In 2012, a railway operator decided to create a strategic railway network to embrace the need to increase the scale and volume of cargo traffic. This network was comprised of three railway ports and six transport and logistics terminals. The network was aimed at enhancing the efficiency of cargo transportation. The first stage of launch would increase cargo traffic by 100-120 million tons per year.
Engineering Ingegneria Informatica is an international specialist in the field of digital system integration. The company has more than 11,000 employees in more than 50 offices around the world. One of its flagship projects is an ecosystem of platforms that enable other technologies to interact with each other – exchanging value, digitizing processes, developing digital services, and creating value for users, especially through the leverage of 8D.
A manufacturing performance evaluation tool for optimizing flexible manufacturing system design and operation. Case study of how MCM worked with Engineering Group to capture systems expertise for a powerful manufacturing performance evaluation tool.
The largest CIS rail car building facility, Tver Carriage Works, needed to choose the best passenger rail car concept for a city train. The plant needed to compare passenger entrance/exit times during peak loads for concepts that had different door amounts and widths, and then choose the best variant. They contracted ITS Consulting to perform this task. The consultants found pedestrian simulation modeling to be the best possible instrument to provide a solution.
Distributors, such as retailers, are the intermediaries between producers of products and other entities in the distribution supply chain. They often encounter problems with supply chain configurations and fleet setups. To analyse and optimize this interaction for one of the largest book distributors, engineers from Goldratt Research Labs used simulation and vehicle routing optimization. This case study will provide an overview as to how this was performed.
A biotech startup, providing experimental personalized medical treatment, wanted to conduct data-driven pharmaceutical manufacturing simulation to optimize decision-making processes when delivering new products. These products were undergoing clinical trials, and the manufacturing processes remained unclear while US Food and Drug Administration (FDA) approval was pending. The company was short of resources, but it was crucial to produce its products as fast as possible and without failures.
RUSCON is one of the major container shipping companies in the CIS region. The company needed a container yard planning solution to modernize one of the rail container terminal and determine maximum capacity of the whole facility and its components. It sought the expertise of container yard simulation specialists from Dilibrium Consulting Company to model terminal components including the container yard, transshipment equipment, and rail infrastructure.
Centrotherm Photovoltaics AG is a global supplier of technology and equipment for the photovoltaics, semiconductor, and microelectronics industries. The company needed to identify the best-automated production line and factory configuration to minimize costs and maximize throughput and reliability.
A public electricity company in France needed to optimize routes to ensure that all orders were delivered by electric trucks on time. They decided to develop a delivery route optimization model using simulation software, visualize the logistics network, and collect statistics. To reflect the real system, the team had to consider trucks’ battery capacity, chargers’ electric power, and many other constraints.
Bryden Wood, with Tata Steel and the Advanced Manufacturing Research Centre, developed a simulation model of the automated factory system for truss production planning and scheduling. Using simulation and optimization techniques, Bryden Wood tested different scenarios to increase the factory's throughput. They included and excluded process times and changed the production schedule, which impacted the sizing of different factory areas.