIEW OF STATISTICAL PROCESS CONTROL (SPC):-A QUALITY MANAGEMENT TOOL
M.Wasi Baig
1, Afroz Ahmad
2, Ali Ahmed Khan
31
Assistant Professor & In-Charge,
2,3Lecturer, Section of Applied Science, Integral University Campus Shahjahanpur (India)
ABSTRACT
Statistical process control (SPC) is a tool of quality control which basically uses statistical methods.it is used to monitor and control a particular process. Monitoring and controlling of a process ensure that it is operates at its full potential. The key tools used in SPC include control chart, design of experiment etc.
Implementation of SPC is a prominent global phenomenon especially in manufacturing environmnet.It is one of the standard methods for visualizing and controlling process on the basis of measurement of randomly selected samples.
In this paper we will study in detail about SPC its advantages, limitation, application and control charts.
In this paper we will study about Statistical process control and its application
Keywords: SPC, 5M’S
I. INTRODUCTION
Statistical process control (SPC) is a standard method from visualizing and controlling processes on the basis of measurement of randomly selectedsample. With the help of statistical methods controlling of closed loop is takingplaced. The main objective of SPC is to ensure that the planned process output is achieved and the related customer requirement is fulfilled.
Regarding process is measured and shown by control charts. Statistical indicator are determine Measurement and used to evaluated status of the process.
II. COMMON TERMS USED IN SPC ARE
1.Process:-A process is series of activities in which extraction of raw material or pre-machined parts or components converted into finished products.
The definition is as follow ―set of interrelated or interacting activities which transform input into outputs.A process can be described as a transformation of set of inputs into desired outputs.
2. Stable Process
3. Quality capable process 4. Stewart quality control chart 5. Capability and performance indices 6. Machine capability study
7 Process capability study 8. Capability indices
III. TYPES OF MEASURES
Measures where the metric is composed of a classification in one of two (or more) categories are called Attribute data.
Measures where the metric consists of a number which indicates a precise value is called Variable data.
IV. POPULATION VS. SAMPLE (CERTAINTY VS. UNCERTAINTY)
A sample is just a subset of all possible values
Since the sample does not contain all the possible values, there is some uncertainty about the population.Hence any statistics, such as mean and standard deviation, are just estimates of the true population parameters.
V. THE ROLE OF STATISTICS
Statistics is the art of collecting, classifying, presenting, interpreting and analyzing numerical data, as well as making conclusions about the system from which the data was obtained.
5.1 Descriptive Statistics
It characterizes and summarizes the most prominent features of a given set of data (means, medians, standard deviations, percentiles, graphs, tables and charts.
5.2 Inferential Statistics
Inferential Statistics is the branch of statistics that deals with drawing conclusions about a population based on information obtained from a sample drawn from that population.
5.3 Statistical Process Control (SPC)
Measures performance of a process
Uses mathematics (i.e., statistics)
Involves collecting, organizing, & interpreting data
Objective: Regulate product quality
Used to
Control the process as products are produced Inspect samples of finished products
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5.4 Functions of a Process Control System are
To signal the presence of assignable causes of variation
To give evidence if a process is operating in a state of statistical control
5.5 Quality Characteristics
5.5.1 Variables
1. Characteristics that you measure, e.g., weight, length 2. May be in whole or in fractional numbers
3. Continuous random variables 5.5.2 Attributes
1. Characteristics for which you focus on defects
2. Classify products as either ‗good‘ or ‗bad‘, or count # defects – e.g., radio works or not
VI. CATEGORICAL OR DISCRETE RANDOM VARIABLES
5M’S of SPC:- 1) Man 2) Machine 3) Material 4) Method
5) Milieu(Environment) Application of SPC:-
The application of SPc consist of three main activities 1) Understanding of process
2) Measuring the sources of variation
3) Eliminating assignation (Special) sources of variation
VII. ADVANTAGE OF SPC IMPLEMENTATION
It could improve process performance by reducing product variability Improves production efficiency by decreasing scrap and rework
Leads to higher quality product by reducing: Variability and defects
Improving their overall business competitiveness
Minimize rework
Minimize loss of sales
Maintain a desired degree of conformance to design
Eliminate any unnecessary quality checks
Reduce the percentage of defective parts purchased from vendors
Reduce returns from customers
VIII. CONCLUSION
SPC can be applied for manufacturing and non-manufacturing process.SPC is a useful tool when applied to non- repetitive, knowledge-intensive processes such as research and development or systems engineering has encountered skepticism and remains controversial
REFERENCES
[1]. Manus Rungtusanatham:‖Beyond improved quality: the motivational effects of statistical process control‖, Journal of Operations Management 19 (2001) 653–673.
[2]. Antony J., Balbontin A. and Taner T., (2000).―Key ingredients for the effective implementation of statistical
[3]. process control.‖ Work Study, 49(6): 242-247.
[4]. Attaran M., (2000). ―Why does reengineering fail. A practical guide for successful implementation.‖
Journal of
[5]. Management Development, 19(9): 794-801
[6]. [Benneyan, J.C., Chute, A.D., (1993): ―SPC, process improvement, and the Deming PDCA circle in freight
[7]. administration.‖ Production and Inventory Management Journal 34 (1), 35–40.
[8]. D. Ridleya, D. Duke (2007), ―Moving -window spectral model based statistical process control.‖
[9]. Deros B. M., Rahman M. N. Ab, Ismail A. R., Yee L. W. Zain R.M. (2010), ―Application of Statistical Process Control Technique for Evaluating Machine Capability:Case Study.‖ Jump up^ Fred P. Brooks (1986) No Silver Bullet — Essence and Accident in Software Engineering, Proceedings of the IFIP Tenth World Computing Conference 1986, pp. 1069–1076
[10]. Improvement, and the Deming PDCA circle in freight administration.‖ Production and Inventory Management
[11]. journal 34 (1), 35–40.
[12]. Jump up^ Deming, W. Edwards and Dowd S. John (translator Lecture to Japanese Management, Deming [13]. Electronic Network Web Site, 1950 (from a Japanese transcript of a lecture by Deming to "80% of
Japanese top management" given at the Hotel de Yama at Mr. Hakone in August 1950)
