The outbreak of COVID-19 has exerted an enormous impact on society, enterprises, and individuals. It has affected the work attitudes and psychology of employees to a certain extent and their job stress (JS) has also augmented accordingly, leading to increased turnover intention (TI). With the survey responses of 720 employees of small and medium enterprises (SMEs) in China as the sample, we studied the impact of COVID-19 related JS and TI with the moderating effect of perceived organizational support (POS). We utilized linear and multiple regression analysis using Windows SPSS 25. The research findings indicated that the JS caused by COVID-19 in the first affected region (Hubei) was significantly stronger than that in other regions (non-Hubei). JS had a significant positive relationship with employees’ TI, while POS had a significant negative connection with employees’ TI. We also identified that POS weakened the positive association between JS and employees’ TI. These findings are expected to be conducive to and conductive for the upcoming theoretical and empirical investigations as the founding guidelines, as well as for managers in formulating effective policies to curb JS, which would ultimately be helpful in reducing TI.
Blanks, an important raw material for the manufacturing industry, are semi-finished products for further processing. The energy consumption and processing efficiency in the process of blank production and use can be determined to a great extent in the blank design stage. The design of appropriate blank dimensions is an important means of realizing ecological civilization. Current blank designs seldom consider the production conditions of enterprises. In order to design energy-saving and efficient blanks on the basis of the actual conditions of an enterprise, this paper establishes the blank dimension optimization design model from the perspective of a business compass. With energy savings and efficiency as the goals, and the blank production and use-process equipment parameters as variables, the blank dimensions were optimized by an NSGA-II algorithm, and the results showed that the energy efficiency and processing efficiency of the designed blank dimensions were significantly better than for the existing blank dimensions in the process of enterprise operation.
The optimal selection of machine equipment can reduce the energy consumption and processing time of the parts processing process in enterprises. The energy consumption and time of using different equipment to process the same product vary greatly. Traditional equipment selection is only through qualitative analysis comparing the process characteristics of using different equipment or optimizing parameters for a single piece of equipment. It does not take into account the dynamics of the production process and does not consider the impact of process factors on production decisions. To solve this problem, we established a production equipment selection model based on the business compass model and proposed a calculation method that considered energy consumption and time objectives in the production process. Quantitative analysis can be performed for different equipment. The energy consumption and processing time of different equipment are calculated by the beetle antennae search (BAS) algorithm. A case study of machining end cap holes was carried out. The results showed that this method can calculate the optimal energy consumption and the optimal time of different equipment for producing the same product, which has good theoretical and practical significance for enterprises and governments to choose energy-saving and efficient production equipment.
Blank is the foundation for manufacturing enterprise production. The change of blank dimension is the fundamental purpose of product processing, and blank dimension change process dramatically affects the cost and energy consumption of blank production and use process. Therefore, the blank dimension design is of great significance for the sustainable development of enterprises. Based on the management concept of the business compass, combined with the enterprise development plan and production situation, this article established a blank dimension optimization design model, which can design the blank dimension according to enterprise demand. The model took the energy consumption and cost of the blank production and used process as the optimization objectives, and was solved by the gray wolf algorithm. The model was verified by analyzing the machining process of a fixture cavity. By comparison with standard square blank dimensions, the research results showed that the optimized square blank dimension can meet the objective of saving energy and reducing costs, it can also fully coordinate economy and resource consumption.
Sustainable blank dimension design is the key to the implementation of green industrial development. However, blank dimension design only considers the blank production factor of the blank dimension design stage, which cannot guarantee the blank production stage and the use stage’s overall goal. In this paper, based on the guiding thinking of a business compass, a low-carbon and low-energy consumption blank dimension optimization design model was proposed. Taking the process parameters of the production and the use of the blank as the variables, the grey wolf optimization algorithm was adopted to solve the problem. Taking the gear blanks dimension as an example, the optimized blank dimension is 98.6, compared with the standard blank dimension of 100, 105, the energy consumption is 95.7% and 93.1%, the carbon emission is 92.6% and 90.2%, and the material consumption is 96.5% and 87.5%, respectively. The sustainable blank dimension design has obvious advantages in terms of low energy consumption and low carbon, and it can save a lot of materials; it can also promote product sustainability.
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