A neuro-fuzzy linguistic approach in optimizing the flow rate of a plastic extruder process

Abstract

The plastic extruder system is an important process in the solid waste recycling system. This paper optimizes the flow rate of this process with the application of a neuro-fuzzy model. The model identifies a specified desired output from a large number of input parameter. The methodology adopted is neuro-fuzzy. The concept of neuro-fuzzy is not new as a research methodology but new in its applied form to plastic recycling extruder process. The result obtained indicates the feasibility of applying the methodology in this instance. Thus, the study may be extended to other recycling processes apart from plastic base. The study is predicated on the need to attain more precision in the derivation of optimal values for the plastic extruder system in recycling plant. The research has strong economic implications since it has theory with an applied bias on a problem experienced by the industry. It can be used by managers in the plastic industry, or practitioner i.e. those supporting practice such as consultants or software developers, to mention a few. The work particularly has an economic justification. Intrinsically, the result obtained being an improvement over what was reported by earlier researchers is noteworthy. The paper is new in that it appears to be the first application of neuro-fuzzy in the system being researched.