Docstoc

IIJM-2013-12-06-022.pdf

Document Sample
IIJM-2013-12-06-022.pdf Powered By Docstoc
					                                                     IPASJ International Journal of Management (IIJM)
                                                                                   Web Site: http://www.ipasj.org/IIJM/IIJM.htm
A Publisher for Research Motivation........                                                 Email: editoriijm@ipasj.org
Volume 1, Issue 6, December 2013                                                                          ISSN 2321-645X


 The Use of Theiles Rule in Modelling of Machines
     Performance in Manufacturing Industry
                                   1
                                       Adedoyin Salami .I., 2Okeniyi,O.M., and Alabi Risikat.A3
                                   1
                                       Dept. Business Administration Kwara State Polytechnic Ilorin,Nigeria.
                            2
                                Dept. Mathematics and Statistics Federal Polytechnic Offa,Kwara State,Nigeria.
                    3
                        Dept. Leisure and Tourism/Hospitality Management Kwara State Polytechnic Ilorin,Nigeria.




                                                                ABSTRACT
Theil statistic can reasonably be assumed to give results that also track the (unobserved) evolution of inequality within
industries. While the evolution of inequality in manufacturing earnings cannot be taken as per se indicating the larger
movements of inequality in household incomes, including those outside the manufacturing sector An attempt to control word
economy by industrialized nation of the world generated the idea of total quality management for every manufacturer products
.Raw materials have been the major production requirement from the time immemorial. It is quite obvious that without raw
materials there will be no production in any form. The modern plastic industry has developed to a great extent out of research
to substitutes to rubber and some metal products. In fact, the use of plastic products has largely replace any item in this world
presently. This research focuses on the use of non-parametric statistics in quality control on the usage of raw materials in
production of plastic.Therefore this research,use the theiles rule in modelling the machines performance in manufacturing
industry to determined linear equation on the products and defective items, theile’s method is use to obtain the regression
equation Y = -40.236 + 0.0182X and from the result obtain it was discovered that about 2% of the materials contribute to the
defectives product of the company ,we thereby concluded that company should use the quality materials to avoid defective item .
Keywords: conformance , measure , variability, Raw materials ,modelling.


1. INTRODUCTION
Quality is now beyond conformance to specification as a measure of evaluation and continuously striving to decrease
the variability about the target value to make more uniform. Initially, there was competition between the American and
Japan on the concept of quality originally. America dominated the world with their industrial and domestic product but
instead for America to make use of the intelligent people that were bestowed upon the nation in order to ensure high
degree of accuracy, uniformity and total quality for their products they did not because of the non-challant attitude of
the nation and manufactures towards the reaching of those people [3]. Year-to-year economy-wide measures of income
distribution, such as the Gini coefficient, are rarely available for long periods except in a few developed countries, and
as a result few analyses of year-to-year changes in inequality exist[4]. But wage and earnings data by industrial sectors
are readily available for many countries over long time frames. This paper proposes the application of the between-
group component of the Theil index to data on wages, earnings and employment by industrial classification, in order to
measure the evolution of wage or earnings inequality through time. We provide formal criteria under which such a
between-group Theil statistic can reasonably be assumed to give results that also track the (unobserved) evolution of
inequality within industries. While the evolution of inequality in manufacturing earnings cannot be taken as per se
indicating the larger movements of inequality in household incomes, including those outside the manufacturing sector,
we argue on theoretical grounds that the two will rarely move in opposite directions. We conclude with an empirical
application to the case of Brazil, an important developing country for which economy-wide Gini coefficients are scarce,
but for which a between-industries [1]. Theil statistic may be computed on a monthly basis as far back as 1976
This research takes quality into consideration. An attempt to control word economy by industrialized nation of the
world generated the idea of total quality management for every manufacturer products.[2].Raw materials have been the
major production requirement from the time immemorial. It is quite obvious that without raw materials there will be no
production in any form. This research focuses on the use of non-parametric statistics in quality control on the usage of
raw materials in production of plastic.

2. METHODOLOGY
 Simple Linear Regression (Theil’ Rule)
Y =  + xi + ei
Y =  + xi

Volume 1, Issue 6, December 2013                                                                                        Page 1
                                            IPASJ International Journal of Management (IIJM)
                                                                         Web Site: http://www.ipasj.org/IIJM/IIJM.htm
A Publisher for Research Motivation........                                       Email: editoriijm@ipasj.org
Volume 1, Issue 6, December 2013                                                                ISSN 2321-645X

If the assumption is hold on ordinary least square then
              S xy
  
              S xx
    = y - x
If the assumption is not hold, rank correlation is used. = median (ij). ij = Yj - Yi
                                                                                  Xj - Xi

