The global economy is currently in a situation of complete and prolonged uncertainty. This economic condition has a significant impact on any enterprise, on any business in principle, forcing companies to take decisive action. Often, however, organizations are not prepared to take any serious steps due to the lack of tools that could help them deal with the difficulties that arise. This makes them mere observers of the rapidly changing reality, which can cause irreparable damage to their operational and strategic activities.
Of course, it is worth bearing in mind that the risks faced by companies are absolutely unprecedented both in their scale and their level of impact. It is impossible to list all the risks, so in this article we propose to consider the following ones. Among others, suppliers refuse to sign new contracts or fulfill existing commitments, which leads to a breakdown in existing supply chains. There are also problems with equipment maintenance due to lack of spare parts or qualified contractors. Many companies are unable to meet delivery deadlines because they themselves experience delays or cancellations of deliveries.
When it comes to modernization, automation and robotization projects, many of them are suspended, frozen or, at the very least, their acceptance and execution are severely delayed. A number of organizations are losing new or existing customers due to unavailability of the necessary components and services on the market. Many industrial enterprises face the issue of a critical decrease in demand for their products and the need to switch to the production of new ones.
It is absolutely necessary to level out the considered risks as far as possible, but appropriate tools are needed for this purpose. When selecting tools, it is worth taking into account the efficiency criteria relevant in the current situation. The first criterion is the speed that the tool can provide to make a decision. The sooner management can decide to act, the greater value of the tool, because otherwise the decision may be outdated, and the analysis will have to be repeated.
It is also possible to make a drastically wrong decision quickly, so the second criterion could be the accuracy or correctness that the tool provides. Accuracy means that we have a complete, comprehensive picture of the current and target state, supported by production analytics. The greater the accuracy, the fewer changes will need to be made in the future. However, changes are more likely to be made – so another criteria for the right tool is to take the ability to make operational changes to the project.
A digital twin of production (hereafter referred to as a DTP) meets all of the above criteria. Digital twin of production is a virtual prototype of a really existing/planned production cell, area, workshop, or the entire production in general. DTP allows not only to visually see the production, but also to conduct 3D simulation and testing of optimization hypotheses, obtaining statistics for each requested parameter.
The value of the DTP is determined by a number of factors, which are based on the basic properties of this tool. Firstly, a digital twin of existing production can be created quickly to assess the current state, making it possible to estimate a starting point from which to work. Secondly, the DTP allows changes to the project in the shortest possible time, which means that the adaptation of technological processes to the new reality will occur more organically and in a timely manner. These features will reduce such risks as the risk of losing customers and disruption of supplies, because they allow the organization to immediately restructure its processes and maintain the required level of production.
DTP is also effective in the reorganization of modernization plans, because it can provide comprehensive analytical material in a short period of time to make the correct decision.
Let’s look at an example of how a modernization project can be changed quickly with the help of the DTP.
Figure 1 shows the robotic cell as originally planned. The cell consisted of two machining machines and a Fanuc industrial robot. An incoming conveyor belt brought parts to the robot for machining, and the robot placed each part into one machine and then into the other. Once the machines were finished, the robot would pick up the part and place it on the conveyor, which would then direct it to the next process step.
Figure 1
However, the situation was such that the Fanuc robot was unavailable due to supply problems. In this case, the plant management decided to swap the robot for a similar one from another manufacturer. After working through several options, the choice was made on the industrial manipulator of the KUKA brand, which showed the same performance and was on the market (see Figure 2)
Figure 2
This data was obtained through 3D simulated testing of each selected robot model, meaning that the user only changed the robot in the DTP and ran the analysis on the required production parameters. This analysis took about 2 hours in total – in 2 hours management got a balanced answer to a problem that could have derailed the entire project.
The ability to optimize processes remains an important feature of the DTP. Process optimization in a period of economic growth is usually aimed at increasing productivity, expanding automation and robotization initiatives, etc. In a crisis situation, companies are more likely to seek to reduce costs and, at present, to reorient themselves to new products due to the impossibility or unprofitability of producing previously sought-after products. It may also often be necessary to switch to manual labor because of equipment problems.
Consider how a previous manufacturing process that was implemented as a modernization project can be transformed and optimized (see Figure 3).
Figure 3
During the physical deployment of the equipment, it turned out that one of the parts suppliers had withdrawn its commitments. This resulted in one of the machines being unable to operate. However, this machine was originally intended to replace manual labor. There was no other choice, so these operations were again assigned to workers. The process began to look like the following: first the worker did his part of the machining, then the workpiece was fed by a conveyor belt to the robotic station, where the robot put it in the machine and then set it on the conveyor belt, which directed the part to packaging.
With the DTP, it was possible to further optimize this process by analyzing, using 3D simulation testing, what number of workers would give, on the one hand, the greatest productivity and, on the other hand, not create a bottleneck at the entrance to the machining center. One, two and three workers were analyzed, and two workers performing the same operation in parallel proved to be the best number. The final view of the process is shown in Figure 3.
It is important to note that the visual aspect of the DTP is able to provide significant support for the work of organizations both within the company and between them. The visual part of the DTP allows you to simply, quickly and clearly convey the idea of the solution to employees, management, contractors, customers and other stakeholders, as it makes it possible to show not only a static, but also a dynamic representation of any processes, the interaction of equipment with each other and with people. It can also be used to educate employees/customers about the changes that are being made to the processes and production landscape.
Thus, we can conclude that the CDP is a tool that can be useful for responding quickly and efficiently to the changes that have already occurred or are expected to occur in the industries.
