Many improvement techniques, methods, and technologies have been the driver of the development of supply chain systems. However, many managers and companies are focused only on new technologies without considering a comprehensive evaluation, and therefore lacking a real need and purpose. As a result, practitioners are often confused with regard of how to integrate improvement strategies and new technologies, as well as how to evaluate their convenience. Thus, this research aims to develop a model for the assessment for each manufacturing capability. This assessment aims to enable a continuous business transformation aligned with organizational goals; thus, a dynamic maturity assessment is chosen. Based on this, the study seeks to provide an integration model for relevant improvement strategies and new technologies that can be applied to any organization. As a result, the paper develops a sequence model, the GUVEI-Model, for the application of Industry 4.0 related technologies for continuous improvement in five different clusters. Furthermore, the research develops an evaluation scheme of optimization alternatives. Based on this conceptual development, a simulation model is built for specific use cases, such as additive manufacturing or virtual reality. The results show how the use cases along the GUVEI-Model application improve relevant indicators significantly, with the first two steps, obtaining and using data, acting as enablers of the three subsequent optimization steps that allow the virtualization, expansion, and improvement of capabilities and a higher impact on the target indicators than the first two steps. Finally, a discussion is presented about the utility of digital twin models for dynamic maturity level assessment and for simulating project improvement impacts before, during, and after their implementation.

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Vertical mobility, as a commercial service, has been strongly focused on the scheduled volume and long-distance mobility services. Thus, limiting its potential coverage, flexibility, and adaptability with high investments and centralized mobility hubs, called airports. In this context, a customized and on-demand air mobility concept providing high flexibility in location combinations and time schedules appears as an unexplored challenge for regional mobility needs. As a result, the aim of this research is to provide a generic framework for various mobility means as well as to design a holistic air mobility management concept for electric vertical mobility for profitable and sustainable operations by providing a service to society. A system dynamics simulation case study applies the conceptual model for an on-demand air mobility network of electric aircrafts in a regional area considering capacity constraints in vertiports, aircrafts, charging, and parking stations. Thus, bottlenecks and delays can be quantified by using a digital twin tool for customized scenarios. Simulation results show how an optimal maintenance management and redistribution of aircraft units improve service indicators in passenger quantity and customer order lead time as well as reduce aircraft on ground time. As a result, a digital twin air mobility network model with simulation capabilities is a key factor for successful operations.

Human behavior in supply chains is insufficiently explored. Wrong decisions by decision makers leads to insufficient behavior and lower performance not only for the decision maker, but also for other stakeholders along the supply chain. In order to study the complex decision situation, we developed a supply chain game in which we studied experimentally the decisions of different stakeholder within the chain. 121 participants took part in a web-based supply chain game. We investigated the effects of gender, personality and technical competency on the performance within the supply chain. Also, learnability and the effect of presence of point-of-sale data are investigated. Performance depended on the position within the chain and fluctuating stock levels were observed in form of the bullwhip effect. Furthermore, we found that risk taking had an impact on the performance and that the performance improved after the first round of the game.

The industrial revolutions and their impact on production systems have increased productivity and quality in manufacturing over time. Lean methods have been the driver of the development of production systems from the 1990s to the rise of the fourth industrial revolution, or Industry 4.0. However, many different approaches and methodologies have been described, applied, and discussed for achieving improvements in production systems. As a result, organizations are often confused in regard to the order, the convenience, and the outcomes intended by the different improvement strategies and techniques. This paper provides a systematic sequence of process optimization steps that can be applied to any organization. A conceptual model was built based on the systematic sequence. In addition, a simulation model was built with the goal of representing and quantifying the sequential steps of the conceptual model. The results of the simulation model show a clear improvement in quality, performance, and economic indicators, with the first two steps in the optimization sequence providing critical initial information, while the three last steps served as net contributors to a global production system improvement for demanding market scenarios. Finally, we analyzed the impacts of Industry 4.0 on production systems and developed a methodological sequence to design, select, implement, and control projects, even those that include Industry 4.0 technologies.