To alleviate the greenhouse gas emissions by the chemical industry, electrification has been proposed as a solution where electricity from renewable sources is used to power processes. The adoption of renewable energy is complicated by its spatial and temporal variations. To address this challenge, we investigate the potential of distributed manufacturing for electrified chemical processes installed in a microgrid. We propose a multi-scale mixed-integer linear programming model for locating modular electrified plants, renewable-based generating units, and power lines in a microgrid that includes monthly transportation and hourly scheduling decisions. We propose a K-means clustering-based aggregation disaggregation matheuristic to solve the model efficiently. The model and algorithm are tested using a case study with 20 candidate locations in Western Texas. Additionally, we define a new concept, “the Value of the Multi-scale Model”, to demonstrate the additional economic benefits of our model compared with a single-scale model.

The sputtering technique used for deposition of thin film metallized product onto base substrate material. The experiment was conducted to deposit thin film Cr-coating on glass substrate with varying process parameters. The design of experiment (DOE) was conducted to optimize the process parameters to achieve defect-free coating on glass substrate. Taguchi fractional factorial orthogonal array was used to perform DOE & ANOVA analysis. The deposition of chromium metal on glass substrate was used during the experiments conducted. The results of the experiments were evaluated against quality of the coating and the thickness. Detailed ANOVA analysis has been performed to standardize the variables.