The Airbus Group joined the European Union ARUM (Adaptive Production Management) project, which is focused on creating an IT solution for risk reduction, decision-making, and planning during new product ramp-ups. The project is aimed mainly at aircraft and shipbuilding industries. Simulation was chosen as a part of the ARUM solution, because it would allow the participants to reproduce the real production facility experience.
Consolidated Contractors Company (CCC) is the largest construction company in the Middle East and ranks #18 internationally. CCC has offices and projects in over 40 countries, and a workforce of more than 130,000 employees. Just after contract signature of a site preparation project (earthmoving scope of approximately four million cubic meters), the client and local authorities placed new, more restrictive constraints on the operation. The newly placed constraints essentially meant that the project schedule will be severely impacted and with it the total cost to complete.
YPF is the largest oil and gas company in Argentina. YPF was aiming to reduce its costs associated with oil wells’ maintenance downtime and equipment breakdown. The analysis showed that the root cause of inefficiencies was the lack of a robust maintenance scheduling process. YPF approached Simcastia to develop a scheduling tool to streamline asset management at all YPF facilities.
The world’s largest companies use data analytics to increase their revenue and keep up with the changing business world. But how does data science relate to simulation modeling, and what are the cases for the implementation of this interaction, primarily concerning value for the business? The United Services Automobile Association (USAA), a Fortune 500 group of companies, has answered these questions with real-life solutions.
The European Institute for Energy Research constructed a digital twin that can be compared with the real world. The simulation investigated how the proportion of locally generated and used energy can be increased by intelligently controlling the generation and consumption of electricity and heat.
CSX is a US railroad company that operates about 21,000 route miles (34,000 km). AnyLogic allows the railroad industry users to simulate line-of-road, terminal, and yard problems. The following three projects, completed by CSX in 2014, covered a variety of tasks that were solved using AnyLogic software.
Fannie Mae (The Federal National Mortgage Association) is a US government-sponsored enterprise that operates in the secondary mortgage market. It purchases and guarantees mortgages from lenders, such as banks and other financial institutions, securitizes them, and then sells them back into the secondary mortgage market as mortgage-backed securities. This provides market liquidity and helps stimulate activity. In 2018, Fannie Mae was ranked 21st on the Fortune 500.
The researchers at Ruhr University Bochum analyzed various logistics processes of mechanized tunneling. The main purpose was to reduce the construction time. An optimized simulation model helped achieve more robust planning of logistics and maintenance processes that could also consider uncertainties.
European Institute for Energy Research (EIFER) is an organization that deals with the decentralization of energy systems on various territories, and promotes renewable energy sources. Localized energy systems, unlike classical ones, do not need to transmit electricity over long distances, as they are located close to the load they serve. Being less hierarchical, they provide the prospects of power storage, renewable energy inclusions, and demand forecasting. EIFER engineers chose AnyLogic simulation modeling to find out how the localized systems should be planned and operated.
The cost of one hour of down time of a tunnel boring machine is usually high and project managers have to do their best to avoid unnecessary delays in construction. The aim of the simulation project, which was carried out at Ruhr University Bochum in Germany, was to create a simulation model that would be capable of determining the bottlenecks in tunnel building processes in order to minimize the possible monetary losses.