TEMPORAL PROCESSES ALIGNMENT METHOD FOR COMPLICATED SYSTEMS
DOI:
https://doi.org/10.20998/2413-3000.2020.2.1Keywords:
Temporal Processes, Complicated System, Lifecycle, Costs, Optimization, Recovery, Forecast, Time SpanAbstract
The presented work researches a possibility to compose temporal processes to reduce complicated system operation expenditures. It is established, that temporal processes are classified into three categories in view of their influence on a system’s functional state. They are single (1), repeating (2) and cyclic (3). It is also established, that presence of large number of temporal processes within a system requires an individual approach to their control. Temporal processes alignment method is developed consisting of six fundamental provisions: 1) with none additional restrictions the attraction point falls within the time interval of either of temporal processes; 2) temporal processes’ shifting does not involve additional expenditures if it does not generate extra temporal process within the time interval under review; 3) with increased system’s stoppage costs the attraction points tend to areas of the system’s forced stoppage and increase noticeably their attracting features; 4) attraction area is determined by an area where all the not repeating temporal processes are located; 5) in the course of alignment of temporal processes involving reduction of the number of system’s stoppages there is always a limit expenditures value justifying such an alignment; 6) alignment of temporal processes running within relative attraction zone may be implemented providing meeting the conditions. These provisions construe a basis to take a decision about possibility and feasibility of their alignment. It is identified, that one of essential parameters of the processes’ alignment is a choice of a proper time for their alignment. An algorithm is offered based on the developed method enabling to implement temporal processes alignment procedure depending on data processing systems’ resources to reduce substantially chance of error in adopting a decision in complicated systems’ management.References
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