Data mining methods for macro level process planning
Günther Schuh, Jan-Philipp Prote, Philipp Hünnekes
Abstract
Due to increasing availability of feedback data from the shop floor and prevalence of feature technology for CAD data, relevant information for process planning is available in data of completed production orders. Data mining can be used to extract the relevant information, however the identification of suitable methods for the specific domain of macro level process planning is challenging. In this paper, we analyze data types and distributions of process planning problems as well as the suitability of data mining methods. The methods are matched to planning problems and successfully applied to case study data to obtain process planning information.
Topics & Concepts
Process (computing)MacroComputer scienceData miningDomain (mathematical analysis)Identification (biology)Feature (linguistics)Production planningProduction (economics)MathematicsBotanyLinguisticsOperating systemBiologyPhilosophyProgramming languageMacroeconomicsMathematical analysisEconomicsManufacturing Process and OptimizationFlexible and Reconfigurable Manufacturing SystemsAssembly Line Balancing Optimization