**3. Materials and Methods**

A comprehensive study of the energy consumption of a production system was based on the identification of all elements of the system that consume electricity. The exclusion of any element will result in an incomplete view of the analysis and subsequently in inappropriate decisions being made by the enterprise. The literature review shows that depending on the purpose of the study and the analysis capabilities, the approaches will vary. In this paper, a multi-stage research method is presented to show how to study energy consumption in an enterprise using simulation modeling. The research method is shown in Figure 1. The subsequent stages of the method are described below.

**Figure 1.** Research method.

**Stage 1. Defining the subject of energy consumption research.** The purpose of the analysis to be performed will influence the scope of the work undertaken. From the literature survey conducted, there are several approaches to studying energy consumption, related to either a tight or wide scope of the study. In the tight scope, the analysis deals with energy consumption on a single machine, where the study will focus on that single facility and the instrumentation/equipment used on that machine. In the case when the analysis concerns the entire production cell (production line, production slot), tests will be conducted for each machine (including equipment) and the transport operations related to the flow of material between objects (machines, buffers between stations, place of collection of materials/parts or storage of finished products). Transport operations include belt feeders, forklifts, etc.

A comprehensive approach assumes the identification of the impact of the environment in which the studied production system operates. Therefore, the analysis of the entire production system should not only take into account the individual energy consumption of individual production cells (located in a given area), the service system (transport, picking materials, parts, semi-finished or finished goods), but also the environment of the given production system (lighting, air conditioning, social facilities, computers for processing production orders). In selected studies, further levels of analysis appeared concerning energy consumption within interconnected production systems or the entire supply chain. Due to the research topic undertaken in this paper, the authors decided to include the first three levels indicated in the research method.

The specific scope of the research carried out influences the subsequent activities performed within the method—limiting or extending the scope of these activities.

**Stage 2. Identification of enterprise resources in terms of power and electricity consumption.** The subject specified in stage 1 sets the level at which the electricity consumption analysis will be performed. Based on this, it is clear how detailed the enterprise resources should be analyzed. The classification of enterprise resources includes physical resources, information resources, human resources, and financial resources. In the framework of each group, it is necessary to identify all objects used in the implementation of the production process that are associated with energy consumption. The largest number of objects can be found in the material resources, where the following are distinguished: machines, tools, possible means of transport, or equipment of the entire production system. In other resources, the range of identified objects will be tighter and will be more limited to the level of analysis performed (machine level, production cell level, or production system level).

As part of information resources, the knowledge that employees have should be identified. Knowledge itself is not associated with energy consumption, but the way it is collected, processed, and the process of exchanging knowledge among employees (for example, through computers, tablets, and cell phones) is.

Within human resources, employees who perform tasks in the production area under study should be identified. Similar to information resources, workers affect energy consumption by performing activities related to/involving machine operation, connecting/disconnecting tooling, or operating logistics equipment. Therefore, the identified activities must be classified appropriately to the levels of analysis performed. For example, devices used to collect and process data on the process flow or readers recording working time should be analyzed only at the level of examining a production cell or the whole production system.

The final resource is financial resources. Similar to the previously described information and human resources, the nature of financial resources does not involve/directly cause energy consumption. However, the activities related to recording or managing these resources using electronic equipment (computers, tablets) are associated with energy consumption. The identification of each resource at the listed levels of energy use analysis is shown in Table 2.


**Table 2.** Identification of resources corresponding to energy consumption levels.


**Table 2.** *Cont*.

**Stage 3. Modeling individual detailed resources of an enterprise due to electricity consumption.** It is necessary to identify the power and energy consumption profile of the enterprise, having determined the enterprise resources to be studied. For this purpose, for each identified resource, the parameters characterizing the consumption profile are determined. The range of parameters studied is complex and should take into account the standard nature of the work of a given resource. Additionally, it should include changes of this nature depending on the changing factors of the surrounding environment. Therefore, these parameters can be divided into internal factors (related to the operation of the machine—the operating states of the analyzed object) and external factors. If there are several resources with similar parameters working at the same time, the resources can be aggregated and studied as a whole. A summary of the key factors is presented in Table 3.

**Table 3.** Parameters characterizing the power and energy consumption profile.



**Table 3.** *Cont*.

**Stage 4. Building a simulation model of a manufacturing system.** Based on the specified level of analysis of energy consumption (machine, production cell, or production system), the objects that should be placed in the simulation model should be identified. The list of objects should be as presented in Table 1. For each level, the resources enabling the realization of the production process have been defined, divided into the material, personnel, financial, and information resources. Within the framework of the simulation model being built, it is possible to represent material and personnel resources using objects occurring in the selected computer modeling program. In the next step, it is necessary to identify the connections occurring between these objects. For each identified object, it is necessary to determine the set of parameters, characterizing the data on the course of the production process (duration of a technological operation, setup time, the size of the production batch) and data on energy consumption (normative for different states of the machine). The simulation model should be validated to confirm the correctness of the representation of the tested real system.

