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Title: Critical path analysis type scheduling in a finite capacity environment
Author: Almeida, Dagoberto Alves De
ISNI:       0000 0001 3417 9502
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 1992
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In order to cope with more realistic production scenarios, scheduling theory has been increasingly considering assembly job shops. Such an effort has raised synchronization of operations and components as a major scheduling issue. Most effective priority rules designed for assembly shops have incorporated measures to improve coordination when scheduling assembly structures. However, by assuming a forward loading, the priority rules designed by these studies schedule all operations as soon as possible, which often leads to an increase of the workin- progress level. This study is based on the assumption that synchronization may be improved by sequencing rules that incorporate measures to cope with the complexity of product structures. Moreover, this study favours the idea that, in order to improve synchronization and, consequently, reduce waiting time, backward loading should be considered as well. By recognizing that assembly shop structures are intrinsically networks, this study investigates the feasibility of adopting the Critical Path Method as a sequencing rule for assembly shop. Furthermore, since a Critical Path type scheduling requires a precise determination of production capacity, this study also includes Finite Capacity as a requisite for developing feasible schedules. In order to test the above assumptions, a proven and effective sequencing rule is selected to act as a benchmark and a simulation model is developed. The simulation results from several experiments showed significant reduction on the waiting time performance measure due to the adoption of the proposed critical path type priority rule. Finally, a heuristic procedure is proposed as a guideline for designing scheduling systems which incorporate Critical Path based rules and Finite Capacity approach.
Supervisor: Galgut, P. E. ; Kay, John M. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Statistics