Yeonjee Choi¹, Hyun Suk Hwang², Chang Soo Kim^1,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4901-4916, 2023, DOI:10.32604/cmc.2023.035219

Abstract A small and medium enterprises (SMEs) manufacturing platform aims to perform as a significant revenue to SMEs and vendors by providing scheduling and monitoring capabilities. The optimal job shop scheduling is generated by utilizing the scheduling system of the platform, and a minimum production time, i.e., makespan decides whether the scheduling is optimal or not. This scheduling result allows manufacturers to achieve high productivity, energy savings, and customer satisfaction. Manufacturing in Industry 4.0 requires dynamic, uncertain, complex production environments, and customer-centered services. This paper proposes a novel method for solving the difficulties of the SMEs manufacturing by applying and implementing… More >

Qinhui Liu¹, Nengjian Wang^1,*, Jiang Li¹, Tongtong Ma², Fapeng Li¹, Zhijie Gao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2073-2091, 2023, DOI:10.32604/cmes.2022.021433

Abstract As a typical transportation tool in the intelligent manufacturing system, Automatic Guided Vehicle (AGV) plays an indispensable role in the automatic production process of the workshop. Therefore, integrating AGV resources into production scheduling has become a research hotspot. For the scheduling problem of the flexible job shop adopting segmented AGV, a dual-resource scheduling optimization mathematical model of machine tools and AGVs is established by minimizing the maximum completion time as the objective function, and an improved genetic algorithm is designed to solve the problem in this study. The algorithm designs a two-layer coding method based on process coding and machine… More > Graphic Abstract

Eman K. Elsayed¹, Asmaa K. Elsayed^2,*, Kamal A. Eldahshan³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5103-5120, 2022, DOI:10.32604/cmc.2022.030803

Abstract Industry 4.0 production environments and smart manufacturing systems integrate both the physical and decision-making aspects of manufacturing operations into autonomous and decentralized systems. One of the key aspects of these systems is a production planning, specifically, Scheduling operations on the machines. To cope with this problem, this paper proposed a Deep Reinforcement Learning with an Actor-Critic algorithm (DRLAC). We model the Job-Shop Scheduling Problem (JSSP) as a Markov Decision Process (MDP), represent the state of a JSSP as simple Graph Isomorphism Networks (GIN) to extract nodes features during scheduling, and derive the policy of optimal scheduling which guides the included… More >

K. Gayathri Devi^*, R. S. Mishra, A. K. Madan

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 429-448, 2022, DOI:10.32604/iasc.2022.019330

Abstract An NP-hard problem like Flexible Job Shop Scheduling (FJSP) tends to be more complex and requires more computational effort to optimize the objectives with contradictory measures. This paper aims to address the FJSP problem with combined and contradictory objectives, like minimization of make-span, maximum workload, and total workload. This paper proposes ‘Hybrid Adaptive Firefly Algorithm’ (HAdFA), a new enhanced version of the classic Firefly Algorithm (FA) embedded with adaptive parameters to optimize the multi objectives concurrently. The proposed algorithm has adopted two adaptive strategies, i.e., an adaptive randomization parameter (α) and an effective heterogeneous update rule for fireflies. The adaptations… More >

Chia-Nan Wang¹, Zhao-Hong Cheng^2,*, Nguyen Ky Phuc Phan³, Van Thanh Nguyen⁴

Computer Systems Science and Engineering, Vol.38, No.2, pp. 239-249, 2021, DOI:10.32604/csse.2021.016578

Abstract Production scheduling involves all activities of building production schedules, including coordinating and assigning activities to each person, group of people, or machine and arranging work orders in each workplace. Production scheduling must solve all problems such as minimizing customer wait time, storage costs, and production time; and effectively using the enterprise’s human resources. This paper studies the application of flexible job shop modelling on scheduling a woven labelling process. The labelling process includes several steps which are handled in different work-stations. Each workstation is also comprised of several identical parallel machines. In this study, job splitting is allowed so that… More >