The design of simulation languages for systems with multiple modularities
Article Abstract:
Biological systems exhibit several characteristics that are not shared by human-engineered systems: there are often no clear module boundaries (or there are several module boundaries, depending on the question being asked); individual parts often serve multiple roles, depending on the behavior being studied; and system characteristics often vary from individual to individual. Conventional simulation languages, however, do not cope well with this non-modularity. We have developed a theory of the design of simulation languages for such systems, and partially verified it in one case study. We separate the notion of "structure" S of a system from the "behavior" B of its parts. We allow multiple versions of both the structure (S1, S2, ...) and the corresponding behavior (B1/Si~, B2/Si~, ...) of each part Si. The different structures or behaviors might be alternative theories, or abstractions of each other, for example. We also have theories of how to interpret the simulations produced by (Si, Bj, /Si~) pairs. One goal is to extract "design" information, i.e. explain how the system solves problems. Another is to test the effects of alternative models of behavior B1/Si~, B2/Si~, ... for the same structure, or the effects on behavior due to alterations in structure. A third is to judge the relative degree of consistency between various (Si, Bj/Si~) pairs. We exhibit how these ideas apply to the motor nervous system of the nematodes C. elegans and Ascaris suum. We also provide arguments that this kind of simulation methodology is also applicable to engineered artifacts, such as systems where parts must serve multiple roles. (Reprinted by permission of the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1991
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A simulation model for determining maintenance staffing in an industrial environment
Article Abstract:
In a plant, the size of a maintenance staff must be related to the level of output. The optimal level of maintenance is essential for maximizing the output of the production process. This paper develops a simulation model to determine the size of a maintenance crew. The heart of the simulation model is the machine servicing model. The model is applied to a local soft drink plant to determine the optimal number of their maintenance crew, and the result of the study is presented. (Reprinted by permission from the publisher.)
Publication Name: SIMULATION
Subject: Engineering and manufacturing industries
ISSN: 0037-5497
Year: 1992
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