Theil’s Procedure
    Estimate the slope of the line by the median of all slope joining pairs of point with different X values ie for
        point ( Xi , Yi ) and ( Xj , Yj ) obtain
     ij = Yj - Yi
           Xj - Xi
    Obtain the n (n-1) of ij
                         2
    obtain = median of bij
     = median ( yij) -  median of (xi)).
        Y =  +  Xi
         = y1 + bx1
        = y2 + bx2
        ;
       ; n  = y n + bx n
             = median (i)
3. DATA PRESENTATION
  The data used in this research work shows the average number of item produced and the number of scraps generated
during the process by 25 selected machines in march 2013 being shown in table 1 below.
 Table 1:Average Number Of Items Produced With The Average Number Of Scraps From 25 Selected Machines
                                            For 25 Days In March 2013.
                                   Days      Number Of Items         Number Of
                                             Produced (“000”)     Scraps Produced
                                  1        2880                   19
                                  2        3268                   12
                                  3        2980                   13
                                  4        2940                   15
                                  5        3204                   14
                                  6        2960                   20
                                  7        3040                   13
                                  8        3424                   14
                                  9        3600                   21
                                  10       3060                   16
                                  11       3012                   16
                                  12       2392                   16
                                  13       2692                   15
                                  14       3124                   18
                                  15       3132                   16
                                  16       2486                   14
                                  17       3144                   19
                                  18       2732                   13
                                  19       2512                   10
                                  20       3208                   15
                                  21       3188                   24
                                  22       2832                   13
                                  23       2492                   15

Volume 1, Issue 6, December 2013                                                                             Page 2
                                            IPASJ International Journal of Management (IIJM)
                                                                  Web Site: http://www.ipasj.org/IIJM/IIJM.htm
A Publisher for Research Motivation........                                Email: editoriijm@ipasj.org
Volume 1, Issue 6, December 2013                                                         ISSN 2321-645X

                               24        3144                   15
                               25        3312                   11
  Source: OK Plast Limited iloron Nigeria
4. ANALYSIS OF DATA
  Linear regression using theil’s rule
      The following data shows the average number of items produced and scraps generated from 25 selected machines
for 5 days in may where “X” represents the number of items produced in thousand (000) and “W” represents the
number of scraps produced while M1, M2, M3, M4….M25 represents the respective machines in production floor.
  Table 2.:Shows the average number of items produced and scraps generated from 25 selected machines for 5 days in
                                                        may
                                      X    2880 3268 2980 2940 3204
                                      Y    19     12     13      15     14

Rank of x = 2880, 2940, 2980, 3204, 3268
Median ( Xi) = 2980
Rank of y = 12, 13, 14, 15, 19
Median (Yi) = 14
                    n ( n  1) 5(5  1)
number of bij                          10
                         2        2
bij = Yj - Yi
      Xj - Xi
b1,2 b1,3 b1,4 b1,5 b2,3   b2,4 b2,5 b3,4     b3,5   b4,5
 b1,2 = 13 – 12
         2940 – 2880
          =0.0167
 b1,3 = 14 – 12
          2980 – 2880
         =0.0400
 b1,4 = 15 – 12
            3204 -2880
         =0.0278
 b1,5 = 19 – 12
          3268 –2880
         =0.0181
 b2,3 = 14 –13
           2980 - 2940
         = 0.025
 b2,4 = 15 – 13
         3204 – 2940
           = 0.0076
 b2,5 = 19 – 13
       3269 - 2940
          = 0.0183
 b3,4 = 19 – 14
          3204- 2980
          = 0.0045

b3,5 = 15 – 14
         3268- 2980
       = 0.0174
b4,5 = 19 – 15
          3268-3204
      = 0.0625
Rank of bij
Rbij = 0.0045,0.0076,0.0167,0.0174,0.0181
,0.0183,0.0256,0.0278,0.049,0.0625

Volume 1, Issue 6, December 2013                                                                          Page 3
                                           IPASJ International Journal of Management (IIJM)
                                                                        Web Site: http://www.ipasj.org/IIJM/IIJM.htm
A Publisher for Research Motivation........                                      Email: editoriijm@ipasj.org
Volume 1, Issue 6, December 2013                                                               ISSN 2321-645X

Median  = 0.0181+0.0183
                   2
 = 0.0182
 = median (Y) - ( median (X)
 = 14 – 0.0182 ( 2980 )
 = -40.236
Y = -40.236 + 0.0182X
5. CONCLUSION
 For the linear regression (theil’s rule), the fitted model equation is equal to Y = -40.236 + 0.0182xi .this implied that
about 2% of the good product contribute to the defectives
6. RECOMMENDATION
   With respect to the above conclusion on the test and analysis made, I hereby suggest to the management to maintain
the standard or improve on their current methods of production to in order to acquire better quality products .I also
suggest to the management to introduce the use of automated process monitoring devices to enhance the periodic
recordings of their production for easier detection of errors. Finally, I recommend for the management to employ the
use of statisticians for better planning to attain a greater height in quality production.

