| Under the major context of developing intelligent manufacturing,the intelligence,customization,small-batch and multi-species-oriented manufacturing mode will become one of the outstanding symbols of the new-generation industrial revolution.Advanced Planning and Scheduling(APS)is one of the key technologies critical to corporate intelligence,customization,small-batch and multi-species agile manufacturing mode.Tissue papermaking enterprises which produce small-batch,multi-species,multi-purpose products in the complicated market have extremely prominent demands for intelligence and customization agile manufacturing technologies and efficiency improvement technologies.The APS system including accurate and rapid sales(marketing)forecasting and efficient production scheduling are two related key technologies to realize enterprise agile manufacturing.Taking the manufacturing process in a tissue papermaking enterprise in Guangdong(hereinafter referred to as M Company)as the research subject,the thesis observes the APS system key technology applied by tissue papermaking enterprises during agile manufacturing link,including sales prediction and production scheduling.Here list the prime research contents:1.The research conducts an in-depth study on the manufacturing and sales features of tissue papermaking enterprises,and points out that tissue papermaking enterprises belong to mixed manufacturing industry which not only possesses process manufacturing properties but also possesses discrete manufacturing properties.For tissue papermaking enterprises with mixed manufacturing mode,both accuracy of sales prediction and drafting and execution of production scheduling are of vital importance.2.The research observes and establishes a sales prediction mathematical model proper for tissue papermaking enterprises.Through analyzing the historical sales data in tissue papermaking enterprises,multiple regression analysis methods have been utilized to compare the predictive modeling of sales volume in tissue papermaking enterprises and set up a highly precise sales prediction model based on time series data.Therefore,the research could predict sales data variation tendency in future period through summarizing and analyzing the changing law of historical data.3.The research observes and establishes a production scheduling mathematical model proper for tissue papermaking enterprises.Through analyzing the manufacturing features of tissue papermaking enterprises,it determines the production scheduling constraints and optimization objectives,constructs a production scheduling model on this basis,and designs a solution which hybrids intelligent optimization methods.4.Based on the study of production scheduling in tissue papermaking enterprises,the research further explores the production scheduling means based on improved energy efficiency and material efficiency and establishes energy consumption model and material consumption model proper for tissue papermaking enterprises,of which energy consumption model includes processing energy consumption,set-up energy consumption,auxiliary manufacturing energy consumption and stand-by energy consumption,and material consumption includes processing material consumption and set-up material consumption.Integrating efficiency optimization and energy efficiency production scheduling in the Drying Department,the thesis designs a hybrid intelligent optimization algorithm and optimizes multiple optimization objectives consisting of energy consumption,material consumption and makespan.5.The research profoundly analyzes problems existing in current management application APS,including inability to monitor workshop manufacturing process,inability to directly collect manufacturing process data,and absence of closed-loop management function.This thesis proposes combining APS system with MES(Manufacturing Execution System),namely the APS+MES mode and aims to improve the production scheduling accuracy of APS system with considerable manufacturing process data provided by MES.Besides,it suggests applying MES system to monitor manufacturing operation conditions and realize APS system closed-loop management.6.In combination with the features of tissue papermaking enterprises and the structural characteristics of MES,the thesis integrates above-mentioned tissue papermaking enterprise-targeted corporate sales prediction mathematical model,production scheduling mathematical model,energy consumption and material consumption model,energy efficiency optimization and production scheduling developed in this research with APS system and MES to design an APS system proper for tissue papermaking enterprises.Main innovative points and characteristics of the thesis are shown as follows:1)GBRT(Gradient Boost Regression Tree)modeling method has been adopted to establish a highly precise sales prediction model proper for tissue papermaking enterprises based on historical sales data.2)A production scheduling mathematical model full of tissue papermaking enterprises characteristics has been established targeted at the manufacturing features of tissue papermaking enterprises.In addition,the thesis also designs a hybrid intelligent optimization algorithm for solution.3)The thesis establishes energy consumption and material consumption model proper for tissue papermaking enterprises and later establishes corresponding energy efficiency and material efficiency production scheduling model in combination with production scheduling model.Additionally,energy efficiency optimization in the Drying Department and energy efficiency production scheduling have been combined to optimize factory energy consumption.The genetic algorithm designed in the thesis also has limitation in the relatively long operation time.Moreover,APS system designed in the thesis is simply functional design without any practical operation test.Therefore,follow-up research work needs to improve the efficiency of genetic algorithm and verify the system in manufacturing process so as to improve and perfect system performance. |
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