microprocessor design team assignment problem with a new multistage stochastic/Brownian motion model

The Microprocessor Design Team Assignment Problem models the microprocessor design efforts of Intel Corporation over a 29-year period from 1972 until 2001. The basic model is a Erlang queuing system based probability model of the individual programming-design team daily operations. After extensive research the Erlang Loss/Delay Blocked Multiserver Model is utilized throughout the dissertation The Erlang loss-delay model takes into account the Key Man Constraint for team leaders and programming team personnel. The Microprocessor Design Team Assignment Problem Case Study and massive research effort, into Intel Corporations design efforts, is complicated by modeling a major programming-design team operation without any current data or assistance from Intel Corporation. However much of the lack of assistance and data was obtained by utilizing a critical managerial design team decomposition which answered most major questions about Intels lack of adequate personnel and overutilization of team leaders and asst. team leaders throughout the 48 months of most major design projects. The study-dissertation concludes that Intels and Hewlett Packards current positions in the computer industry are relatively secure because of extremely high entry level costs exceeding $850,000,000.00 million dollars. Many individual issues about programming-design team operations are analyzed in a great amount of detail. This is the first time that much of this design-programming team material and information is being made public for future research and continuing improvement upon large scale project managerial methods and techniques. The basic design-programming team effort is also modeled with Erlang probability models and stochastic Riccati differential equations. This modeling effort is discussed in great detail in chapter 5 and Appendix Alpha. It is believed that this fundamental research leads the way for more advanced efforts in manufacturing systems and possibly mechatronics for further models utilizing strong Markov properties. This research effort substantially advances the basic research and knowledge of Partially Observable Markov Decision Processes and Strong Brownian Motion with the basic unit being strong Markov properties.