FCE Frankfurt Consulting Engineers GmbH (FCE) is a mathematically oriented engineering company with is administrative office in Floersheim am Main, Germany and its main office in the Gateway Gardens sector of Frankfurt Rhein-Main Airport. FCE was founded in 2004 as a German Limited Liability Company building on twelve years of experience of its founder, Wolfgang Mergenthaler, as a self-employed engineer and 20 years as an employee in the automotive industry, both in Germany and the United States. FCE has substantial experience in the industrial application of Mathematical Statistics, Mathematical Optimization, Pattern Recognition etc. From the very beginning on, one of the predominant areas of research was the analysis of multivariate stochastic sensor time series and notably the task of predicting the time series for a finite planning horizon. If the sensor readings are accompanied by certain significant events worth forecasting, then the above task can be narrowed down to predicting exactly those events. Another area of activity of FCE has been for many years the task of mathematically modeling certain aspects of production planning, mainly in the context of designing optimal production sequences, for instance in the automotive world. Last but not least, the entire field of Multivariate Statistics with all its ramifications such as parameter estimation, non-linear regression, multidimensional response surfaces etc. are at the core of FCE’s professional interest.
FCE’s main mission is the application of state-of-the-art Computational Mathematics and Computer Science to the solution of industrial problems. It has been proven on many occasions throughout the history of industrialization that Mathematics is an indispensable tool in the engineering domain. Only lately has this observation been carried over to the production and manufacturing world as well. As an example think of the Travelling Salesman Problem (TSP) as the modeling backbone in many sequencing and scheduling operations.
FCE’s future work will be strongly influenced by our general stream of research activities in the fields of Pattern Recognition and Machine Learning and the needs of industry, mainly our long-time partners in the automotive, aviation and power industry. Another promising area of industrial data analysis arises from within the Naval Industry. As an example, one may think of the engine of a container vessel generating large streams of signal data containing important information about fuel efficiency, emissions, machine vibrations etc. The ship operator may be interested in the relationship between ambient conditions and control variables on one hand and response variables such as fuel efficiency on the other hand. State-of-the -art nonlinear regression and data visualization techniques will enable the operator to understand how his engine works and to find optimal operating conditions under an unlimited set of operating constraints. The development of the Internet of Things (IoT) is one of the most exciting industrial opportunities at the beginning of the 21st century. Remote efficiency monitoring of moving or non-moving assets may become rather sooner than later a central task of an IoT service provider.