An Intelligent Process Model for Manufacturing System Optimization

Abstract:

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The paper aims to develop an intelligent modeling system using Microsoft Excel spreadsheet interface through mathematical language, mathematical reasoning and algorithms flow chart technique for manufacturing system optimization without human involvement. The paper begins to search for a mathematical theorem which is arithmetic series to represent a dynamic manufacturing system in a production floor using production time variable through numerical analysis and is validated using software simulation. The mathematical theorem is modeled with Industrial Engineering (IE) variables into spreadsheet to perform intelligent decision making. The model sets inventory target variable to be achieved with automated computation through the data input from users. Manual analysis from human can be transposed to mathematical language in order automate the system intelligently. The building of intelligent modeling system into spreadsheet using mathematical language sets a new platform for researchers to promote the next generation of modeling technique in the manufacturing field.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

6674-6678

DOI:

10.4028/www.scientific.net/AMR.383-390.6674

Citation:

H. K. Hoe et al., "An Intelligent Process Model for Manufacturing System Optimization", Advanced Materials Research, Vols. 383-390, pp. 6674-6678, 2012

Online since:

November 2011

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Price:

$35.00

[1] Bos, E.: Comprehensive User Behaviour Using Psycholinguistics. Behaviour and Information Technology, Vol. 14, Iss. 6, pp.342-356, (1995).

[2] Donald Clarke: A Timeline of Management and Leadership, 2004. Available from: http: /www. nwlink. com/~donclark/history_management/management. html. [Access 12 September 2010].

[3] Brad D. Hume: Industrial Engineering [online]. College Park, University of Dayton, 2007. Available from: http: /campus. udayton. edu/~hume/IndustEng/industeng. htm[Accessed 5September 2010].

[4] Sormaz, D: Intelligent Manufacturing Based on Generation of Alternative Process Plans. Proceeding of 9th International Conference of Flexible Automation and Intelligent Manufacturing, Tilburg, (1999).

[5] Harvey J. Greenberg. A Prospective on Mathematics and Artificial Intelligence: Problem Solving = Modelling + Theorem Proving. Annals of Mathematics and Artificial Intelligence, Volume 28, Number 1-4, Pages 17-20, (2000).

DOI: 10.1023/a:1018935718357

[6] Ho Kok Hoe, KK. Harikrishnan and K. Muthusamy; A Numerical Analysis in the Lean Manufacturing. Presented at 14th Asia Pasific Management, 18-20 November 2009, Airlangga University, Surabaya, Indonesia.

[7] National Coalition for Advanced Manufacturing (NACFAM)A: Exploiting E-Manufacturing: Interoperability of Software Systems Used by U.S. Manufacturers., 2001, Washington D.C. Available from: http: /www. mel. nist. gov/div826/msid/sima/FinalReportSummary. PDF. [Accessed 12 September 2010].

[8] Ramussen: Information Processing and Human-Machine Interaction: An Approach to Cognitive Engineering. New York, North Holland, (1986).

[9] Terveen L., Selbridge, P., and Long, D. Living Design Memory: Framework, Implementation, Lesson Learned. Human Computer Interaction, Vol. 10, Iss. 1, pp.1-37, (1995).

DOI: 10.1207/s15327051hci1001_1

[10] Wikipedia, 2010. Scientific Management [online]. The Free Encyclopedia Wikipedia. Available from: http: /en. wikipedia. org/wiki/Scientificmanagement#cite_note-Taylor1911-1 [Accessed 10 September 2010].

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