3 research outputs found
ΠΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ ΡΠΈΡΡΠ΅ΠΌΠ°Ρ Ρ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΠΌΠΈ Π±ΡΡΠ΅ΡΠ°ΠΌΠΈ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ²
Modern methods of process planning in conveyor systems with buffers of a certain size between processing devices allow optimizing schedules for single tasks or fixed task packages with a limited number of them and a limited number of devices. The use of mathematical models of the processes of performing single tasks (task packages) used by these methods in optimizing the composition of packages and schedules for their execution in systems with an arbitrary number of packages and devices is impossible. At the same time, mathematical models of the processes of executing task packages in conveyor systems in the presence of buffers of limited sizes between devices are the basis for the development of methods for optimizing their (package) compositions and schedules for the implementation of actions with them on the devices of conveyor systems. In this regard, the article develops mathematical models of multi-stage processes of performing an arbitrary number of task packages in conveyor systems in the presence of intermediate buffers of limited sizes for two and three devices, as well as for an arbitrary number of devices. The use of these models makes it possible to determine the time points of the start of the execution of task packages on the devices of conveyor systems, taking into account the limited size of intermediate buffers, as well as the duration of time intervals for the use of these resources and the efficiency of their use over time. An algorithm has also been developed for mathematical modeling of the processes of executing task packages in conveyor systems in the presence of intermediate buffers of limited size, which calculates the time characteristics of these processes based on a given order of implementation of actions with task packages on the devices of conveyor systems. An application has been developed that implements synthesized mathematical models of the processes of executing task packages in conveyor systems with intermediate buffers of limited sizes and an appropriate method for modeling these processes. Versatile testing of the developed application has shown that the obtained mathematical models and the modeling method adequately describe the course of multi-stage processes of task packages in pipeline systems, set using different values of their (processes) parameters.Π‘ΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Ρ Π±ΡΡΠ΅ΡΠ°ΠΌΠΈ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π·ΠΌΠ΅ΡΠ° ΠΌΠ΅ΠΆΠ΄Ρ ΠΎΠ±ΡΠ°Π±Π°ΡΡΠ²Π°ΡΡΠΈΠΌΠΈ ΠΏΡΠΈΠ±ΠΎΡΠ°ΠΌΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΠΎΠΏΡΠΈΠΌΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΡΠ°ΡΠΏΠΈΡΠ°Π½ΠΈΡ Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ Π΅Π΄ΠΈΠ½ΠΈΡΠ½ΡΡ
Π·Π°Π΄Π°Π½ΠΈΠΉ Π»ΠΈΠ±ΠΎ ΡΠΈΠΊΡΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ ΠΏΡΠΈ ΠΈΡ
ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅ ΠΈ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΠΎΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π΅ ΠΏΡΠΈΠ±ΠΎΡΠΎΠ². ΠΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ Π΅Π΄ΠΈΠ½ΠΈΡΠ½ΡΡ
Π·Π°Π΄Π°Π½ΠΈΠΉ (ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ), ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΡ
ΡΡΠΈΠΌΠΈ ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠΈ, ΠΏΡΠΈ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΡΠΎΡΡΠ°Π²ΠΎΠ² ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² ΠΈ ΡΠ°ΡΠΏΠΈΡΠ°Π½ΠΈΠΉ ΠΈΡ
Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ Π² ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ»ΡΠ½ΡΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎΠΌ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² ΠΈ ΠΏΡΠΈΠ±ΠΎΡΠΎΠ² ΡΠ²Π»ΡΠ΅ΡΡΡ Π½Π΅Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΡΠΌ. Π ΡΠΎ ΠΆΠ΅ Π²ΡΠ΅ΠΌΡ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
ΠΏΡΠΈ Π½Π°Π»ΠΈΡΠΈΠΈ Π±ΡΡΠ΅ΡΠΎΠ² ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ² ΠΌΠ΅ΠΆΠ΄Ρ ΠΏΡΠΈΠ±ΠΎΡΠ°ΠΌΠΈ ΡΠ²Π»ΡΡΡΡΡ ΠΎΡΠ½ΠΎΠ²ΠΎΠΉ Π΄Π»Ρ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΈΡ
(ΠΏΠ°ΠΊΠ΅ΡΠΎΠ²) ΡΠΎΡΡΠ°Π²ΠΎΠ² ΠΈ ΡΠ°ΡΠΏΠΈΡΠ°Π½ΠΈΠΉ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΄Π΅ΠΉΡΡΠ²ΠΈΠΉ Ρ Π½ΠΈΠΌΠΈ Π½Π° ΠΏΡΠΈΠ±ΠΎΡΠ°Ρ
ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ. Π ΡΠ²ΡΠ·ΠΈ Ρ ΡΡΠΈΠΌ Π² ΡΡΠ°ΡΡΠ΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΌΠ½ΠΎΠ³ΠΎΡΡΠ°Π΄ΠΈΠΉΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ»ΡΠ½ΠΎΠ³ΠΎ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π° ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
ΠΏΡΠΈ Π½Π°Π»ΠΈΡΠΈΠΈ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΡ
Π±ΡΡΠ΅ΡΠΎΠ² ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ² Π΄Π»Ρ Π΄Π²ΡΡ
ΠΈ ΡΡΠ΅Ρ
ΠΏΡΠΈΠ±ΠΎΡΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ Π΄Π»Ρ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ»ΡΠ½ΠΎΠ³ΠΎ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²Π° ΠΏΡΠΈΠ±ΠΎΡΠΎΠ². ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠΈΡ
ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΡΡ ΠΌΠΎΠΌΠ΅Π½ΡΡ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π½Π°ΡΠ°Π»Π° Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π½Π° ΠΏΡΠΈΠ±ΠΎΡΠ°Ρ
ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ Ρ ΡΡΠ΅ΡΠΎΠΌ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ² ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΡ
Π±ΡΡΠ΅ΡΠΎΠ², Π° ΡΠ°ΠΊΠΆΠ΅ Π΄Π»ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»ΠΎΠ² Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΈΡ
ΡΠ΅ΡΡΡΡΠΎΠ² ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΈΡ
ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ. Π’Π°ΠΊΠΆΠ΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½ Π°Π»Π³ΠΎΡΠΈΡΠΌ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
ΠΏΡΠΈ Π½Π°Π»ΠΈΡΠΈΠΈ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΡ
Π±ΡΡΠ΅ΡΠΎΠ² ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ², ΠΎΡΡΡΠ΅ΡΡΠ²Π»ΡΡΡΠΈΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π·Π°Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠΎΡΡΠ΄ΠΊΠ° ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ Π΄Π΅ΠΉΡΡΠ²ΠΈΠΉ Ρ ΠΏΠ°ΠΊΠ΅ΡΠ°ΠΌΠΈ Π·Π°Π΄Π°Π½ΠΈΠΉ Π½Π° ΠΏΡΠΈΠ±ΠΎΡΠ°Ρ
ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ Π²ΡΡΠΈΡΠ»Π΅Π½ΠΈΠ΅ Π²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΡΡΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ². ΠΡΡΡΠ΅ΡΡΠ²Π»Π΅Π½Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ, ΡΠ΅Π°Π»ΠΈΠ·ΡΡΡΠ΅Π³ΠΎ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
Ρ ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΡΠΌΠΈ Π±ΡΡΠ΅ΡΠ°ΠΌΠΈ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½Π½ΡΡ
ΡΠ°Π·ΠΌΠ΅ΡΠΎΠ² ΠΈ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΡΡΡΠΈΠΉ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΡΡΠΈΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ². Π Π°Π·Π½ΠΎΡΡΠΎΡΠΎΠ½Π½Π΅Π΅ ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΈΠ»ΠΎΠΆΠ΅Π½ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΎ, ΡΡΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΈ ΠΌΠ΅ΡΠΎΠ΄ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎ ΠΎΠΏΠΈΡΡΠ²Π°ΡΡ Ρ
ΠΎΠ΄ ΠΌΠ½ΠΎΠ³ΠΎΡΡΠ°Π΄ΠΈΠΉΠ½ΡΡ
ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ² Π²ΡΠΏΠΎΠ»Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΊΠ΅ΡΠΎΠ² Π·Π°Π΄Π°Π½ΠΈΠΉ Π² ΠΊΠΎΠ½Π²Π΅ΠΉΠ΅ΡΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
, Π·Π°Π΄Π°Π²Π°Π΅ΠΌΡΠΉ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π·Π½Π°ΡΠ΅Π½ΠΈΠΉ ΠΈΡ
(ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ²) ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΎΠ²
Development and Simulation Assessment of Semiconductor Production System Enhancements for Fast Cycle Times
Long cycle times in semiconductor manufacturing represent an increasing challenge for the industry and lead to a growing need of break-through approaches to reduce it. Small lot sizes and the conversion of batch processes to mini-batch or single-wafer processes are widely regarded as a promising means for a step-wise cycle time reduction. Our analysis with discrete-event simulation and queueing theory shows that small lot size and the replacement of batch tools with mini-batch or single wafer tools are beneficial but lot size reduction lacks persuasive effectiveness if reduced by more than half. Because the results are not completely convincing, we develop a new semiconductor tool type that further reduces cycle time by lot streaming leveraging the lot size reduction efforts. We show that this combined approach can lead to a cycle time reduction of more than 80%
Considering stockers in reentrant hybrid flow shop scheduling with limited buffer capacity
Diversification of products has increased the involvement of reentrant manufacturing processes, in which a job returns multiple times to a machine at the preceding workflow stage to continue the manufacturing process. Reentrant flow shop manufacturing can substantially improve manufacturing efficiency when scheduled properly. In practice, advanced manufacturing companies (e.g., semiconductor foundries) have introduced automated material handling system (AMHS), including stockers that serve as centralized inventory buffer space for temporarily storing the inventories owing to limited buffer capacity of each machine. However, no previous studies on reentrant flow shop scheduling have considered the impact of limited buffer capacity or stockers on scheduling efficiency. Consequently, this study investigated the application of stockers in solving the reentrant hybrid flow shop scheduling problem with limited buffer capacity. With the objective of optimizing the makespan and mean flowtime of a schedule, this problem is NP-hard because it generalizes the flow shop problem. Therefore, this study developed a hybrid harmony search and genetic algorithm (HHSGA) for the problem, in which limited buffer capacity and stockers cause solution decoding to be non-trivial. Experimental comparison on scheduling problems with different numbers of jobs showed that the HHSGA performed better than conventional algorithms. Moreover, among three manufacturing conditions (i.e., with buffers and stockers, with buffers only, and with stockers only), the results indicated that the condition using inventory buffers and stockers was more beneficial