No abstract

With the rapid development of mobile and wireless networking technologies, data has become more ubiquitous and the IoT (Internet of Things) is attracting much attention due to high expectations for enabling innovative service, efficiency, and productivity improvement. In next-generation manufacturing, the digital twin (DT) has been proposed as a new concept and simulation tool for collecting and synchronizing real-world information in real time in cyber space to cope with the challenges of smart factories. Although the DT is considered a challenging technology, it is still at the conceptual stage and only a few studies have specifically discussed methods for its construction and implementation. In this study, we first explain the concept of DT and important issues involved in developing it within an IoT-aided manufacturing environment. Then, we propose a DT construction framework and scheme for inputting data derived from the IoT into a simulation model. Finally, we describe how we verify the effectiveness of the proposed framework and scheme, by constructing a DT-oriented simulation model for an IoT-aided manufacturing system.

Summary An exponential contrast stretching (ECS) technique is developed to reduce the charging effects on scanning electron microscope images. Compared to some of the conventional histogram equalization methods, such as bi‐histogram equalization and recursive mean‐separate histogram equalization, the proposed ECS method yields better image compensation. Diode sample chips with insulating and conductive surfaces are used as test samples to evaluate the efficiency of the developed algorithm. The algorithm is implemented in software with a frame grabber card, forming the front‐end video capture element.

Companies can suffer significant losses as a result of unanticipated business disruptions caused by natural disasters or outbreaks of disease. In order to restore the organization's critical functions and minimize the impacts of a disruption, it is important to establish business continuity planning and recovery planning. First the risks in the external environment surrounding the companies and business continuity planning were described. Then, how the computer-based simulation technique could be utilized to establish the business continuity planning was examined under a pandemic environment. In this study, an approach of examining the operation rates and the plant-utilization rates was proposed for a factory, by applying simulation. The proposed approach was applied to a real manufacturer especially under a pandemic flu environment in order to confirm its effectiveness.

No abstract