Modelling, Design, and Operation ofCentralized and Decentralized Production Systems and Networks in a Highly Customer-DrivenEnvironment
Professor Dimitris MourtzisiscurrentlytheDeputy Head of theDepartment of Mechanical Engineering and Aeronautics at the University ofPatras, Greece.He is the Director of the Laboratory for Manufacturing Systems and Automation(LMS). He is an elected Fellow of the International Academy for ProductionEngineering (CIRP), and a member ofASME, IFAC and IFIP. His research interests arefocused on the field of design, planning and control of manufacturing systemsand networks, advanced manufacturing processes modelling and automation in manufacturing,flexibility and complexity in manufacturing systems. He is also involved in digitaltransformation and implementation of Industry 4.0 practices. He is a guesteditor in 7 international scientific journals. He has more than 200publications reaching a total number of unique citations that exceeds 3000.
Themass customizationparadigm,incombination with the volatility of globalized heterogeneous markets, directlyaffects industries towards realizing efficient manufacturing networkconfigurations. Modern industrial shop-floors are highly affected by theever-increasing product variety and volatile market demands introduced by thecurrently established mass customization and personalization paradigm.Moreover, The Industry 4.0 philosophy promotes the digitalization ofmanufacturing systems. This results in a transformation of the traditionalmanufacturing systems and creates new capabilities in the subjects ofmonitoring and control. To assist this shift, new modelling practices andcommunication standards should be employed. To that end, this Academic Reportaims to describe the design and operation of manufacturing networks based on amulti-objective decision-making and simulation approach. The above-mentionedapproaches are validated through a real-life case acquired, among others, fromthe CNC machine building industry. Additionally, an investigation on theperformance and viability of centralized and decentralized production networks,by discrete-event simulation models and multiple conflicting user-definedcriteria, under heavy product customization is presented. An assessment of the examinedapproaches, with respect to their responsiveness and suitability for highlycustomer-driven environments is provided, and can be used as a guideline forthe production network design. Finally, this Academic Report includes machinemonitoring techniques for the near real-time identification of machine status,in order to allow a predictive maintenance engine to diminish machine toolfailures. Moreover, an adaptive short-term scheduling mechanism is employed,using monitoring data for the refinement of production schedules based on thecurrent and future conditions of the shop-floor.