Case Study of Intralogistics in the Framework of Logistics 4.0

Industry 4.0 has led to changes that have reduced the labor force and created production environments where machines that bring together information technology and industry communicate with each other. Logistics 4.0, which emerged with Industry 4.0, paved the way for improvement in logistics processes. Using information technologies in logistics reduces the labor force costs of enterprises by leading all stages of activities to digitalization. It can be possible to increase customer satisfaction and product quality by reducing human failures with digitalization. This study was performed by planning intralogistics using Logistics 4.0 technological tools, and also the problem of a manufacturing company was elaborated as a case study. This study was carried out by quantitative data analysis in the case study and a large-scale production company in the automotive industry in Turkey providing the intralogistics of the materials from the supplier in the entrance warehouse with RFID (Radio Frequency Identification) technologies. This paper presents the research, development, and application of logistics 4.0 in the intralogistics process from the entrance warehouse to the production lines. The aim of the case study was provided to information about the technologies available within the scope of Logistics 4.0 and contribute to the literature and industry with solution suggestions depending on the result of the application study within the logistics operations. As a result, depending on the case study, it was determined that Logistics 4.0 improved intralogistics operations costs by 13.37%

Warehouse commodity classification from fundamental principles. Part II: Flame heights and flame spread

In warehouse storage applications, it is important to classify the burning behavior of commodities and rank them according to their material flammability for early fire detection and suppression operations. In this study, a preliminary approach towards commodity classification is presented that models the early stage of large-scale warehouse fires by decoupling the problem into separate processes of heat and mass transfer. Two existing nondimensional parameters are used to represent the physical phenomena at the large-scale: a mass transfer number that directly incorporates the material properties of a fuel, and the soot yield of the fuel that controls the radiation observed in the large-scale. To facilitate modeling, a mass transfer number (or B-number) was experimentally obtained using mass-loss (burning rate) measurements from bench-scale tests, following from a procedure that was developed in Part I of this paper. Two fuels are considered: corrugated cardboard and polystyrene. Corrugated cardboard provides a source of flaming combustion in a warehouse and is usually the first item to ignite and sustain flame spread. Polystyrene is typically used as the most hazardous product in large-scale fire testing. The nondimensional mass transfer number was then used to model in-rack flame heights on 6.19.1 m (2030 ft) stacks of 'C' flute corrugated cardboard boxes on rack-storage during the initial period of flame spread (involving flame spread over the corrugated cardboard face only). Good agreement was observed between the model and large-scale experiments during the initial stages of fire growth, and a comparison to previous correlations for in-rack flame heights is included. © 2011 Elsevier Ltd. All rights reserved

PhyNetLab: An IoT-Based Warehouse Testbed

Future warehouses will be made of modular embedded entities with communication ability and energy aware operation attached to the traditional materials handling and warehousing objects. This advancement is mainly to fulfill the flexibility and scalability needs of the emerging warehouses. However, it leads to a new layer of complexity during development and evaluation of such systems due to the multidisciplinarity in logistics, embedded systems, and wireless communications. Although each discipline provides theoretical approaches and simulations for these tasks, many issues are often discovered in a real deployment of the full system. In this paper we introduce PhyNetLab as a real scale warehouse testbed made of cyber physical objects (PhyNodes) developed for this type of application. The presented platform provides a possibility to check the industrial requirement of an IoT-based warehouse in addition to the typical wireless sensor networks tests. We describe the hardware and software components of the nodes in addition to the overall structure of the testbed. Finally, we will demonstrate the advantages of the testbed by evaluating the performance of the ETSI compliant radio channel access procedure for an IoT warehouse

East Midlands strategic distribution study

This study assesses the importance of the logistics sector to the economy of the East Midlands and provides an understanding of land requirements and demand for sites from logistics companies in the region in the short, medium and long term

Modeling views in the layered view model for XML using UML

In data engineering, view formalisms are used to provide flexibility to users and user applications by allowing them to extract and elaborate data from the stored data sources. Conversely, since the introduction of Extensible Markup Language (XML), it is fast emerging as the dominant standard for storing, describing, and interchanging data among various web and heterogeneous data sources. In combination with XML Schema, XML provides rich facilities for defining and constraining user-defined data semantics and properties, a feature that is unique to XML. In this context, it is interesting to investigate traditional database features, such as view models and view design techniques for XML. However, traditional view formalisms are strongly coupled to the data language and its syntax, thus it proves to be a difficult task to support views in the case of semi-structured data models. Therefore, in this paper we propose a Layered View Model (LVM) for XML with conceptual and schemata extensions. Here our work is three-fold; first we propose an approach to separate the implementation and conceptual aspects of the views that provides a clear separation of concerns, thus, allowing analysis and design of views to be separated from their implementation. Secondly, we define representations to express and construct these views at the conceptual level. Thirdly, we define a view transformation methodology for XML views in the LVM, which carries out automated transformation to a view schema and a view query expression in an appropriate query language. Also, to validate and apply the LVM concepts, methods and transformations developed, we propose a view-driven application development framework with the flexibility to develop web and database applications for XML, at varying levels of abstraction

Warehouse commodity classification from fundamental principles. Part I: Commodity & burning rates

An experimental study was conducted to investigate the burning behavior of an individual Group A plastic commodity over time. The objective of the study was to evaluate the use of a nondimensional parameter to describe the time-varying burning rate of a fuel in complex geometries. The nondimensional approach chosen to characterize burning behavior over time involved comparison of chemical energy released during the combustion process with the energy required to vaporize the fuel, measured by a B-number. The mixed nature of the commodity and its package, involving polystyrene and corrugated cardboard, produced three distinct stages of combustion that were qualitatively repeatable. The results of four tests provided flame heights, mass-loss rates and heat fluxes that were used to develop a phenomenological description of the burning behavior of a plastic commodity. Three distinct stages of combustion were identified. Time-dependent and time-averaged B-numbers were evaluated from mass-loss rate data using assumptions including a correlation for turbulent convective heat transfer. The resultant modified B-numbers extracted from test data incorporated the burning behavior of constituent materials, and a variation in behavior was observed as materials participating in the combustion process varied. Variations between the four tests make quantitative values for each stage of burning useful only for comparison, as errors were high. Methods to extract the B-number with a higher degree of accuracy and future use of the results to improve commodity classification for better assessment of fire danger are discussed. © 2011 Elsevier Ltd. All rights reserved