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What is Logistic Membership Function

Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and Solutions
An appropriate function to represent the degree of truth
Published in Chapter:
Integration of Fuzzy Logic Techniques into DSS for Profitability Quantification in a Manufacturing Environment
Irraivan Elamvazuthi (Universiti Teknologi PETRONAS, Malaysia), Pandian Vasant (University of Technology Petronas, Malaysia), and Timothy Ganesan (Universiti Teknologi PETRONAS, Malaysia)
DOI: 10.4018/978-1-4666-0294-6.ch007
Abstract
Production control, planning, and scheduling are forms of decision making, which play a crucial role in manufacturing industries. In the current competitive environment, effective decision-making has become a necessity for survival in the marketplace. This chapter provides insight into the issues relating to integration of fuzzy logic techniques into decision support systems for profitability quantification in a manufacturing environment. The chapter is divided into five sections with a general introduction of the topic, followed by a thorough literature review on the existing techniques. Thereafter, fuzzy logic algorithms using logistic membership functions and resource variables for decision making aiming at quality improvement are discussed. A case study involving a textile firm is then described with the computational results and findings, and finally, future research directions are presented.
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