Design of Manufacturing Systems Based on Digital Shadow and Robust Engineering

In the era of digital transformation, industry is facing multiple challenges due to the need for implementation of the Industry 4.0 standards, as well as the volatility of customer demands. The latter has created the need for the design and operation of more complex manufacturing systems and networks. A case study derived from Process Industries (PIs) is adopted in this research work in order to design a framework for flexible design of production lines, automation of quality control points, and improvement of the performance of the manufacturing system. Therefore, a Digital Shadow of a production line is developed to collect, analyze and identify potential issues (bottlenecks). An edge computing system for reliable and low-latency communications is also implemented. The digital model is validated using statistical Design Of Experiments (DOE) and ANalysis Of VAriance (ANOVA). For the assessment of what-if scenarios, the Digital Shadow model will be used in order to evaluate and find the desired solution. Ultimately, the goal of this research work is to improve the design and performance of the industry's production section, as well as to increase the production rate and the product mix.

Automated summary

This research adopts a case study from Process Industries to design a flexible production line framework, automate quality control points, and improve manufacturing system performance. A digital shadow of a production line is developed to collect, analyze, and identify potential issues, and an edge computing system is implemented for reliable and low-latency communications. The digital model is validated using statistical Design of Experiments and Analysis of Variance. The goal of this research is to improve the design and performance of the industry's production section and increase production rate and product mix.