第五段階の新たな社会であるSociety 5.0 の実現に向けては，データをめぐるプライバシーや サイバーセキュリティや越境移転，プラットフォーマーをめぐる競争政策や課税政策，さらには米中新 冷戦等の課題が存在する．新型コロナウィルス感染症が蔓延するなか，新しい時代への移行の模索が 今，強く求められている.

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The world is facing serious challenges on resource depletion and environmental degradation. There needs to be a balance urgently between economic development and environmental sustainability. A novel outcome-selling — as opposed to product-selling — economic model has been proposed in the World Economic Forum where the focus of the business is to be shifted from products delivering the outcome to the intended outcome directly. Such a model, supported by advanced digital technologies, is not only demand-driven and customer-centered but also more environmentally sustainable. This paper explores the key technology and business enablers of this model, followed by an illustration of a pilot study incorporating sharing economy. Finally, additional potential impacts of outcome economy on economy, society and environment are presented.

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The development of intelligent manufacturing play an important role in the transformation and upgrading of Chinaʼs manufacturing industry. It can promote the deep integration of informatization and industrialization, and also drive the innovation in the whole manufacturing value chain. Firstly, in this paper, the driving factors of Intelligent Manufacturing are explored. Secondly, the current development status of Intelligent Manufacturing in China are discussed. Although intelligent manufacturing started late and its foundation is weak, it has also made some progress. Finally, according to the current situation and relevant policy in China, the development trend of Intelligent Manufacturing is described.

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In this paper, we focus on scheduling by simulation in a cyber-physical system (CPS). We propose measures to utilize appropriate simulations for a variety of purposes, from the schedule planning level in the production system to the material procurement and sales logistics planning level in the business system. Running the simulation model as a digital twin at all times to monitor real-world conditions. When an unplanned problem occurs, the system switches from real-time monitoring to future prediction, which is the main purpose of the simulation, and feeds back the experimental results of the model to the field. It can be said that the way to utilize system simulation as an everyday tool has opened up.

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Digital twin (DT) is not only a concept, but also a simulation tool that can be expected to construct models of smart factories and autonomous production by utilizing cyber-physical systems (CPS) concept. Simulation is used to reproduce and monitor the manufacturing site and to feed back the results of prediction and optimization by modeling the real world. However, previous studies so far have often been limited to explain the concept of the DT, and the associated discussion of the DT implementation is not enough from the practical standpoint. In this study, after surveying the previous researches, we clarify the problems remaining in the DT implementation, and then, propose a data input scheme for the synchronization /monitoring mode in a DT. Then, a framework of cooperation between the monitoring mode and the evaluation-experiment mode, which is an important issue in constructing a DT, is also proposed. By applying them to case studies of DT-oriented simulation models for a physical factory model, the proposed scheme and framework are verified.

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With the evolution and development of the IoT (Internet of Things) and AI (Artificial Intelligence) technology, new value creation has been achieved by connecting various people, things, organizations and spaces to the network. Among them, as the international logistics hub, digital transformation of the seaport has become Mid- to Long-Term Policy for expecting to create new value and improving national competitiveness. In this study, we surveyed the national seaport policies in the IoT environment and clarified the development generations and characteristics of the seaport digital transformation. Then, based on the materials and information flow at the container terminal, the mechanism of data collection in the terminal operating system is proposed. In addition, historical log file is used to build a simulation model for representing the yard operation for evaluating performance. In addition, limitations of current data collection processing, and simulation modeling method is clarified.

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This special issue, “Industry 4.0”, aims to build an autonomous decentralized digital network society. BTSM (Business Transaction State Machine) is expected to play an important role as its technical infrastructure. It could be used as a mechanism to enhance the safety and reliability of business transactions shared among the members in a decentralized network. The current model for designing the BTSM has the limitation that it can’t adequately identify the business event necessary to complete a transaction. Although a LAP-based model has been proposed to overcome this limitation, this model also occurs another new limitation. It can’t properly represent a transaction scenario starting from a sales proposal or counteroffer. Therefore, this paper proposes an amplified model which could overcome them. It, especially, can’t properly represent a transaction scenario starting from a sales proposal or counteroffer. This paper proposes an amplified model which could overcome them.

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