Physical Internet,conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study

The Physical Internet (PI) logistics system is an innovative logistics concept that has been gathering a lot of attention lately. This system consists of open, modular and shared containers and transit hubs to move goods globally. The purpose of this paper is to compare the performance of PI with regard to the conventional (CO) logistics system in order to quantify the advantages and disadvantages of PI from a truck and driver routing perspective with an explicit constraint on maximum return time for drivers. The comparison presented in this work is carried out through Monte-Carlo simulation within a sequential three-phase optimisation framework. Based on our analysis, PI reduces driving distance (and time), GHG (greenhouse gas) emissions and the social cost of truck driving. On the other hand, it increases the number of container transfers within the PI logistics centres. This insight is a contribution of the paper and reinforces the current literature on PI. The other main contribution of the paper is a validation of the claim that the number of drivers who can go back home at the end of a work day remains consistently high in PI, regardless of the traffic level.     

物联网语境下现代物流与运输包装设计

目的 本文研究物联网语境下,现代物流的发展与运输包装设计的关系以及未来运输包装设计的新特征和发展趋势。方法 通过分析研究国内外优秀销售包装和运输包装案例以及现代物流系统智能化技术,用互联网设计思维,思考新语境下现代物流行业的发展趋势、对现代包装设计在空间、结构、材料等方面的创新应用,以及运输包装设计的现状和未来发展趋势。结果 为了满足现代物流智能化要求,现代运输包装不仅日益趋向智能化与标准化,而且未来运输包装在结构设计、智能技术与环境保护和资源再生领域也有了新特征。结论 在物联网语境下,设计师应该熟悉运输包装设计新范式,更加注重现代包装设计与现代物流运输的关系,只有在现代运输包装设计发展过程中融合求变,包装创新设计和物流生态才能更加智能可持续。     

Exploring self-organization and self-adaption for smart manufacturing complex networks

Trends toward the globalization of the manufacturing industry and the increasing demands for small-batch, short-cycle, and highly customized products result in complexities and fluctuations in both external and internal manufacturing environments, which poses great challenges to manufacturing enterprises. Fortunately, recent advances in the Industrial Internet of Things (IIoT) and the widespread use of embedded processors and sensors in factories enable collecting real-time manufacturing status data and building cyber–physical systems for smart, flexible, and resilient manufacturing systems. In this context, this paper investigates the mechanisms and methodology of self-organization and self-adaption to tackle exceptions and disturbances in discrete manufacturing processes. Specifically, a general model of smart manufacturing complex networks is constructed using scale-free networks to interconnect heterogeneous manufacturing resources represented by network vertices at multiple levels. Moreover, the capabilities of physical manufacturing resources are encapsulated into virtual manufacturing services using cloud technology, which can be added to or removed from the networks in a plug-and-play manner. Materials, information, and financial assets are passed through interactive links across the networks. Subsequently, analytical target cascading is used to formulate the processes of self-organizing optimal configuration and self-adaptive collaborative control for multilevel key manufacturing resources while particle swarm optimization is used to solve local problems on network vertices. Consequently, an industrial case based on a Chinese engine factory demonstrates the feasibility and efficiency of the proposed model and method in handling typical exceptions. The simulation results show that the proposed mechanism and method outperform the event-triggered rescheduling method, reducing manufacturing cost, manufacturing time, waiting time, and energy consumption, with reasonable computational time. This work potentially enables managers and practitioners to implement active perception, active response, self-organization, and self-adaption solutions in discrete manufacturing enterprises.     

The SDGs and the sustainability assessment of private-sector projects: theoretical conceptualisation and comparison with current practice using the case study of the Asian Development Bank

The Sustainable Development Goals (SDGs) are receiving increasing attention in the private sector; however ex post assessment of operational sustainability performance remains well in advance of ex ante sustainability assessment of capital projects. It is also not yet commonplace to structure emergent forms of sustainability assessment to support the SDGs explicitly. This article reviews theoretical frameworks that aim to conceptualise sustainability assessment, and then explores the potential to develop SDG-focussed forms for use at the project-level. The extent of enhancement needed to current practice is illustrated using the case study of the Asian Development Bank. This analysis reveals that sustainability is being presented as a goal of project-level assessment and there has been progress towards delivering on this by, in particular, extending the thematic coverage. Amongst the key challenges remaining are how to address trade-offs (typically unavoidable for projects) and how to connect the SDGs, set at a global level, to the local-level where projects are considered. These findings, which reveal the gap between theory and practice, can inform efforts to develop SDG-focussed sustainability assessment.