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Minimum Inventory Variability Dispatching Policies (Mivp)

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Conference

2000 Annual Conference

Location

St. Louis, Missouri

Publication Date

June 18, 2000

Start Date

June 18, 2000

End Date

June 21, 2000

ISSN

2153-5965

Page Count

15

Page Numbers

5.453.1 - 5.453.15

Permanent URL

https://peer.asee.org/8567

Download Count

34

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Paper Authors

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Jose'-Job Flores-Godoy

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Frank C. Hoppensteadt

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Donald W. Collins

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Kostas Tsakalis

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Session 2563

Minimum Inventory Variability Dispatching Policies - MIVP

Donald Collins, Ph.D., Manufacturing Engineering Technology, José-Job Flores-Godoy, M.S., Electrical Engineering Frank Hoppensteadt, Ph.D., Math and Electrical Engineering, Kostas Tsakalis, Ph.D., Electrical Engineering Arizona State University

Abstract

This paper illustrates the use of discrete event stochastic simulation modeling to compare two scheduling (dispatching) policies for machines in a factory when a machine becomes available for processing. The two policies are first-in-first-out (FIFO) and Minimum Inventory Variability Policies (MIVP), both control the items in the queue (buffers) in front of the machine or resource 8,9,10,11. The simulation model is run with FIFO for each queue for 100 days to establish a baseline set of data. This baseline cycle time and work-in-progress (WIP) data are collected for comparison to MIVP. The only change between the model runs is that the queues in the model are switched to run the rule set of MIVP.

With discrete event simulation modeling, the user can play “what if” scenarios without expended a lot of capital 4,5,8,9,10,11,19,20. The results from simulation give the user an additional input in making decisions. Examples of such a simulator use include the analysis of machine utilization, queue statistics, mean cycle time and mean WIP and production throughput, etc. This analysis can serve to push the bottleneck capacity to its limit, setup and test scheduling rules and preventive maintenance schedules, and determine personnel (operator) availability requirements. Thus, a good simulator allows for the investigation of complex “what-if” scenarios at a minimal cost, high speed, and without disturbing the normal production.

The System Model

The following figure and specification was taken from a test-bed designed by Karl Kempf, Manufacturing Systems Principal Scientist, of the INTEL Corporation. This test-bed is an example of a very small section in the Semiconductor FAB and is referred to as a Mini-FAB 6,14,16 .

The Mini-FAB included two products and test wafers with their process flows (production recipes) of six steps utilizing three different machine sets. There was one re-entrant step at each machine group, steps 4, 5 and 6. The machine groups emulate (in a small scale) Diffusion-C1 (2

Flores-Godoy, J., & Hoppensteadt, F. C., & Collins, D. W., & Tsakalis, K. (2000, June), Minimum Inventory Variability Dispatching Policies (Mivp) Paper presented at 2000 Annual Conference, St. Louis, Missouri. https://peer.asee.org/8567

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