Study On Sales Revenue Forecast Of Coal Preparation Plant

Coal industry plays a dominant role in national economy, and as an indispensablestep to improve product quality in coal industry, coal dressing is not only an effectiveway to utilize resources comprehensively, to save energy and to protect theenvironment, but also an important part of clean coal technology of the nationalstrategy for sustainable development in the21st century.A coal preparation plant is usually affiliated with a upper coal company or groupwhich owns the leadership of the plant, and is assessed by the market. As a rule, theCoal Quality Department of the preparation plant analyzes the clean coal recoverybased on the production of each underground working face, which is used to establishindicators of clean coal recovery and to make plans and arrangements forunderground coal mining. However, the gap between the calculated clean coalrecovery and the actual recovery and the accumulated data of ground coal washing isbeyond accepted, which makes the calculated recovery lose its referential function.Thus the reference gained from the calculated clean coal recovery is unserviceable forthe company’s financial budget and revenue prediction. Therefore, from theperspective of a variety of coal processing products, this thesis does a research onsales revenue of coal preparation plant. Focused on this topic, the thesis has doneresearches as follows.First of all, from angles of the ratio of coal washing, automaticity, equipmentdiversification and technologies, a literature review on studies both home and abroadof coal dressing industry is conducted. Problems existed in sales management arerevealed through analyses of the current management, especially sales management ofthe coal preparation plant. And the most important finding is that the applied researchon sales revenue of coal dressing is still far from sufficient, while it is very vital to thecompany’s financial budget and revenue prediction. Therefore, the necessity andfeasibility of studies on coal dressing sales management are obvious, and furthermore,the research approaches are put forward.In the second place, factors having influence on sales revenue of the coalpreparation are studied. Based on the generalizations, the extent of impacts of andrelationships between these different factors are interpreted by qualitative andcorrelation analyses. And the relationship between raw coal ash and clean coalyielding, economic efficiency is specified, from which, it can be seen that raw coal ash has a significant effect on clean coal yielding and economic efficiency of the coalpreparation plant. On this basis, a prediction model of sales management is built, andthis model first uses Particle Swarm Optimization algorithm to make a fittingprediction of ash and yielding, then optimizes the structure of coal processingproducts according to the relationship between clean coal yielding and sales revenueand the principle of largest output value, and finally fulfills the prediction of sales.In addition, combined with the actual data of the LX coal preparation plant (take35monthly sets of data, from January,2011to November,2013, as an example),through statistics analyses of ashes in coal processing products and the products’prices, the thesis produces an estimate of the productivity of coal processing productsand their prices during the period from December,2013to February,2014, andforecasts the sales revenue of LX coal preparation plant.Lastly, in order to provide solid supports and useful reference for the LX coalcompany to predict its sales revenue, some policies and suggestions that can help raiserevenues are proposed from the perspective of its management and administrationmode, manufacturing technologies, marketing management model and so on.