Browsing by Subject "Machine parts"
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Item Analysis of the parts/machines grouping problem in group technology manufacturing systems(Texas Tech University, 1981-05) Charles, Oliver EkepreNot availableItem Integrating hierarchically significant part numbers to bill of materials processing(Texas Tech University, 1985-12) Kini, Ranjan BailurThe Bill of Materials is the front-end information required in the material planning function of an organization. Processing of the Bills of Materials in an organization is usually computerized. Products can be exploded and requirements for the production schedule can be planned in an efficient and timely manner. Currently, bill processing is performed by maintaining two separate direct access files--Item Master File and Product Structure File. By linking these two files through pointers product explosion or implosion is accomplished. This method, as it incurs a large number of disk accesses, slows down Master Production Schedule explosion in material planning. Most major commercial software are using basically the same logic in their bill processing applications. Although part numbers are not related to bill processing other than to uniquely identify a part, a new part numbering scheme indicated an opportunity to use it in bill processing. This Hierarchically Significant Part Numbering (HSPN) scheme through its unique encoding/ decoding part numbering algorithm generates a numerator/denominator part number embedding the parent-child linkage information in it. This information about the structure is used in developing the HSPN approach to bill processing. This approach not only identifies a part uniquely but also helps out substantially in the data processing function of bill processing by exploding and imploding a product much faster. The HSPN approach is compared to the current link listing approach for its performance in explosion/implosion queries. The testing is conducted by simulating both the approaches and actually counting instruction operations for each query. For data, a set of complex product structures used in several other research is used. The results have indicated the HSPN approach to be far superior to the current link listing approach. When the tables of part numbers used in the HSPN approach are kept in entirety in the main memory the HSPN approach performed significantly better by a factor of 150 in all explosion and implosion queries, where as when only the partial segments of tables are brought into the main memory the HSPN performed moderately better than the current approach. Regardless, the HSPN approach has shown a new way of processing the bills and an approach to process the bill significantly faster than with the traditional approach.Item Reliability prediction of the series system with spares subject to Weibull failure(Texas Tech University, 1984-12) Pan, Jeh-nanThis research effort has developed a mathematical model for predicting the system reliability of a series system with spares subject to Weibull failures. Many modern equipment systems are designed in a series configuration with spares available when necessary. The Weibull distribution is one of the most widely applied and flexible failure distributions used to describe and model present day single component systems. Due to the theoretical intractability of the Weibull distribution in spares models, it is extremely difficult to solve the multiple integration involved in this type of model analytically. Therefore, a numerical integration method using Simpson's Rule was selected as a tool to address the problem of multiple integration of the Weibull distribution. Then, a recursive algorithm was developed for the reliability prediction of a series system with spares subject to a general failure model (including the Weibull distribution). The developed model has been validated for accuracy using a two component series system with spares. A sensitivity analysis has also been performed on the two parameters of the Weibull distribution, and the effect of adding spares or stages on the system reliability has been assessed. This research also demonstrates the application of the developed reliability prediction model with a realistic example pertaining to a tool reliability problem common to manufacturing industries.