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SPC techniques using M/M/1 queueing model
Language
English
Obiettivo Specifico
3IT. Calcolo scientifico
Status
Published
JCR Journal
N/A or not JCR
Peer review journal
Yes
Title of the book
Issue/vol(year)
4/7(2019)
Publisher
Inderscience Enterprises Ltd
Pages (printed)
377-384
Issued date
2019
Abstract
: In a manufacturing process, no two products can be exact, which
might be due to many factors. These variations need to be monitored and
controlled through the use of statistical process control (SPC). When they are
small, and their effects are barely noticeable, we say the process is ‘in control’.
Otherwise, they lead the process to ‘out of control’. Items enter the system and
wait in a line for measurements; by following a queue discipline. Such a queue
is then characterised according to service time, number of quality inspectors
and waiting space. A good process control will also protect the product in the
sense that the lots produced at permissible levels of quality will have a good
chance to be in control. The objective of this paper is to introduce a control
chart using M/M/1 queueing discipline to study and maintain a process control
in a regular interval.
might be due to many factors. These variations need to be monitored and
controlled through the use of statistical process control (SPC). When they are
small, and their effects are barely noticeable, we say the process is ‘in control’.
Otherwise, they lead the process to ‘out of control’. Items enter the system and
wait in a line for measurements; by following a queue discipline. Such a queue
is then characterised according to service time, number of quality inspectors
and waiting space. A good process control will also protect the product in the
sense that the lots produced at permissible levels of quality will have a good
chance to be in control. The objective of this paper is to introduce a control
chart using M/M/1 queueing discipline to study and maintain a process control
in a regular interval.
References
Allen, A.O. (2014) Probability, Statistics, and Queueing Theory with Computer Science
Applications, 2nd ed., Elsevier, Academic Press, Orlando, FL, USA.
Costa, A.F.B. (1999) ‘Joint X and R charts with variable sample sizes and sampling intervals’,
Journal of Quality Technology, Vol. 31, No. 4, pp.387–397.
Elion, S. (1969) ‘A simple proof of L=λW’, Operations Research, Vol. 17, No. 5, pp.915–917
Gross, D., Shortle, J.F., Thompson, J.M. and Harris, C.M. (2008) Fundamentals of Queueing
Theory, 4th ed., John Wiley & Sons, New Delhi.
Montgomery, D.C. (2012) Introduction to Statistical Quality Control, 7th ed., Wiley, New York,
NY.
Applications, 2nd ed., Elsevier, Academic Press, Orlando, FL, USA.
Costa, A.F.B. (1999) ‘Joint X and R charts with variable sample sizes and sampling intervals’,
Journal of Quality Technology, Vol. 31, No. 4, pp.387–397.
Elion, S. (1969) ‘A simple proof of L=λW’, Operations Research, Vol. 17, No. 5, pp.915–917
Gross, D., Shortle, J.F., Thompson, J.M. and Harris, C.M. (2008) Fundamentals of Queueing
Theory, 4th ed., John Wiley & Sons, New Delhi.
Montgomery, D.C. (2012) Introduction to Statistical Quality Control, 7th ed., Wiley, New York,
NY.
Type
article
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Aunali et al. 2019.pdf
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