The design of complex systems, including manufacturing systems, factories, supply chains and business processes requires in-depth understanding of the nature of the system itself, the environment and context in which it operates as well as the behaviour, performance and capability of the resources and building blocks of this system and the architecture and layout of its design and implementation. An important task for engineers is to model these systems so as to optimize the design in the first instance and to analyse and improve the ongoing performance of the system. The objective thus is to create, what is called, a "Digital Twin" of the real system or process. This is an invaluable tool for designing, operating and improving real systems and it is increasingly used as a cornerstone in Industry 4.0. Few decisions are made directly without testing, experimenting and optimising strategic as well as design and operational alternatives and options.
Manufacturing engineers routinely solve complex problems involving resource allocation, process and supply chain optimization, work and activity flow and balancing, machine capacity analysis and the planning of capital expenditure. Since simulation (particularly discrete event simulation) is increasingly used in industry, this course will place heavy emphasis on simulation and the statistical analysis of results. Simulation software used is Rockwell Arena ®.
One of the important aims of the course is to develop the ability to analyse real world systems by understanding the nature of the underlying process, the ability to abstract its behaviour, and to select appropriate quantitative techniques for modelling this behaviour with the goal of improving it.
