Correlation Analysis of Manufacturing Systems

点击翻译按钮获取中文摘要

9812858Altiok This grant fluids a project to study tile performance effects of correlations (as proxies of temporal dependence) in manufacturing systems. The project will identify random components of manufacturing systems with appreciable correlations; will study their impact on performance statistics; and will develop modeling technologies to capture correlations whenever present in appreciable magnitudes. Potential random components include stochastic processes of customer demands, order load times, machine failures and down times The project will employ a novel modeling methodology, called TES/QTES, which emphasizes explicit modeling of correlations in such stochastic processes. TES processes constittute a versatile class of continuous-space, discrete-time stochastic processes designed to capture empirical distributions and autocorreclations, simultaneously, while QTES is essentially a discretized variant of TES, suitable for analytical modeling. The methodology will be applied to various industries including pharmaceutical, food processing and microelectronics, to obtain analytical and/or numerical solutions for performance metrics. It will farther be used ti explore the impact of correlations on various manufacturing performance measures and optimal operating policies. If successful, this research will produce a new correlation-oriented paradigm. correlation analysis, designed to impact both manufacturing research and practices. The research TES/QTES models promise to yield significantly more accurate analytical or simulation models of manufacturing systems and associated performance predictions in manufacturing systems. Improved predictions will faxcilitate more effective production planning, scheduling and inventory control. The practical aspects of the researched correlation analysis will be exercised in collaboration with industrial partners. From The educational viewpoint, correlation analysis will be incorporated into undergraduate and graduate courses on manufacturing-related theory and applications, including simulation, production control, inventory theory and performance analysis.