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Stock cover is presented by a key performance indicator calculating the number of days of forecasted consumption which the current stock level can face. The identified problem in production companies, when calculating the “Stock Cover” indicator companies opt for one of three ways, among which there are large
deviations in planning frequency and la...
Contexts in source publication
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... a more precise analysis of the "Stock cover" it is possible to use the technique of analysis of product sales time series. By observing graphics in Fig. 1 (which represents the monthly amount/volume of sales of products A and B), behaviour patterns of the curve (different trends of growth and decline and seasonality) that can be useful in predicting future demand and stock levels can be ...
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... A -it has a declining trend in demand with moderate seasonality of demand, which is typical of an obsolete market (Fig. 1). When planning replenishment of stocks, it can be assumed that demand fore- casting is based on historical data, so that the indicator StChs has a major importance in a complex indi- cator BStC. In other words, target stocks should strive to value between 2.5 (BStC) and 1.4 (StChs) weeks of stock cover. For Product B -besides a slight ...
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... StChs has a major importance in a complex indi- cator BStC. In other words, target stocks should strive to value between 2.5 (BStC) and 1.4 (StChs) weeks of stock cover. For Product B -besides a slight increase in overall demand, expressed seasonality of demand that oc- curs during the market placement of promotional products can be identified ( Fig. 1). At the moment when a promotional product is launched in retail (eg. 20 [%] extra products or more favourable price), sales of the main product fall to a minimum and are close to zero. These characteristics suggest the possibility that this is a market which is in transition from a developing to a growing market. In this case, ...
Citations
... This value must be between the minimum and the maximum number of adequate performance indicators for considered performance. The control domain is defined by three constraints (3)(4)(5). ...
Research Question: This paper presents a simulation model aimed at improving total adequacy calculation for performance indicators of the first phase of production management. Motivation: Defining a set of adequate performance indicators that are specific and highly important for the observed planning phase has a significant impact on the effectiveness of the production process management. The result of the developed model is the value of selected performance indicators adequacy. Consequently, it can be concluded whether defined performance indicators are essential for the observed phase or other performance indicators should be selected. The monitoring of defined performance indicators should provide complete information about the observed phase and improvement of the planning phase management. Idea: The main idea of this paper is to develop a user-friendly simulation model, in accordance with the basic principles of spreadsheet engineering, for improving the selection of adequate performance indicators. This model is intended for use in Small and Medium Enterprises (SMEs) for the improvement of production management. Data: The data used in the paper are grounded on the scientific articles, reviews and empirical studies, related to the performance and performance indicators in production management. The set of most adequate performance indicators based on a relevant literature review and used in the model, represents performance indicators for the planning phase that are the most suitable for SMEs. Tools: The simulation model is developed in a spreadsheet environment. The use of spreadsheet applications enables simple data entry, processing, editing, analyzing and output reports compiling. Findings: Simulation results show the overall efficiency of the developed model in the determination of adequate performance indicators. They influence overall adequacy of performance indicators on the observed phase. Contribution: The main contribution of this paper lies in the model developed to maximize the adequacy of the performance indicators, suitable for use in the production management of SMEs.
Research Question: Optimal financing of the raw material inventories in the copper processing industry is perceived as a problem of choosing the financing sources and determining the purchase dynamics. Motivation: The company can realize the financing of raw material inventories from multiple sources under various conditions. The company efforts should be aimed at reducing the total costs that can occur in the process of purchase. Each company should simultaneously strive to satisfy the demand, but also to avoid keeping the excess of cash assets in inventories. Idea: The core idea of this paper is to evaluate the optimal financing of raw material inventories by the usage of the mathematical model that refers to the determination of financing sources, from which the required assets should be borrowed. Data: For the purpose of the case study example, the data used in the paper are approximations of information from the company and metal stock exchange. Tools: Excel was used to predict demand, while GLPK programme (GNU Linear Programming Kit) was used for the optimization of the defined model. Findings: The paper defines an optimization problem for determination of the financial sources, optimal periods, and the number of assets that will be used from these sources to secure continuity of the production process with minimum purchase costs. The paper also formulates a mathematical model of this problem and then illustrates it on the example of the real-life company for copper processing. Contribution: The results of this study show that such analysis gives the decision-makers a better insight into the possible scenarios while the final decision depends on their assessment, flexibility, attitude towards risk, need for security, etc.
