Browsing by Subject "Production planning"
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Item A procedure to integrate aggregate production planning and master scheduling(Texas Tech University, 1980-05) Adams, MarkNot availableItem A profit-based lot-sized model for the N-job, M-machine job shop: incorporating quality, capacity, and cycle time(Texas Tech University, 1997-12) Kenyon, George N.Existing economic order quantity models base their calculations upon operations management principles established in the early 1900's. These principles focused primarily upon the control and reduction of the firm's variable costs. Total Quality Management has shifted this focus from costs and local optimization to quality and systems optimization. The marketplace also has changed. It has expanded from being primarily domestic into a globally competitive marketplace. In this new business environment, quality, market share, and profits must be primary elements in all of the firm's operating policies. Recent operations management theories, such as Goldratt's (1980) Theory of Constraints, not only address these concerns but redefine how operations management should think about the production system. This research proposal evaluates the classical economic order quantity model and proposes a new model that addresses the lot sizing decision for shop floor operations. A profit maximizing (rather than a cost minimizing) perspective is taken. In this research, a theorized model is derived that considers cycle time and quality issues in addition to the traditional cost issues of production, holding and setup. To validate this model, empirical data and a simulation model are developed to parameterize and collaborate the findings of the theorized model.Item Designing product architecture: a systematic method(2002) Van Wie, Michael James; Wood, Kristin L.; Campbell, Matthew I.Item Tolerance analysis for setup planning in computer-aided process planning(Texas Tech University, 1996-05) Mei, JiannanAutomated tolerance analysis is one of the most critical problems for computer aided process planning (CAPP) systems to be applied in the real manufacturing environment. The traditional way in CAPP uses only designed shape and nominal dimensions to generate an operation sequence arbitrarily, calculate operational dimensions and assign operational tolerances. Then, the dimensionai tolerance chain method is used to check the operational tolerances of the generated plan. The operational tolerances have to be made closer if the designed tolerance requirements are not met. Neither setup sequences nor datum elements are clearly specifíed. However, the economy of manufacture and the increase in the overall accuracy of many products can be greatly improved by the use of properly selected and specified datums for positioning purpose. How to generate feasible and economical operation sequences with specified datum elements and setups according to designed dimensional and geometric tolerances, how to evaluate altemative setup plans, and how to use computers to do it automatically have not been addressed. In this study, a graphical approach and a rulebase are developed and a neural network approach experiment is conducted for automated tolerance based analysis and selection of setups and datums for CAPP systems. The approaches and rules are based on a detailed analysis of the assembly tolerance analysis versus operational tolerance analysis, manually operated machining versus numerically controlled machining, and design datums versus machining datums. The knowledge and rules obtained in this study are used to train a back-propagation neural network to select datums and setups. The study is to improve the quality and economy of manufacturing by minimizing the effect of the cause of the variation of manufacturing process without controlling the cause itself performance measure of altemative plans is developed. The datums and setups are selected in such a way that the operation tolerances can be maximized to meet the design tolerance specifications. Because the manufacturing error sources have been considered and the effect of error sources is minimized, the selections will be more accurate and economical. The mlebase developed (A Manufacturing Datum And Setup Selection Rule Base For Rotational Parts-Technical Report) has been sent to the National Institute of Standard and Technology (NIST) depository of Process Planning Tested and is accessible by the process planning community all over the country.Item Two-product, single-machine, capacity-constrained ELSP with set-up time(Texas Tech University, 1997-12) Kosadat, VasaNot availableItem Uncapacitated and capacitated dynamic lot size models for an integrated manufacturer-buyer production system(Texas Tech University, 2001-08) Chang, PiyenNot available