One of Tata Steel's steel manufacturing units showed potential for increasing the overall unit throughput by optimizing the internal logistics systems. The opportunity was in improving crane and ladle handling by introducing optimized process flows and testing different layout configurations.
Automotive industry leaders use autonomous mobile robots (AMR) in their production facilities to improve productivity. In this case study, Tesla Material Flow Engineer and former BMW Group PhD Student and AMR researcher, Maximilian Selmair, describes standard industry practice when deploying large-scale transporter fleets and demonstrates how AnyLogic cloud-based simulation helps develop optimal task allocation algorithms.
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.
Semiconductor demand is unstable, highly dependent on innovation cycles, and due to its volatility, the semiconductor supply chain is prone to the bullwhip effect. These challenges were compounded by supply chain shortages and the COVID crisis. This case study shows how supply chain engineers at Infineon optimized their supply chain and mitigated the bullwhip effect using simulation modeling.
GSK determined a possible 20% lower capital expenditure for the renewal of its biopharmaceutical manufacturing facility in Parma, Italy, by using simulation modeling. For analysis, planning, and decision support on the project, GSK worked with the award-winning tech application company Decision Lab.
Leading global steel producer, Tata Steel, optimized quicklime production operations using simulation. The analysis of five production scenarios led to a reduction in power consumption and operating costs at a quicklime production facility. Learn how they accomplished it in this case study.
The Model Group, in their factory in Weinfelden, Switzerland, was producing about 200 jobs a day. The job shop scheduling was done manually, and this was found to be inefficient. So, they needed to find a way to implement different job shop scheduling techniques and compare and validate them. ProSim combined simulation modeling and AI to develop a solution that would create accurate schedules and therefore reduce bottlenecks.
CNH Industrial is a global leader in capital goods. It is financially controlled by the Italian investment company Exor and is comprised of 12 brands, including Case, New Holland, and Iveco. Through its brands, CNHI designs, produces, and sells a wide range of agricultural, industrial, and commercial vehicles and powertrains. CNH Industrial identified maintenance processes as a promising area to start applying new Industry 4.0 technologies. In the automotive and related industries, downtime costs can be large. As such, improving maintenance in order to reduce downtime can deliver...
Intel factories used a particular type of equipment that often broke down, which caused capacity constraints. These expensive parts were used in critical factory operations, and the repairs took significant time, so it was necessary to have extra spare parts on hand to avoid downtimes. Broken parts caused constraints at some of the factories while other factories over purchased spares.
In 2012, GE opened a new battery manufacturing plant in conjunction with the launch of an innovative energy storage business. GE’s exciting opportunity brought on many new challenges, such as increasing production throughput and yield under evolving processes and uncertainties, and reducing manufacturing costs in order to gain market share. The GE Global Research Center sought out a powerful and flexible tool to analyze, not just the specific process, but the manufacturing system as a whole.