Cost Implication of Inventory Management in Organised Systems

This paper investigates the role of cost implication in inventory management in order to improve Institutions’ Stores. The study takes a critical look at the costs involved and the use of economic order quantity as a tool that minimizes the total inventory costs, the time saved between the manual and the automated operational system using a Nigerian University Store, AYZ University (not the real name because of the ethical issue), as a case study. The study was being guided by the following objectives; to have stocks available when required, to maintain accurate stock records and facilities, and to recommend area improvement of the inventory system at AYZ University Stores. Findings revealed that the economic order quantity is seen as a control technique that is attributed to determine the inventory costs and how it can be minimized. The data collected from the store were analyzed and the results obtained shows that the existing system which is majorly manual based is not effective when it comes to time management and efficiency. A new automated system, computerized maintenance store system (CMMS) was proposed for development and implementation for the AYZ University Store for her end users of the store and her clients from within and outside the University system. This would be greatly improved in terms of both financial and time cost of inventory management

Modelling the power output from a steam power plant in Nigeria

Adequate supply of electricity at a competitive price is pivotal to sustainable development. More often than not, the generation of electricity which drives modern growth and development is currently powered by limited fossil fuels in many nations. Electricity generation and megawatt demand are also usually fluctuating due to several pertinent factors. In a bid to articulate the impact of inherent variations in process parameters on the performance of steam power plant at different loads, this paper presents an investigation into the efficacy of two validation strategies in predicting the net power output from the plant using GMDH Shell software. Using the combinatorial algorithm, the k-fold cross-validation strategy and the training/testing validation technique were applied to empirical data of a power plant in Nigeria. The performance of the models returned from the two validation strategies was evaluated using maximum negative error, maximum positive error, mean absolute percentage error (MAPE), root mean square percentage error (RMSPE), residual sum, the standard deviation of residuals, coefficient of determination (R2) and correlation. For the number of folds and the training/testing split percentage considered in this study, results show that both models obtained were quite competitive, with the k-fold model having a slight edge over the other model. It is expected that the outcome of the study will be handy in researches for providing knowledge base information on choosing and setting optimum operating conditions at various load demand