One of the main key enablers for a successful realization of the Physical Internet (PI) scenario is a modular box that meets all requirements of an interconnected logistical network. To address all these requirements, a holistic approach including all needs of the shipping network is integrated in the methodical development process that leads to the modular box prototypes. This paper describes the methodological engineering process for the first approach to develop a modular and multifunctional load unit to implement a first real PI scenario in the fast-moving consumer goods industry. From the identified research questions, three different layers to point out in detail arise. Following the presentation of the sizing approach, engineering design is the main part. A technical view on loading PI unit loads completes this work. Several methods are applied on these different layers, and final results are presented. By highlighting the significance of technical aspects and introducing a methodological approach, the reader can pick out additional benefit from this work to use in familiar topics from engineering design in logistics.

Manufacturing and service processes are composed of several elements: Technical, financial, logistics, information and human resources. Staff deployment and staffing is an essential problem in the human resource management domain because the structure of employees would be continuously in an optimal relationship to the jobs to be performed. This paper proposes a conceptual model for the analysis of human resource deployment processes. After a systematic literature review, it was found that algorithms are important tools for the design and control of human resource problems since a wide range of models determines an optimization problem. According to that, the main focus of this research is the modelling and analysis of human resource deployment processes of manufacturing companies using Markov-chain mathematics, also taking into account the absorbing phenomena of employees’ promotion. The main contribution of this article includes the model framework of Markov-chain simulation of a human resource deployment problem; the mathematical description of different human resource deployment strategies with subdiagonal and superdiagonal promotion matrices; the computational results of the described model with different datasets and scenarios. In the case of a given human resource strategy, the Markovian human resource deployment process of a company was analyzed. The analyzed model was the HR deployment of assembly line operators in a multinational company, including six levels of promotion. The results of the scenario analysis show that promotion and recruitment rates have a great impact on the future employees’ structure.

The trend of sharing concepts is constantly increasing, whether this may be for economic or environmental reasons. Consequently, numerous scientific research works have addressed the subject of sharing concepts. Many of these works have dealt with questions on the topic of sharing concepts itself, however, much less research has been dedicated to the question of how the sharing concept can be developed in the very first place. Thus, the purpose of this work was to systematically use systems engineering methods to develop a sharing concept for heavy-duty agricultural vehicles, while having a strong focus on technical and logistical aspects. Due to the multidisciplinary complexity of the sharing concept, a method from the field of model-based systems engineering, ARCADIA, was chosen. On ARCADIA’s top level, operational analysis was carried out to identify the key stakeholders. The next level, systems analysis, showed that the sharing model can be divided into three main processes: (1) data acquisition and preparation; (2) location planning; (3) and route planning. For these main processes, corresponding methods, algorithms and models were sought and compared against each other in the last level, logical analysis. It can be concluded that the ARCADIA method has provided a framework for evaluating the correlations and interrelationships between methods, algorithms and models at different levels to develop a sharing concept for compost turners from a technical perspective.

The Physical Internet (PI) envisions a global logistics system that integrates physical, digital and operational connections. This study aims to develop a hyperconnected logistic platform for heavy-duty machinery (HDM) in the composting industry by utilizing a systematic methodology. The proposed architecture consists of four layers: the Domain Model, the MBSE Model, the Information Sharing Model and the Agent-based Simulation Platform. The Domain Model analyzes the current situation and investigates stakeholder viewpoints, and the MBSE Model reduces complexity and describes mutual interactions between requirements and needs. The Information Sharing Model focuses on the information exchange among the main components, and the Agent-based Simulation Platform implements the proposed platform. The feasibility of the proposed architecture is demonstrated through a use case in Styria, Austria. Three simulation-based scenarios are analyzed, starting from the semi-hyperconnected approach up to the hyperconnected approach with PI vision integration. The results indicate that the hyperconnected platform is successful in serving all composting facilities, leveraging underutilized resources and promoting high-quality compost production. Thus, the platform provides support in a local, communal setting, resulting in enhancing the circular economy within the composting sector. Our efforts aim to contribute to the realization of the Physical Internet vision and promote composting to ultimately achieve a more sustainable future.

The use of automated guided vehicles (AGVs) in manufacturing systems has become particularly widespread in the latter period, thanks to the intensification of automation and to the adoption of the Industry 4.0 principle. Modern AGVs can also have greater autonomy then before, thanks to the advancement of the related technologies which further improve their applicability in numerous complex settings. In the Industry 4.0 principle, the use of predictive simulations in relation to manufacturing logistics systems also plays an important role, which applies to the modelling of the operation of AGVs as well. In light of these developments, the current paper introduces an initial model with the aim to demonstrate a possible approach for modelling the operation of freely moving AGVs in a discrete event simulation environment. The model is made with Plant Simulation, a widely applied discrete event simulation software. The presented approach opens the door for multiple future research avenues and could also serve as a basis for a further developed general model with wider utilization possibilities.