Ensuring Success with Simulation

Simulation is an approximation of reality, the level to which it mimics reality depends on the tool and method used to implement the simulation model. The closer the simulation model mimics reality, the better its results and analysis are, while the faster the model is built and validated the greater the return on investment.

Molded Fiber Glass had a modest beginning in 1948 in Ashtabula, Ohio, near the shores of Lake Erie. Robert S. Morrison, our founder, and a handful of dedicated men and women worked diligently together to mass-produce the first commercial products using polyester resins and fiberglass reinforcements. The watershed event in the composites industry took place in 1953. MFG was chosen to produce all FRP parts for the Corvette. This led to the FRP boats, which MFG commercialized in 1955. Since those early days, MFG has grown substantially, sometimes with great difficulty.
 

The manufacturing environment is faced with many challenges that must be properly identified, analyzed and optimized prior to implementing any operational changes. Because of the integrated nature of manufacturing environments, each component has the ability and possibility of affecting another component within the system. Due to the high inter-connectivity of the system, special attention must be paid to possible changes and how these changes affect overall system productivity and functionality. With Simcad Pro dynamic simulation, manufacturing operations have the ability to mitigate and reduce risk with the proper planning of processes prior to the implementation of changes.

Next generation dynamic simulator operates under an entirely different paradigm than traditional static tools. The graphical interface used to build models does not generate or compile code since it interfaces directly with the multi-core simulation engine. When the simulation starts, the animation instantly displays, both in 2D and 3D , the current state of the engine. As inefficiencies develop, real time modifications can be made to model properties and constraints. These “on-the-fly” changes allow users to instantly realize potential gains and perform dynamic optimization.