High Production Capacity Plan Research Based On Ant Colony Algorithm

As the hard core of manufacturing production management, production schedule is alwaysthe subject of close attention. How to optimize production schedule rational is the criticalelement of improving production efficiency and increasing economic benefit.Current situation is relying on experience to make production schedule. One side, familiarwith the products and all the machines performances is required to be the staffs that makeproduction schedule, but the other side, huge products' information, insufficient basic data formachine performance and variance individual experiences. The result is time-consuming andschedule unreasonable, end in poor efficiency, low productivity and long production period.The target of this paper is using ant colony algorithm and interrelated theories to optimizeproduction schedule, investigated subject is project order big batch size production andproduction process sequencing in the workshop. This study is not only high theoreticalsignificance, but also important practical value.The results of this research are as follows:1. Production time measurement and analysis is carried out base on60referenced itemsfrom2furniture series, create process working time database for the2series. Arrive at aconclusion that the working time regulation factor for manual work is between0.3-1,machining is0.6-1, process cycle for1item is1.7in F company.2. Optimized the machine selection using ant colony algorithm, suggested the productionmodel of "turn scattered into the whole, section cooperate with team". Machine utilization is21%higher when using the optimized production schedule than the original one.3. On the basis of the research results,"intelligent schedule system" is developed, andtheoretical validation responds well.4.Run the test and verify the functionality of the "intelligent schedule system" bycomputerized emulation,81%lower incidence rate in bottle-neck process,26.5%higher output,0.4days reduced for machining production period and86%higher working performance formaking working schedule, as the final outcome from this research.