Digital twin is an important emerging technology for digital transformation and intelligent upgrading. Digital twin models are the prerequisite for digital twin applications, and their quality directly affects the quality of digital twin services in monitoring, simulation, prediction, optimization, and other areas. However, researchers have paid insufficient attention to the quality control of digital twin models, thus hindering their effective application. To effectively control model construction and optimize model quality in the design process, this study developed digital twin model quality optimization and control methods based on workflow management. First, a workflow process model integrating digital twin model evaluation was constructed, which integrated the design process and model evaluation methods into workflow management. Then, digital twin model quality control and optimization in different stages were achieved at the macro and micro levels. Thus, the digital twin model quality was effectively controlled during the design process, and targeted design resources were selected to optimize model quality. Finally, the validity of the proposed method of model quality optimization and control was verified using the digital twin models of a practical teaching platform and a multifunctional lift-and-slide experimental line. All evaluation indexes of the model achieved good values, and the target quality optimization of the model could be performed during the design process. The results indicate that the proposed method can effectively control and optimize the model quality, which has excellent feasibility and enables the effective application of the digital twin.

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In the car-sequencing problem of mixed-model assembly lines, a series of cars with different model types will be put into the assembly line in a certain order considering a variety of goals and constraints. In this paper, a multi-objective cuckoo search algorithm based on the record matrix is proposed to solve this problem. In this algorithm, the factors, including the variation of parts usage rates, variation of workstation workload, idle time, overload time, and model switching cost are considered. The record matrix proposed in this paper is utilized to record the characteristic information of the optimal solutions and historical solutions. Meanwhile, two search strategies based on the record matrix are proposed to enhance the ability of local search and global search in the algorithm. The proposed algorithm is verified by a real case. The results show that the proposed model and algorithm have good results, and they have the potential to address other similar problems. INDEX TERMS Car-sequencing problem, mixed-model assembly line, multi-objective cuckoo search algorithm, record matrix.

Dodders (Cuscuta chinensis) are rootless and holoparasitic herbs that can infect a variety of host plants, including the vitally important economic and bioenergy crop soybean (Glycine max). Although dodder parasitism severely affects the physiology of host plants, little is known about its effects on fungal communities and root secondary metabolites in hosts. In this study, variations in root-associated fungal communities and root metabolites of soybean under different parasitism conditions were investigated using ITS rRNA gene sequencing and UPLC–MS/MS metabolome detection technologies. The results showed that dodder parasitism significantly altered the composition and diversity of the fungal communities in the rhizosphere and endosphere of soybean. The relative abundance of the potential pathogenic fungus Alternaria significantly increased in the root endosphere of dodder-parasitized soybean. Furthermore, correlation analysis indicated that the fungal community in the root endosphere was susceptible to soil factors under dodder parasitism. Meanwhile, the content of soil total nitrogen was significantly and positively correlated with the relative abundance of Alternaria in the rhizosphere and endosphere of soybean. Metabolomic analysis indicated that dodder parasitism altered the accumulation of flavonoids in soybean roots, with significant upregulation of the contents of kaempferol and its downstream derivatives under different parasitism conditions. Taken together, this study highlighted the important role of dodder parasitism in shaping the fungal communities and secondary metabolites associated with soybean roots, providing new insights into the mechanisms of multiple interactions among dodder, soybean, microbial communities and the soil environment.