The developed simulation model makes it possible to carry out several analyses of a given production area without the need to interfere in the real process. Particularly in the case of the analysis of power consumption by the equipment, carrying out tests on the real system would be difficult due to the necessity of stopping the production of objects in progress, the possibility of failure to the objects consuming energy from the system, or the entire power system in the company. An additional advantage of using computer simulation is the possibility of conducting tests in a short time considering many different variants of solutions through one built model—changing only the values of selected variables. The more data are entered into the model, the more analyses (with a wider scope) will be possible to conduct.

**Stage 5. Verification of changes in electricity consumption with the simulation model. Power limitation addressing.** In a general case, the subject of research can be the analysis of the impact of the power limitation (by a set value) on the analyzed production system. The power limitation may be of soft or hard character (constraint). The soft constraint may result from high electricity prices in a certain part of the planning period (e.g., during selected hours of the work shift). Exceeding this constraint is possible and

affects the high cost of implementing the production process. Maintaining this constraint makes it necessary to shift production to other hours (e.g., night hours), when the energy price is acceptable. The hard case of the capacity constraint may be caused by the limitation of supply by the power system. This constraint cannot be exceeded. Any non-executed production must be postponed to another period. In any case, at the start of the operation, the production system has a certain level of available capacity. Then, during the execution of the process, the available power is reduced in the specified time. It is necessary to identify objects on which it is possible to change the state of power consumption. This should be conducted in the period with the introduced constraint, according to Table 2.

The reduction in power consumption can be realized in many ways, depending on the possibilities and needs of the implemented production process. A general (optimal or sub-optimal) procedure for power reduction should be the subject of further research. In the general case, a mathematical model of the problem and an optimization algorithm for its solution should be developed. In the practical case, a heuristic approach can be used. In such an approach, different action scenarios can be proposed and investigated. The scenarios can be based on the sequential start-up of operations, keeping selected machines in operation, keeping a bottleneck in operation, and in worst cases, stopping production. The criterion for each scenario should be to not exceed the limit of available power.

**Stage 6. Recommendations for the production process activities.** Based on the results obtained from the experiments, it is necessary to determine the impact of different strategies for dealing with the occurrence of power limitations. The simulation carried out allows one to determine the change in the studied parameters in terms of measurable and non-measurable quantities. For each investigated state, it is necessary to determine quantities such as the production schedule, the graph of power consumption, the duration of the production process, the value of energy consumption, and the load of machines involved in the implemented production process. The data obtained from the simulation model are only the proposals of different strategies of action by the enterprise and should be evaluated by the enterprise because of the possibility of implementing each strategy in the production process and the effects it will have on the enterprise. The results of the evaluation should be recommendations for further actions in the production process.

The indicated characteristics such as process duration and energy consumption are measurable parameters that allow for a simple comparative analysis of each strategy. At the same time, they may require a more in-depth analysis of a given parameter. For example, the increase in the duration of the production process causes both delays in delivering the product to the customer and affects the increased wear and tear of machinery/equipment or the need to pay compensation to employees. Repeated allocation of overtime to employees will have an impact on lowering the motivation of employees to work, the overtiredness of employees, thus consequently lowering the work efficiency or increasing the number of mistakes made by employees.

The increased exploitation of machinery leads to faster deterioration of its components, which means the implementation of more frequent repairs and maintenance and the need to stop production in a given production area. It is also possible for more frequent failures in the system to occur, which can be particularly severe when they occur at the moment of realization of the production process just after lifting the limitation of power consumption— at the moment of increased realization of the operation. These characteristics are difficult to introduce to the simulation model, focusing on the analysis of the selected production area. These will be taken into account as additional quantities analyzed in the given treatment strategies. The analyzed parameters include the amount of employee overtime, energy consumption by other resources necessary for the implementation of the production process (lighting of workspaces, social rooms, corridors, ventilation/space heating) as well as increased operation of machinery/equipment. In summary, it is necessary to use practical data from the enterprise to determine recommendations. In terms of production management, this is primarily an assessment of whether it is possible to implement the production process in a manner deviating from the established ones. This applies to

changing the order of some technological operations, the implementation of only selected technological operations, a different order of starting and ending operations, the possibility of extending the operation of machinery, and the availability of an adequate number of workers, etc. The above information should be collected, analyzed, and evaluated by an authorized production manager. Alternatively, it can be collected in the form of a procedure to be followed in the production process in the case of a limitation of available capacity. The procedure will have a specific form for each company. As far as enterprise control is concerned, the choice of the recommended strategy should first be assessed based on the simulation results by comparing the values of the determined process parameters. On this basis, information on the cost of implementing the selected strategy and the possible lost benefits in the case of its abandonment can be determined. As a result, a decision should be made on whether the selected strategy will be implemented.
