The mitogen-activated protein kinase (MAPK) Hog1p plays an essential role in the yeast hyperosmotic response. A homolog of the HOG1 gene was isolated from the halophilic black yeast Hortaea werneckii encoding a putative 359 amino acid protein, HwHog1p, with high homology to Saccharomyces cerevisiae Hog1p and to other eukaryotic Hog1p homologs. HwHog1p contains a TGY motif within a protein kinase catalytic domain and a C-terminal common docking (CD) motif. Its activation by increased salinity is regulated at the posttranscriptional level. HwHog1p is located on the plasma membrane under nonstress conditions. Upon increased external salinity it is translocated from the membrane, presumably to the nucleus.
Due to increasing competition in the global market and to meet the need for rapid changes in product variability, it is necessary to introduce self-configurable and smart solutions within the entire process chain, including manual assembly to ensure the more efficient and ergonomic performance of the manual assembly process. This paper presents a smart assembly system including newly developed smart manual assembly workstation controlled by a smart algorithm. The smart assembly workstation is self-configurable according to the anthropometry of the individual worker, the complexity of the assembly process, the product characteristics, and the product structure. The results obtained by a case study show that is possible to organize manual assembly process with rapid adaptation of the smart assembly system to new products and workers characteristics, to achieve ergonomic working conditions through Digital Human Modelling (DHM), to minimize assembly time, and to prevent error during the assembly process. The proposed system supports the manual assembly process redesign to ensure a better working environment and aims to have an important value for applying the smart algorithms to manual assembly workstations in human-centered manufacturing systems.
Industry 4.0 introduces smart solutions throughout the company’s supply chain, including manual assembly, where the goal is to ensure shorter work cycle time, increase productivity and quality, while minimizing costs. Following the principles of this paradigm, this paper proposes a digital transformation of the manual assembly process by implementing a multi-criterial algorithm (MCA) for adjusting and configuring a human-centered smart manual assembly workstation to ensure efficient and ergonomic performance of the manual assembly process. The MCA takes into account various influential parameters, such as the anthropometry of the individual worker, gender, complexity of the assembly process, product characteristics, and product structure. The efficiency of the MCA was verified both in the laboratory environment with the time analysis and in the virtual environment using Digital Human Modelling through several ergonomic analyses. The results of the implementation of the MCA on a manual assembly workstation support the digital (re)design of the manual assembly process with the aim of creating an efficient and ergonomically suitable workstation for each worker, thus increasing the productivity and efficiency of the human-centered manual assembly process.
The paper presents a simple simulation model of the lifting procedure that can be used to predict the total time required for the sequence of basic manual assembly tasks depending on the various parameters of the load and with regard to the workers' health. The aim of the research is to determine the appropriateness of using simulation tool for (re)setting time standards for manual assembly tasks. An avatar in the simulation model performs sequences of tasks with a handling mass of up to 20.5 kg. The individual times obtained from the simulation model were analysed and compared with several time prediction methods and validated in laboratory environment. An analysis of the influence of different load parameters on the total time was also performed. Dependency is mostly linear, so from the practitioner point of view, we can predict with reasonable certainty the total time for any sequence of manual assembly tasks for every size and mass of the box. Based on the results we can confirm that simulation tool JACK is suitable not only for ergonomic analyses but also for setting time standards for the workers. Furthermore, with the simulation tool we analyse the process and get the accurate results in shorter time compared to other mentioned methods.
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