Good tool management and job operating strategies will
result in reduction in tool inventory and associated costs.
Very little empirical research has been conducted on a
Flexible Manufacturing System (FMS) as a whole in relation
to its performances with tool movement approach,
specifically in a dynamic job shop in a tool shared
environment. This study evaluated job loading rules and tool
selection policies in a tool shared environment with regards
to the job shop performance as a whole. This research also
examined the relationship between job loading rules and tool
selection policies when tool movement approach was employed.
A process oriented manufacturing system simulation
procedure was used as the theoretical framework for this
research, which was pursued in two phases. The first phase
was focused on the development of a generalized simulation
model and identification of the bottleneck conditions and
merits of different simple rules. The second phase, then,
was emphasized on development of bi-criterion rules and
determining the "best" strategies used for bottlenecks under
different simulation models and operating conditions.
This research concentrated on heuristic rules. The
nature of the study was observational, in which computer
simulation outputs were collected and analyzed by
multifactor analysis of variance, Fisher's Least Significant
Difference method, and non-parametric tests. Experimental
designs were used for comparing job loading rules and tool
selection policies, as well as shop operating conditions.
Significant differences were found among job loading
rules, tool duplication levels, and tool selection policies.
Furthermore, significant interaction effects were also
observed between some independent factors. Job loading rules
play the most important role in the system performance,
specially with more tool copies. Tool selection policies
affect the percent tardy jobs with single tool copy. It is
noticed that in the multiple-machine and multiple-tool
situations higher machine utilization can be obtained at
higher tool duplication levels. The analysis of results
showed that different processing time distributions also
effect system performance measures. / Graduation date: 1996
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/34643 |
| Date | 16 February 1996 |
| Creators | Xu, Zhongkai |
| Contributors | Randhawa, Sabah U. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
Page generated in 0.002 seconds