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.
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.
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.
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.
The cladding leak detection shop is part of an automated line of fuel assembly production. Leak control is based on heating the fuel element groups. While warming up, defective units eject the control gas, which is detected by a leak locator. The defected group is divided into two parts. Each part is screened in the same way until the leaking fuel element is found. The model, built in AnyLogic, simulates two algorithms of leak detection shop operation.
Engineers at a world-renowned German automotive manufacturer sought a modern and optimized production line for the company’s highly successful commercial van. With over 3.4 million deliveries of the commercial vehicle from various production sites, the company wanted an optimization tool with the flexibility to apply at different plants and account for technologies such as autonomous guided vehicles (AGV). The first stage of the project realized an efficiency gain of 5% and identified further significant gains for the next stage.
The SET-Holding’s newly constructed foam concrete factory in the Oryol Region could not reach its designed capacity. The plant management blamed the poor performance on the human factor: the manufacturing technique was innovative and challenging for the factory employees. SET-Holding recruited consultants to analyze the situation and increase the production capacity. The consultants decided to build the factory’s simulation model using AnyLogic software.
One of the largest turbine manufacturers in the world had a very promising five-year portfolio of gas turbines to produce and was planning an optimistic 30% net margin. The company’s portfolio consisted of over 100 programs, made of 1000’s of projects, with each project composed of a number of phases. Relying on its good past performance, the company built their strategic competitive edge around their reliability, enabling them to offer penalties for late delivery and bonuses for early performance.
Eurystic, an Argentinian consulting company, worked on a project for a large steel manufacturer that was searching for production planning and scheduling software to optimize the production schedule and forecast the system's behavior.
NLMK Manage Steel Center is a strip steel service center in Manage, Belgium. MSC planned to implement a set of modernization activities to increase throughput by 1.5x at their facility. This case study shows how simulation modeling helped MSC to select optimal configurations for the facility and improve their productivity.