Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researche...Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.展开更多
From the point of view of market economy, aiming at the flexible machiningproblem,this paper discusses how to determine the maximum profit-orientedoptimum preduction quantity, optimum cutting speed and optimum price u...From the point of view of market economy, aiming at the flexible machiningproblem,this paper discusses how to determine the maximum profit-orientedoptimum preduction quantity, optimum cutting speed and optimum price underthe condition of single machines,single type of product and limited resources.展开更多
Bioinspired neuromorphic machine vision system(NMVS)that integrates retinomorphic sensing and neuromorphic computing into one monolithic system is regarded as the most promising architecture for visual perception.Howe...Bioinspired neuromorphic machine vision system(NMVS)that integrates retinomorphic sensing and neuromorphic computing into one monolithic system is regarded as the most promising architecture for visual perception.However,the large intensity range of natural lights and complex illumination conditions in actual scenarios always require the NMVS to dynamically adjust its sensitivity according to the environmental conditions,just like the visual adaptation function of the human retina.Although some opto-sensors with scotopic or photopic adaption have been developed,NMVSs,especially fully flexible NMVSs,with both scotopic and photopic adaptation functions are rarely reported.Here we propose an ion-modulation strategy to dynamically adjust the photosensitivity and time-varying activation/inhibition characteristics depending on the illumination conditions,and develop a flexible ionmodulated phototransistor array based on MoS_(2)/graphdiyne heterostructure,which can execute both retinomorphic sensing and neuromorphic computing.By controlling the intercalated Li^(+) ions in graphdiyne,both scotopic and photopic adaptation functions are demonstrated successfully.A fully flexible NMVS consisting of front-end retinomorphic vision sensors and a back-end convolutional neural network is constructed based on the as-fabricated 28×28 device array,demonstrating quite high recognition accuracies for both dim and bright images and robust flexibility.This effort for fully flexible and monolithic NMVS paves the way for its applications in wearable scenarios.展开更多
In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a r...In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a research hotspot in recent years.In this paper,DRCFJSP with the objective of minimizing the makespan is studied,and it should solve three sub-problems:machine allocation,worker allocation,and operations sequencing.To solve DRCFJSP,a novel hybrid algorithm(CEAM-CP)of cooperative evolutionary algorithm with multiple populations(CEAM)and constraint programming(CP)is proposed.Specifically,the CEAM-CP algorithm is comprised of two main stages.In the first stage,CEAM is used based on three-layer encoding and full active decoding.Moreover,CEAM has three populations,each of which corresponds to one layer encoding and determines one sub-problem.Moreover,each population evolves cooperatively by multiple cross operations.To further improve the solution quality obtained by CEAM,CP is adopted in the second stage.Experiments are conducted on 13 benchmark instances to assess the effectiveness of multiple crossover operations,CP,and CEAM-CP.Most importantly,the proposed CEAM-CP improves 9 best-known solutions out of 13 benchmark instances.展开更多
基金Supported by Shanghai Municipal Science and Technology Commission(Grant No.12JC1408700)National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant Nos.2013ZX04012-071,2011ZX04015-022)
文摘Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.
文摘From the point of view of market economy, aiming at the flexible machiningproblem,this paper discusses how to determine the maximum profit-orientedoptimum preduction quantity, optimum cutting speed and optimum price underthe condition of single machines,single type of product and limited resources.
基金National Natural Science Foundation of China,Grant/Award Numbers:12174207,51802220,62274119Fundamental Research Funds for the Central Universities,Grant/Award Numbers:010-63233006,010-DK2300010203。
文摘Bioinspired neuromorphic machine vision system(NMVS)that integrates retinomorphic sensing and neuromorphic computing into one monolithic system is regarded as the most promising architecture for visual perception.However,the large intensity range of natural lights and complex illumination conditions in actual scenarios always require the NMVS to dynamically adjust its sensitivity according to the environmental conditions,just like the visual adaptation function of the human retina.Although some opto-sensors with scotopic or photopic adaption have been developed,NMVSs,especially fully flexible NMVSs,with both scotopic and photopic adaptation functions are rarely reported.Here we propose an ion-modulation strategy to dynamically adjust the photosensitivity and time-varying activation/inhibition characteristics depending on the illumination conditions,and develop a flexible ionmodulated phototransistor array based on MoS_(2)/graphdiyne heterostructure,which can execute both retinomorphic sensing and neuromorphic computing.By controlling the intercalated Li^(+) ions in graphdiyne,both scotopic and photopic adaptation functions are demonstrated successfully.A fully flexible NMVS consisting of front-end retinomorphic vision sensors and a back-end convolutional neural network is constructed based on the as-fabricated 28×28 device array,demonstrating quite high recognition accuracies for both dim and bright images and robust flexibility.This effort for fully flexible and monolithic NMVS paves the way for its applications in wearable scenarios.
基金supported by the Funds for the National Natural Science Foundation of China(Nos.52205529 and 62303204)Natural Science Foundation of Shandong Province(Nos.ZR2021QE195 and ZR2021QF036)+2 种基金Youth Innovation Team Program of Shandong Higher Education Institution(No.2023KJ206)Guangyue。Youth Scholar Innovation Talent Program support received from Liaocheng University(No.LCUGYTD2022-03)Foundation of Young Talent of Lifting engineering for Science and Technology in Shandong,China(No.SDAST2024QTA074).
文摘In real production,machines are operated by workers,and the constraints of worker flexibility should be considered.The flexible job shop scheduling problem with both machine and worker resources(DRCFJSP)has become a research hotspot in recent years.In this paper,DRCFJSP with the objective of minimizing the makespan is studied,and it should solve three sub-problems:machine allocation,worker allocation,and operations sequencing.To solve DRCFJSP,a novel hybrid algorithm(CEAM-CP)of cooperative evolutionary algorithm with multiple populations(CEAM)and constraint programming(CP)is proposed.Specifically,the CEAM-CP algorithm is comprised of two main stages.In the first stage,CEAM is used based on three-layer encoding and full active decoding.Moreover,CEAM has three populations,each of which corresponds to one layer encoding and determines one sub-problem.Moreover,each population evolves cooperatively by multiple cross operations.To further improve the solution quality obtained by CEAM,CP is adopted in the second stage.Experiments are conducted on 13 benchmark instances to assess the effectiveness of multiple crossover operations,CP,and CEAM-CP.Most importantly,the proposed CEAM-CP improves 9 best-known solutions out of 13 benchmark instances.
