AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS AND LOGISTIC REGRESSION TO FACILITATE PRODUCTION SCHEDULING DECISION SUPPORT SYSTEM: AN AUTOMOTIVE INDUSTRY CASE

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MEHRJOO SAEED; BASHIRI MAHDI

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Journal Paper

Paper Information

Journal: JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL Year:2013 | Volume:9 | Issue:9 Page(s): 1-12

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Title

AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS AND LOGISTIC REGRESSION TO FACILITATE PRODUCTION SCHEDULING DECISION SUPPORT SYSTEM: AN AUTOMOTIVE INDUSTRY CASE

Author(s)

MEHRJOO SAEED | BASHIRI MAHDI | Issue Writer Certificate

Keywords

PRINCIPAL COMPONENT ANALYSIS

LOGISTIC REGRESSION

PRODUCTION PLANNING CONTROL

DECISION SUPPORT SYSTEM

Abstract

Production planning and control (PPC) systems have to deal with rising complexity and dynamics. The complexity of planning tasks is due to some existing multiple variables and dynamic factors derived from uncertainties surrounding the PPC. Although literatures on exact scheduling algorithms, simulation approaches, and heuristic methods are extensive in production planning, they seem to be inefficient because of daily fluctuations in real factories. DECISION SUPPORT SYSTEMs can provide productive tools for production planners to offer a feasible and prompt decision in effective and robust production planning. In this paper, we propose a robust decision support tool for detailed production planning based on statistical multivariate method including PRINCIPAL COMPONENT ANALYSIS and LOGISTIC REGRESSION.The proposed approach has been used in a real case in Iranian automotive industry. In the presence of existing multisource uncertainties, the results of applying the proposed method in the selected case show that the accuracy of daily production planning increases in comparison with the existing method.

Cites

DEVELOPMENT OF A CELL FORMATION HEURISTIC BY CONSIDERING REALISTIC DATA USING PRINCIPAL COMPONENT ANALYSIS AND TAGUCHI’S METHOD

References

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APA: Copy

MEHRJOO, SAEED, & BASHIRI, MAHDI. (2013). AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS AND LOGISTIC REGRESSION TO FACILITATE PRODUCTION SCHEDULING DECISION SUPPORT SYSTEM: AN AUTOMOTIVE INDUSTRY CASE. JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL, 9(9), 1-12. SID. https://sid.ir/paper/309910/en

Vancouver: Copy

MEHRJOO SAEED, BASHIRI MAHDI. AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS AND LOGISTIC REGRESSION TO FACILITATE PRODUCTION SCHEDULING DECISION SUPPORT SYSTEM: AN AUTOMOTIVE INDUSTRY CASE. JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL[Internet]. 2013;9(9):1-12. Available from: https://sid.ir/paper/309910/en

IEEE: Copy

SAEED MEHRJOO, and MAHDI BASHIRI, “AN APPLICATION OF PRINCIPAL COMPONENT ANALYSIS AND LOGISTIC REGRESSION TO FACILITATE PRODUCTION SCHEDULING DECISION SUPPORT SYSTEM: AN AUTOMOTIVE INDUSTRY CASE,” JOURNAL OF INDUSTRIAL ENGINEERING INTERNATIONAL, vol. 9, no. 9, pp. 1–12, 2013, [Online]. Available: https://sid.ir/paper/309910/en

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