An Interview with Dr. Servio Butkewitsch-Chose of the University of Pittsburgh. Smart Manufacturing delivers many opportunities. Optimization is one of those new opportunities, with minimized configuration and effort because of the new CESMII Innovation Platform. Consider Digital Twins as a solution for testing your plans prior to an actual production run. A Smart Manufacturing architecture delivers a level of flexibility that has never before been available. Optimization can involve constraints to input or output variables, to identify other variables that will lead to your desired outcome. Calculations can be very complex, and will likely not be solvable, but iteration of the model will deliver the results or directions that out variables should move in. Subject matter experts can assist by explaining known constraints for the model. While all this knowledge has been available and in known, what has changed now, is that Smart Manufacturing is able to simplify the access to data for testing and tuning the models, validating that the results are in line with expectations. Smart Manufacturing brings together IT (Information Technology), OT (Operations Technology) and ET (Engineering Technology). We also discuss Systems Thinking, with a very relatable example of Transporting Passengers. There are several levels of optimization, starting with Descriptive (What Happened), Diagnostic (Why it Happened) and then advanced functions of Predictive (What may Happen) and Prescriptive (What we Want to Happen). There is a “Death Valley” Gap between the first two ad the latter two. The CESMII Platform helps to minimize that gap, through Data Contextualization. We cover a very nice Excel Example for Optimization of product cost based on purchase price, transportation, consumer demand and supply per location. This simplified example can be applied to many more complex applications in industrial automation. You will see the example of an Excel Solver process, a very powerful aspect of Microsoft Excel, in solving multi-variable problems.