The systematic development of new products and processes relies upon the extensive experimentation with simulation and optimization models. Integration between stages is currently manual as resources are heterogeneous (experimental databases, PDFs, computer models, property and cost data, software, technical reports, and images) and widely distributed (separate or distant R&D groups sharing complementary or similar knowledge and expertise). Grids and hyper-infrastructure environments offer particularly attractive technologies with a potential to enable integrated applications and the design of distributed experiments in industrial environments. The paper addresses the design of synthesis experiments in hyper-infrastructure clusters that support GT4.0. The experiments are designed around homogeneous sections of the Markov chains and are distributed over using advanced middleware and upperware (Superscalar and Gridway). The implementation enables the visualization of results and the analysis of solutions.