Optimum Production Planning Problem (A Case Study of Aspect Water Company Limited Intechiman Municipality)

Abstract

All production firms aim at maximizing profit after sales of their products but due to lack of technological and scientific approach in the production setting, many cannot achieve the stated objectives. This study showed the trend of production of sachet water at AWCL which gave the quantity of sachet water produced in each month for the year, 2011. The major objective of this study is to minimize the total cost of production at AWCL using Linear Programming model. The optimal solution to the production planning problem was generated by LP Solver and the demand and supply at each month were determined. The AWCL incurs cost of GH¢1.2355 when producing a bag of sachet water but with the use of linear Programming model, the cost of producing a bag of water was reduced to GH¢0.831519. The analysis also showed that, increasing the wages of regular workers and reducing that of overtime help the company to produce more with minimum cost of production. AWCL should employ more overtime labour when it is necessary to meet the urgent demands from the customers. Instead of employing more manual labour force, the company could have used machinery that can do assembling and packaging of the sachet water.  Computer – based planning (scheduling) help the manufacturers to attend to orders from their respective customers easily and to enhance on – time delivery of products. The computerized   planning performs better and faster than manual scheduling tools. The analysis showed that the production planning can facilitate the production processes in a way that help the company to streamline the activities that go on during acquisition of raw materials for production and the demands from the customers could be met when the wages of regular labour force are increased.

Keywords: Linear Programming Model, Optimum Production of Sachet water,  LP Transportation Model

DOI: 10.7176/JIEA/9-4-01

Publication date:June 30^th 2019