No abstract

This paper addresses electricity consumption management in manufacturing enterprises. The research aims to provide manufacturing enterprises with an effective tool to control electricity costs. Recently, some factors have been observed to affect the rapid changes in the operating conditions of enterprises. These include the transformation of the power sector toward renewable energy, the disruption of supply chains resulting from a coronavirus pandemic, political crises, and process automation. A method for the analysis and management of electricity consumption in enterprises based on simulation modeling is proposed. The simulation model contains predefined objects representing physical system elements and the data processing algorithm. The production order execution time, energy consumption, employee overtime, and machine load are included in the model. The results show that it is possible to determine the level of power available for the process completion and its influence on the production volume and realization time. In the studied case, when the available power was reduced by half, there was an increase in order execution time of nearly 25 percent and an increase in energy consumption of nearly 15 percent. The method can be used in the operational activities of enterprises as well as extended to different types of production processes.

The process of technology management contains various stages, such as the identification, selection, acquisition, implementation, and maintenance of technologies. In the case of power generation companies, a key aspect of the selection stage is the choice of generation technologies for newly commissioned units. The investment decision depends on many factors, primarily economic, environmental, social, technological, and legal, and represents a complex multi-criteria problem. Currently, the decision is further complicated by the often unpredictable tightening of environmental standards, forcing the closure of conventional sources, on which many countries have so far based their energy security. The paper analyzes the problem of choosing one of the so-called clean coal technologies to be implemented in conditions of transformation of the power sector. In this paper, five selected clean coal technologies are characterized, and the SMART method is adopted to technology selection. The following technologies were considered: supercritical coal-fired power plant (with and without CCS), IGCC power plant (with and without CCS), and IGCC power plant with CCS and integrated hydrogen production. Nine practical criteria (in three main groups: environmental, technological, economic) for comparing technologies are defined, computational experiments performed, and conclusions from the research presented. The work was based on the literature study of multi-criteria decision support and an analysis of power sector needs based on the example of the Polish power sector. The conducted research, apart from the technology recommendation, led to the conclusion that the chosen method may be applied to decision-making in the field of power generation technology management. The study also indicated the potential direction of the development of a power generation structure in a situation where a component of ensuring energy security is the use of available coal fuels.

The existing definitions of the logistic centre have been analysed for the purpose of creating a uniform definition. The work uses the main Polish definitions as well as foreign ones. The uniform, suitable to be the basis of further research definition has been created as a result of analysing the main factors of a logistic centre.

Make-To-Stock (MTS) and Make-To-Order (MTO) are the two traditional strategies in production management. In the case of the MTS there is a growing demand for a new approach, which is called Make-To-Availability (MTA) strategy. The paper characterizes and compares the MTS and MTA strategies. The comparative analysis based, among others, on computational experiments carried out in a computer program developed in Microsoft Visual Studio 2017 Environment was presented. The models have been prepared for both strategies with the same assumptions: external conditions (market demand) and internal conditions (structure of the production process). The investigation of how the strategies respond to various scenarios of demand intensity was done. The simulation models were prepared and validated for the case of the production line in one of the industrial automation company. The research shows that the use of the MTA strategy in the majority of cases gives much better results than the use of the MTS strategy due to the minimization of storage costs and the costs of non-fulfillment of the customers' demand. The directions for further research were also presented.