AN OPTIMAL INVENTORY CONTROL OF RAW MATERIALS AND NETWORK ANALYSIS OF PRODUCTION PLANNING FOR AKA PAINT INDUSTRY NIGERIA LIMITED

Amarachukwu H. Okeahialam; Bassey Uwabunkonye; Uche O. Elem; Chukwunonso Madu; Pius M. Oyah; Temple C. Okeahialam

Authors

Amarachukwu H. Okeahialam Akanu Ibiam Federal Polytechnic Unwana, Afikpo, Ebonyi State Nigeria.
Bassey Uwabunkonye Akanu Ibiam Federal Polytechnic Unwana, Afikpo, Ebonyi State Nigeria.
Uche O. Elem Akanu Ibiam Federal Polytechnic Unwana, Afikpo, Ebonyi State Nigeria.
Chukwunonso Madu Akanu Ibiam Federal Polytechnic Unwana, Afikpo, Ebonyi State Nigeria.
Pius M. Oyah Akanu Ibiam Federal Polytechnic Unwana, Afikpo, Ebonyi State Nigeria.
Temple C. Okeahialam Federal University of Technology Minna, Niger State

Keywords:

Inventory, network planning, paint production, EOQ, PERT, CPM

Abstract

This study analyzed an optimal inventory control of raw materials and network analysis of production planning for Aka Paint Industry Nigeria Limited. Inventory and network analysis data from a secondary source, obtained from Aka Paint Industry Nigeria Limited was utilized by the study. Mathematical models such as Economic Order Quantity (EOQ) model were used in determine the optimal quantity of raw materials to be kept on inventory. Programme Evaluation and Review Techniques (PERT) and Critical Path Method (CPM) were used in estimating the completion time and expected duration respectively. The Optimum quantities for the various raw materials were calculated with their inventory length. Also the minimum and the expected duration of the production were obtained. An optimum quantity of 12,409 buckets of water, 9,475 bags of dolomite and 70,372kg of chemicals were obtained, and their inventory lengths were found to be one year for each item. Besides, a total completion time for 59 days and expected duration of 84 days of the production were obtained. In conclusion, it is recommended that the Company should adopts EOQ model in knowing the optimal quantity of raw materials to be ordered for and when best to make the order, and also use PERT and CPM in knowing the optimal scheduling activities.