Model of Adaptable Production Planning and Control

Borislav Gordic

doi:doi:10.11648/j.sjbm.20140205.16

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Model of Adaptable Production Planning and Control

Borislav Gordic

Published in Science Journal of Business and Management (Volume 2, Issue 5)

Received: 6 October 2014 Accepted: 28 October 2014 Published: 30 October 2014

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Abstract

In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.

Published in	Science Journal of Business and Management (Volume 2, Issue 5)
DOI	10.11648/j.sjbm.20140205.16
Page(s)	153-162
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Discrete Corrective Dynamizing Programming, Production Adaptability, Software for Simulation, Profit Rate, Flexible Planning and Production Control, Make-to-Stock and Make-to-Order Batch Production

References

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[2]	L.C.Hendry; B.G.Kingsman, "Production Planning System and Their Applicability to Make-to-order Companies", European Journal of Operational Research, Vol.40, pages 1-15, 1989.
[3]	J.Olhanger; M.Rudberg; J.Vikner, "Long-term Capacity Management: Linking the Perspectives for Manufacturing Strategy and Sales and Operations Planning", International Journal of Production Economics, Vol.69, pages 215-225, 2001.
[4]	P. G. Moscoso, J. C. Fransoo, D. Fisher, "An Empirical Study on Reducing Planning Instability in Hierarchical Planning System", Production Planning & Control Journal, 4/2010, pages 413-426
[5]	G. C. Kim, M. J. Schniederjans, S. S. Kim, "Simulation Study of Availability Management in a Make-to-order Manufacturing Environment for a Differentiated Order System", Production Planning & Control Journal, 1/2010, pages 47-49
[6]	H. Stefansson, P. Jensson, N. Shah, "Procedure for Reducing the Risk of Delayed Deliveries in Make-to-order Production", Production Planning & Control Journal, 4/2009, pages 332-342
[7]	J. E. Hernandez, J. Mula, F. J. Ferriols, "A Reference Model for Conceptual Modelling of Production Planning Processes", Production Planning & Control Journal, 8/2008, pages 725-734
[8]	M. M. Al Durgham, M. A. Barghash, "A Generalised Framework for Simulation-based Decision Support for Manufacturing", Production Planning & Control Journal, 5/2008, pages 518-534
[9]	T. Taskinen, "Improving Change Management Capabilities in Manufacturing: From Theory to Practice", Production Planning & Control Journal, 2/2003, pages 201-211
[10]	S. Mestry, P. Damodaran, Chin-Sheng Chen, "A Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-order Operations", European Journal of Operational Research, Vol.211/2011, pages 480-495
[11]	T. Volling, T. S. Spengler, "Modeling and Simulation of Order-driven Planning Policies in Build-to-order Automobile Production", International Journal of Production Economics, Vol.131/2011, pages 183-193
[12]	J. Mula, R. Poler; J. P. García-Sabater; F.C. Lario, "Models for Production Planning under Uncertainty: A Review", International Journal of Production Economics, Vol.103/2006, pages 271-285
[13]	J. N. D. Gupta, "An Excursion in Scheduling Theory: An Overwiew of Scheduling Research in the Twentieth Century",Production Planning & Control Journal, 2/2002, pages 105-116

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APA Style

Borislav Gordic. (2014). Model of Adaptable Production Planning and Control. Science Journal of Business and Management, 2(5), 153-162. https://doi.org/10.11648/j.sjbm.20140205.16

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ACS Style

Borislav Gordic. Model of Adaptable Production Planning and Control. Sci. J. Bus. Manag. 2014, 2(5), 153-162. doi: 10.11648/j.sjbm.20140205.16

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AMA Style

Borislav Gordic. Model of Adaptable Production Planning and Control. Sci J Bus Manag. 2014;2(5):153-162. doi: 10.11648/j.sjbm.20140205.16

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@article{10.11648/j.sjbm.20140205.16,
  author = {Borislav Gordic},
  title = {Model of Adaptable Production Planning and Control},
  journal = {Science Journal of Business and Management},
  volume = {2},
  number = {5},
  pages = {153-162},
  doi = {10.11648/j.sjbm.20140205.16},
  url = {https://doi.org/10.11648/j.sjbm.20140205.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20140205.16},
  abstract = {In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.},
 year = {2014}
}

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TY  - JOUR
T1  - Model of Adaptable Production Planning and Control
AU  - Borislav Gordic
Y1  - 2014/10/30
PY  - 2014
N1  - https://doi.org/10.11648/j.sjbm.20140205.16
DO  - 10.11648/j.sjbm.20140205.16
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 153
EP  - 162
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20140205.16
AB  - In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.
VL  - 2
IS  - 5
ER  -

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Author Information

Borislav Gordic

MIRAKO Co., Draskoviceva 57, Zagreb, University NORTH - University Center Varazdin, Department of Logistic, Varazdin, Croatia

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APA Style

Borislav Gordic. (2014). Model of Adaptable Production Planning and Control. Science Journal of Business and Management, 2(5), 153-162. https://doi.org/10.11648/j.sjbm.20140205.16

Copy | Download

ACS Style

Borislav Gordic. Model of Adaptable Production Planning and Control. Sci. J. Bus. Manag. 2014, 2(5), 153-162. doi: 10.11648/j.sjbm.20140205.16

Copy | Download

AMA Style

Borislav Gordic. Model of Adaptable Production Planning and Control. Sci J Bus Manag. 2014;2(5):153-162. doi: 10.11648/j.sjbm.20140205.16

Copy | Download

@article{10.11648/j.sjbm.20140205.16,
  author = {Borislav Gordic},
  title = {Model of Adaptable Production Planning and Control},
  journal = {Science Journal of Business and Management},
  volume = {2},
  number = {5},
  pages = {153-162},
  doi = {10.11648/j.sjbm.20140205.16},
  url = {https://doi.org/10.11648/j.sjbm.20140205.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20140205.16},
  abstract = {In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - Model of Adaptable Production Planning and Control
AU  - Borislav Gordic
Y1  - 2014/10/30
PY  - 2014
N1  - https://doi.org/10.11648/j.sjbm.20140205.16
DO  - 10.11648/j.sjbm.20140205.16
T2  - Science Journal of Business and Management
JF  - Science Journal of Business and Management
JO  - Science Journal of Business and Management
SP  - 153
EP  - 162
PB  - Science Publishing Group
SN  - 2331-0634
UR  - https://doi.org/10.11648/j.sjbm.20140205.16
AB  - In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.
VL  - 2
IS  - 5
ER  -

Copy | Download