This article presents research implications related to the analysis of current trends occurring in the industry and resulting from the analysis of trends in literature. A new trend is noticeable in ...the range of computer simulations using digital twin technologies in the optimization of intralogistics processes, the implementation of which is based on Lean philosophy. This article shows the connection of Industry 4.0 with Lean in the context of Digital Twin (simulation) in the area of intralogistics. A three-step methodology of literature research was developed and described. In accordance with the adopted research methodology, research questions were indicated and a detailed list of selection criteria was developed. The research methods included brainstorming and statistical analysis. The research results are presented in three sections: the results of the trend analysis, the results of the quantitative literature research, and the results of the complementary research. The research results confirm the existence of a new trend and form the basis for formulating objectives for further research.
The efficiency of material supply for workstations using Automatic Guided Vehicles (AGVs) is largely determined by the performance of the AGV dispatching scheme. This paper proposes a new solution ...approach for the AGV dispatching problem (AGVDP) for material replenishment in a general manufacturing workshop where workstations are in a matrix layout, and where uncertainty in replenishment time of workstations and stochastic unloading efficiencies of AGVs are dynamic contextual factors. We first extend the literature proposing a mixed integer optimisation model with a delivery satisfaction soft constraint of material orders and two objectives: transportation costs and delivery time deviation. We then develop a new knowledge-guided estimation of distribution algorithm with delivery satisfaction evaluation for solving the model. Our algorithm fuses three knowledge-guided strategies to enhance optimisation capabilities at its respective execution stages. Comprehensive numerical experiments with instances built from a real-world scenario validate the proposed model and algorithm. Results demonstrate that the new algorithm outperforms three popular multi-objective evolutionary algorithms, a discrete version of a recent multi-objective particle swarm optimisation, and a multi-objective estimation of distribution algorithm. Findings of this work provide major implications for workshop management and algorithm design.
In the automotive industry, an innovative tool to support the intralogistics planning is essential. One possibility is the use of augmented reality (AR). AR can be a suitable tool for improving the ...planning of intralogistics processes. An improvement of the intralogistics planning processes can be realized by applying this technology. The application thereby dependents on the acceptance of AR. In this paper, the Technology Acceptance Model and a survey are used to verify the acceptance of AR in intralogistics planning. In addition, relevant factors are identified having an impact on the acceptance using AR in intralogistics.
In the Industry 4.0 era, the Digital Twin has become one of the most promising enabling technologies supporting material flow. Although the literature on the Digital Twin is becoming relatively well ...explored, including a certain number of review papers, the context of the Digital Twins application in internal transport systems has not been investigated so far. This paper thoroughly reviews the research on the Digital Twins applied in internal transport systems concerning major research trends within this research area and identification of future research directions. It provides clarification of various definitions related to the Digital Twin concept, including misconceptions such as a digital shadow, a digital model, and a digital mirror. Additionally, the relationships between terms such as material handling, material flow, and intralogistics in the context of internal transport systems coupled with the Digital Twin are explained. This paper’s contribution to the current state of the art of the Digital Twins is three-fold: (1) recognition of the most influential and high-impact journals, papers, and researchers; (2) identification of the major research trends related to the Digital Twins applications in internal transport systems, and (3) presentation of future research agendas in investigating Digital Twins applied for internal transport systems.
In the context of Industry 4.0, intralogistics faces an increasingly complex and dynamic environment driven by a high level of product customisation and complex manufacturing processes. One approach ...to deal with these changing conditions is the decentralised and intelligent connectivity of intralogistics systems. However, wireless connectivity presents a major challenge in the industry due to strict requirements such as safety and real-time data transmission. In this context, the fifth generation of mobile communications (5G) is a promising technology to meet the requirements of safety-critical applications. Particularly, since 5G offers the possibility of establishing private 5G networks, also referred to as standalone non-public networks. Through their isolation from public networks, private 5G networks provide exclusive coverage for private organisations offering them high intrinsic network control and data security. However, 5G is still under development and is being gradually introduced in a continuous release process. This process lacks transparency regarding the performance of 5G in individual releases, complicating the successful adoption of 5G as an industrial communication. Additionally, the evaluation of 5G against the specified target performance is insufficient due to the impact of the environment and external interfering factors on 5G in the industrial environment. Therefore, this paper aims to develop a technical decision-support framework that takes a holistic approach to evaluate the practicality of 5G for intralogistics use cases by considering two fundamental stages. The first of these analyses technical parameters and characteristics of the use case to evaluate the theoretical feasibility of 5G. The second stage investigates the application's environment, which substantially impacts the practicality of 5G, for instance, the influence of surrounding materials. Finally, a case study validates the proposed framework by means of an autonomous mobile robot. As a result, the validation proves the proposed framework's applicability and shows the practicality of the autonomous mobile robot, when integrating it into a private 5G network testbed.
During the development of intralogistics systems (ILS), heterogeneous models are created, which represent discipline-specific views, e.g., control software developed by automation engineers or ...discrete-event simulation models created by simulation engineers. These models represent discipline-specific views on the system but contain overlapping information. Thereby, keeping the information in different development models consistent is challenging and currently requires high manual effort, which highly depends on the developers’ experience. To overcome this challenge, an approach to link heterogeneous model data and identify potential information inconsistencies within and between models automatically is proposed. The concept is evaluated with a use case containing three typical inconsistencies from five representative engineering models applied in ILS development.
With visual AI processes relying on individual and context accurate training data, the existing common object datasets and randomization based synthetic data pipelines can only hardly be transferred ...or applied on specific and narrow industrial tasks. To enable visual AI applications for intralogistics processes, such as supervision or localization of objects, a domain-knowledge driven implementation for generation of context accurate synthetic training data is introduced. With this consideration of process and domain requirements in the data generation pipeline itself, a data-generator for object identification on load carriers is contributed.
Rapidly changing market conditions and global competition are leading to an increasing complexity of logistics systems and require innovative approaches with respect to the organisation and control ...of these systems. In scientific research, concepts of autonomously controlled logistics systems show a promising approach to meet the increasing requirements for flexible and efficient order processing. In this context, this work aims to introduce a system that is able to adjust order processing dynamically, and optimise intralogistics transportation regarding various generic intralogistics target criteria. The logistics system under consideration consists of various means of transport for autonomous decision-making and fulfilment of transport orders with defined source-sink relationships. The context of this work is set by introducing the Learning Factory Werk 150 with its existing hardware and software infrastructure and its defined target figures to measure the performance of the system. Specifically, the important target figures cost and performance are considered for the transportation system. The core idea of the system’s logic is to solve the problem of order allocation to specific means of transport by linking a Genetic Algorithm with a Multi-Agent System. The implementation of the developed system is described in an application scenario at the learning factory.
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