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:: Search published articles ::
Showing 2 results for Inventory Management

Abolfazl Mirzazadeh, Mehri Nasrabadi,
Volume 3, Issue 1 (5-2016)
Abstract

This study develops a inventory model to determine ordering policy for deteriorating items with shortages under markovian inflationary conditions. Markov processes include process whose future behavior cannot be accurately predicted from its past behavior (except the current or present behavior) and which involves random chance or probability. Behavior of business or economy, flow of traffic, progress of an epidemic, all are examples of Markov processes. Since the far previous inflation rate don’t have a great impact on the current inflation rate, so, It is logical to consider changes of the inflation rate as a markov process. In addition, It is assumed that the cost of the items changes as a Continuous – Time - Markov Process too. The inventory model is described by differential equations over the time horizon along with the present value method. The objective is minimization of the expected present value of costs over the time horizon. The numerical example and a sensitivity analysis are provided to analyze the effect of changes in the values of the different parameters on the optimal solution.
Nsikan John, John Etim, Tommy Ime,
Volume 3, Issue 4 (2-2015)
Abstract

This study examines inventory management practices of flour milling manufacturing firms and their effects on operational performance. Five flour milling manufacturing firms in Lagos were used for this study. Structured questionnaire was the major instrument for the collection of relevant primary data while descriptive statistics such as mean and standard deviation was deployed to analyzing the data gathered. The results obtained showed that exception of the large manufacturing companies, most of the medium-sized flour milling firms adopts different inventory management strategies from the scientific and best practice models. Their inventory management strategies and policies were rather based on factors such as changing level of customer demand, prevailing industry practices, forecast estimates and guesses, and available production capacity. Findings also revealed significant differences between the effective management of inventory and optimal operating performance. For instance, while firms that adopt best practice inventory management approaches reported efficiency in capacity utilization, increased service level, and reduced lead time, others with different strategies had minimal utilization of material resources. There is need for flour manufacturing firms to implement scientific inventory management models to adequately handle material shortages, product stock outs situations, component pile up and their associated penalties.

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