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Title: Product mix optimisation model for the coconut oil industry

Authors: Ivan Gunawan; Lusia Permata Sari Hartanti; Bernadeth Theresia Novita Klau; Nor Chofifah

Addresses: Department of Industrial Engineering, Faculty of Engineering, Universitas Katolik Widya Mandala Surabaya, Surabaya, Indonesia; Program of Engineer Profession, Faculty of Engineering, Universitas Katolik Widya Mandala Surabaya Surabaya, Indonesia ' Department of Industrial Engineering, Faculty of Engineering, Universitas Katolik Widya Mandala Surabaya, Surabaya, Indonesia; Program of Engineer Profession, Faculty of Engineering, Universitas Katolik Widya Mandala Surabaya Surabaya, Indonesia ' Department of Industrial Engineering, Faculty of Engineering, Universitas Katolik Widya Mandala Surabaya, Surabaya, Indonesia ' Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Surabaya, Surabaya, Indonesia

Abstract: Coconut can produce numerous derivatives and by-products. A coconut oil industry with five production processes: expeller-pressing, refinery, extraction, hydrogenation, and pelletising can produce up to 11 products. A product mix problem often arises in the determination of the quantity of each product to be produced. As such, product mix decisions can significantly affect profit generation. This research aims to develop a mathematical model based on linear programming (LP) to maximise profits. The optimisation model developed in this study estimates that the industry can increase profits by 43.9% by applying the best product mix decision. A sensitivity analysis shows that changes in capacity affect the model. Three production flow scenarios were tested in the LP model. Scenario 1 (adding refinery 2, using it like refinery 1 plus using refinery 2 to produce refined bleached deodorised hydrogenised coconut oil super) can increase the industry's profit by 28%.

Keywords: coconut oil industry; linear programming; maximising profit; product mix.

DOI: 10.1504/IJISE.2025.144101

International Journal of Industrial and Systems Engineering, 2025 Vol.49 No.1, pp.1 - 17

Received: 28 Jun 2023
Accepted: 02 Jul 2023

Published online: 27 Jan 2025 *

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