Our team has broad expertise in industrial process development, control and optimization, including methodologies like six-sigma and LEAN. With a solid foundation in statistical process control, a clear understanding of process variability, and experience in successful physical and statistical model building, we are well equipped to ask the right questions, to work with you to develop a deep understanding of your process within a firm quantitative framework, and to deliver quantifiable results.
We believe that almost all industrial processes will benefit from a systematic approach based on quantitative, model-based improvement and control; benefits that take the form of increased consistency, reduced scrap, improved yields and hence reduced costs and operational, material and energy efficiencies.
The team has specific expertise in statistically sound data collection and analysis, exploratory data analysis, data presentation and visualization, development and application of statistical models, as well as numerical, computational modelling of physical processes. Some of the tools we have used include the standard statistical packages, the R environment for statistical computing and graphics, and we have experience with developing numerical models in C, Fortran and Python. We do not aim to compete with six-sigma, LEAN, conventional SPC, or process mapping methodologies. Alongside these we propose a deep, fundamental understanding of the process itself from first principles. Our approach is thus complementary, providing you with an explicit, documented model for understanding your process and managing your process knowledge.