References
[1]. Brabazon. T., (2000): “A connectivist approach to index modelling in financing markets”, In Proceedings, Coil /
    EvoNet Summer School. University of Limerick.
[2]. Salvatore,I. and G. Damiana, C. (2005): “Functional principal component analysis of financial time series”,
[3].Mark O. And Afolabi, O. O. (2007): “Predicting Stock Prices Using a Hybrid Kohonen Self Organizing Map
     (SOM)”, Proceedings of the 40th Hawaii International Conference on System Sciences, IEEE.
[4]. Huixin, K., Jinghua H. and Hao, S. (2007): “Statistics Analysis in Investigation and Research”, Beijing: Beijing
      Broadcast University Press, 465-484..

AUTHOR

               Dr Adedoyin Salami I. was born on July 17th 1964 in Babaloma, Ifelodun Local Government Area of
              kwara state in Nigeria. He obtained his Higher School Certificate(H.S,C) from Kwara state polytechnic
              Ilorin in 1982, Bachelor of Science (B.Sc) Economics from University of Ilorin in 1986, Certificate in
              Computing from Kwara State Polytechnic, Ilorin in 1992 , Master in Business Administration from
University of Ilorin in 1997, Master in Management Science(M. Sc) from University of Ilorin in 2003, Post Graduate
Diploma in Education from National Teacher’s Institute in 2008 and Ph.D Business Administration Ph.D from
University of Ilorin in 2012 all in Nigeria. He is a lecturer in the Department of Business Administration since 1991
up to date. He is Acting Head of Department, Department of Business Administration in 2000-2003.He is a member of
several committee in the polytechnic and currently is Chief Lecturer and Director, Institute of Finance and
Management Studies, Kwara state polytechnic Ilorin from 2010 till date .He Attended many workshops and seminar.
He has many journal both national and international to his credit.

                  Okeniyi Okeyemi.M . was born on December 26th 1968 in Offa ,Offa Local Government Area of
                kwara state in Nigeria. He obtained his National Diploma in Statistic from Federal polytechnic Bida
                in 1988, Bachelor of Science (B.Sc) in Statistics from University of Ilorin in 1993, Master of Science
                in Statistics from University of Ilorin in 2001 and Post Graduate Diploma in Education from National
                Teacher’s Institute in 2007 all in           Nigeria.    He is a lecturer in the Department         of
Mathematics/Statistics from 2005 up to date. He is the Examination Officer 2006-2011,Part-Time coordinator 2011-
2012,ND Project Coordinator2012-2013 all in Department of Mathematics/Statistics Federal polytechnic Offa
.Presently he is Acting Head of Department, Department of Mathematics/Statistics Federal polytechnic Offa 2013 to
date

              Alabi Risikat .A.. was born on November 16th 1959 in Ifelodun Local Government Area of kwara state
             in Nigeria. She obtained her National Diploma and Higher Natiomal Diplomal in Hotel and Catering
             Management from kwara state polytechnic Ilorin in 1981 and 1984respectively. She obtained Post
             Graduate Diploma in Public Relations from kwara state polytechnic Ilorin in 1996, Master in Business
Administration (MBA) from Ondo State University Ado Ekiti in 2005, Bachelor of Science (B.Sc) Home and Hotel
Management from Olabisi Onabanjo University in 2007,Technical Teacher Certificate(TTC) from Federal College of


Volume 1, Issue 6, December 2013                                                                                  Page 4
                                          IPASJ International Journal of Management (IIJM)
                                                                   Web Site: http://www.ipasj.org/IIJM/IIJM.htm
A Publisher for Research Motivation........                                 Email: editoriijm@ipasj.org
Volume 1, Issue 6, December 2013                                                          ISSN 2321-645X

Education Akoka Lagos state in 2007and Master of Science (Msc) from Olabisi Onabanjo University in 2010 all in
Nigeria. She is a lecturer in the Department of Hospitality Management kwara state polytechnic Ilorin since 1995 up
to date. She is the Examination Officer 2008-2010 in the Department of Hospitality Management kwara state
polytechnic Ilorin, Assistant Chief Examination Officer Institute of Basic and Applied Science 2009/2010.She is a
member of several committee in the polytechnic and               and She is a member of           four Professional
bodies,(MNHCI,MWITTED,MHATMAN and MNIM).Currently She is the Head of Department Leisure & Tourism
Management, Kwara state polytechnic Ilorin from 2010 till date .She Attended many workshops and seminar. She has
many journal both national and international to her credit.




Volume 1, Issue 6, December 2013                                                                           Page 5

				
DOCUMENT INFO
Shared By:
Tags:
Stats:
views:0
posted:1/13/2014
language:English
pages:5
Description: IPASJ International Journal of Management (IIJM) Web Site: http://www.ipasj.org/IIJM/IIJM.htm A Publisher for Research Motivation........ Email: editoriijm@ipasj.org Volume 1, Issue 6, December 2013 ISSN 2321-645X