A synergistic methodology and adaptive model for material management in a dynamic environment



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Texas Tech University


This dissertation and the associated research compares the three main manufacturing philosophies of Manufacturing Resource Planning (MRP), Just In Time (JIT) and the Theory of Constraints (TOC) with a new manufacturing concept termed the Adaptive Model. The Adaptive Model uses the synergistic effect of combining selected aspects of the JIT and TOC philosophies into a new manufacturing philosophy. Specifically, the adaptive model identified a second constraint in addition to the primary constraint. This secondary constraint was both optimized and given an increased buffer size. It was envisioned before conducting the research that the adaptive model would be superior to the other models.

Three different manufacturing lines of five, nine and fifteen workstations were developed and modeled. Each of these models with different buffer sizes was simulated for approximately ten time periods of six months.

Performance factors were identified and employed for evaluating the four philosophies. These factors included Throughput levels. Work in Process (WIP) quantities, Time-in-the-system periods, the maximum amount of idle time at the main constraint and the utilization rate for the main constraint. Data for each of the performance factors were collected and analyzed. Additionally, hypothesis tests were developed and conducted. Differences existed between the various manufacturing philosophies, according to the tests.

Observations of the data suggest that the adaptive model produces sporadic superior results when compared with the other philosophies. However, the adaptive model exhibits higher costs of larger WIP levels, increased time-in-the-system lengths and increased costs of operating at an accelerated pace. The research conclusion is that the TOC model for a flow shop manufacturing environment is the best overall manufacturing philosophy.



Theory of constraints, Production management, Manufacturing processes, Just-in-time systems, Manufacturing resource planning