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In addition to functionalities, business process management (BPM) involves several key indicators such as openness, security, flexibility, and scalability. Optimizing system performance is becoming a great challenge for an ever-increasing large-scale distributed application system in the digital economy on the Internet of Things (IoT) era. In a centralized BPM, many indicators, such as security and openness, or cost and flexibility, are conflicting with each other. For example, inviting new partners across enterprises, domains, and regions to form a service workflow exposes new risks and needs additional security mechanisms for scrutiny; enhancing the flexibility of business workflow compositions increases the cost of security assurance. Blockchain technology (BCT) has thrown the light on the development of vital solutions to various BPM problems. BCT has to be integrated with other BPM system components that often involve IoT devices to implement specified functionalities related to the application. Currently, the potentials of using BCT have been explored although still at an early stage. In this paper, the states of the art are presented to identify emerging research topics, challenges, and promising applications in integrating BCT into the development of BPM.

Internet of Things (IoT) refers to networks with billions of physical devices for collecting, sharing and utilizing data in the virtual world. Most of IoT applications centralize security assurance in creating, authenticating, transferring, or delating system components. However, the centralization exposes its limitations to meet security needs of a rapidly-growing number of things world-widely. How to scale up the applications with assured security becomes a critical challenge. Blockchain Technology (BCT) is a promising solution to provide security and protect privacy in a large scale; especially, smart contracts offer opportunities to improve the reliability of IoT applications. Smart contracts establish trusts for both of data and executed processes. Recently, many literature surveys and positioning articles have been published on the integration of BCT with IoT, but they are limited to superficial discussions of technical potentials, and very few of them have a thorough exploration of the challenges in developing BCT for IoT at technical levels. This paper uses the system design approach to scrutinize the state of the art of study on BCT-based applications and clarify critical research areas of enabling BCT for security assurance: (i) the relations of BCT and IoT are modelled and discussed; (ii) the needs of eliminating threats in IoTbased applications are defined as functional requirements (FRs), existing works on enabling technologies of BCT are defined as the physical solutions (PSs); (iii) the mappings between FRs and PSs are established to identify the limitations and the critical areas for the applications of BCT in large-scale distributed environment.

A system paradigm is an abstract representation of system; it includes system architecture used to determine the types and numbers of components and their relations in the system. The design of system paradigm relies on customers’ requirements and the characteristics of the manufacturing environment. Many system paradigms and design guidelines have been proposed for a variety of customers’ needs including functions, cost, quality, personalization, and lead time of products. However, the consideration of sustainability becomes essential to today’s manufacturing systems; a new challenge is how to evolve existing paradigms to accommodate the requirements of sustainability. In contrast to ample research activities on system paradigms in past decades, recent studies on system paradigms have been restricted, partially due to unclear research directions. Limited works can be found on conceiving new manufacturing system paradigms from the perspective of sustainability; most of the related literature concerns the new requirements of sustainability. The objectives of this work are (i) to examine the requirements of manufacturing systems in a wider scope; (ii) to revisit existing paradigms to clarify their limitations and bottlenecks; and eventually (iii) to identify some research directions, which will lead to a solution of sustainable manufacturing. To achieve these objectives, firstly, a brief description of today’s manufacturing environment is provided. Secondly, the requirements of sustainability are discussed, and the relevant researches on system sustainability are surveyed. Thirdly, the reconfigurable system paradigm is focused, and the gaps between a reconfigurable manufacturing system and a sustainable manufacturing system are discussed. Finally, the future endeavors towards to the next-generation manufacturing system paradigms are discussed.

This paper aims to investigate the impact of enterprise architecture (EA) on system capabilities in dealing with changes and uncertainties in globalised business environments. Enterprise information systems are viewed as information systems to acquire, process, and utilise data in decision-making supports at all levels and domains of businesses, and Internet of things (IoT), big data analytics (BDA), and digital manufacturing (DM) are introduced as representative enabling technologies for data collection, processing, and utilisation in manufacturing applications. The historical development of manufacturing technologies is examined to understand the evolution of system paradigms. The Shannon entropy is adopted to measure the complexity of systems and illustrate the roles of EAs in managing system complexity and achieving system stability in the long term. It is our argument that existing EAs sacrifice system flexibility, resilience, and adaptability for the reduction of system complexity; note that higher adaptability is critical to make a manufacturing system successfully. New EA is proposed to maximise system capabilities for higher flexibility, resilience, and adaptability. The potentials of the proposed EA to modern manufacturing are explored to identify critical research topics with illustrative examples from an application perspective.

In this paper, recent developments on the Internet of Things (IoT) and its applications are surveyed, and the impact of newly developed Big Data (BD) on manufacturing information systems is especially discussed. Big Data analytics (BDA) has been identified as a critical technology to support data acquisition, storage, and analytics in data management systems in modern manufacturing. The purpose of the presented work is to clarify the requirements of predictive systems, and to identify research challenges and opportunities on BDA to support cloud-based information systems.