671 research outputs found

    Progress in Material Handling Research: 2010

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    Table of Content

    A Review on Automated Storage/ Retrieval Systems and Shuttle Based Storage/Retrieval Systems

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    Automated storage and retrieval systems are warehousing systems that are used for the storage and retrieval of products in both distribution and production environments. Shuttle based storage/retrieval systems are composed of elevators with lifting tables that are attached on a mast, shuttle carriers, buffer positions and the storage racks. It is observed that the shuttle based storage/retrieval systems increases the throughput capacity of the systems compared to automated storage/retrieval systems. Shuttle based storage/retrieval systems is relatively a new technology in automated storage and retrieval systems and usually works with aisle and tier captive shuttles. This new technology is mostly used for mini-load warehouses. The main body of the paper consists of an overview of literature discussing automated storage/retrieval systems and shuttle based storage/retrieval systems

    Sea Container Terminals

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    Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

    A Roadmap towards an Automated Warehouse Digital Twin: current implementations and future developments

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    Automation and digitization increase the effectiveness and efficiency of logistics processes. In warehousing, Automated Storage and Retrieval Systems (AS/RS) are largely adopted due to their considerable advantages over traditional warehousing, namely high space utilization, shorter cycle times and improved inventory control. To further enhance such advantages, warehouse operations can be digitized via a Digital Twin (DT) which retrieves data from the real-world industrial process, mimics its behaviour and feeds specific inputs back to the real-world process, after elaboration from a simulation-based digital model. This work presents a DT proposal for a real-world AS/RS system, highlighting its current implementations together with its future developments

    An agent approach to improving radio frequency identification enabled Returnable Transport Equipment

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    Returnable transport equipment (RTE) such as pallets form an integral part of the supply chain and poor management leads to costly losses. Companies often address this matter by outsourcing the management of RTE to logistics service providers (LSPs). LSPs are faced with the task to provide logistical expertise to reduce RTE related waste, whilst differentiating their own services to remain competitive. In the current challenging economic climate, the role of the LSP to deliver innovative ways to achieve competitive advantage has never been so important. It is reported that radio frequency identification (RFID) application to RTE enables LSPs such as DHL to gain competitive advantage and offer clients improvements such as loss reduction, process efficiency improvement and effective security. However, the increased visibility and functionality of RFID enabled RTE requires further investigation in regards to decision‐making. The distributed nature of the RTE network favours a decentralised decision‐making format. Agents are an effective way to represent objects from the bottom‐up, capturing the behaviour and enabling localised decision‐making. Therefore, an agent based system is proposed to represent the RTE network and utilise the visibility and data gathered from RFID tags. Two types of agents are developed in order to represent the trucks and RTE, which have bespoke rules and algorithms in order to facilitate negotiations. The aim is to create schedules, which integrate RTE pick‐ups as the trucks go back to the depot. The findings assert that: - agent based modelling provides an autonomous tool, which is effective in modelling RFID enabled RTE in a decentralised utilising the real‐time data facility. ‐ the RFID enabled RTE model developed enables autonomous agent interaction, which leads to a feasible schedule integrating both forward and reverse flows for each RTE batch. ‐ the RTE agent scheduling algorithm developed promotes the utilisation of RTE by including an automatic return flow for each batch of RTE, whilst considering the fleet costs andutilisation rates. ‐ the research conducted contributes an agent based platform, which LSPs can use in order to assess the most appropriate strategies to implement for RTE network improvement for each of their clients

    A Proposed Architecture for Big Data Driven Supply Chain Analytics

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    Advancement in information and communication technology (ICT) has given rise to explosion of data in every field of operations. Working with the enormous volume of data (or Big Data, as it is popularly known as) for extraction of useful information to support decision making is one of the sources of competitive advantage for organizations today. Enterprises are leveraging the power of analytics in formulating business strategy in every facet of their operations to mitigate business risk. Volatile global market scenario has compelled the organizations to redefine their supply chain management (SCM). In this paper, we have delineated the relevance of Big Data and its importance in managing end to end supply chains for achieving business excellence. A Big Data-centric architecture for SCM has been proposed that exploits the current state of the art technology of data management, analytics and visualization. The security and privacy requirements of a Big Data system have also been highlighted and several mechanisms have been discussed to implement these features in a real world Big Data system deployment in the context of SCM. Some future scope of work has also been pointed out. Keyword: Big Data, Analytics, Cloud, Architecture, Protocols, Supply Chain Management, Security, Privacy.Comment: 24 pages, 4 figures, 3 table

    A reinforcement learning approach for transaction scheduling in a shuttle-based storage and retrieval system

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    With recent Industry 4.0 developments, companies tend to automate their industries. Warehousing companies also take part in this trend. A shuttle-based storage and retrieval system (SBS/RS) is an automated storage and retrieval system technology experiencing recent drastic market growth. This technology is mostly utilized in large distribution centers processing mini-loads. With the recent increase in e-commerce practices, fast delivery requirements with low volume orders have increased. SBS/RS provides ultrahigh-speed load handling due to having an excess amount of shuttles in the system. However, not only the physical design of an automated warehousing technology but also the design of operational system policies would help with fast handling targets. In this work, in an effort to increase the performance of an SBS/RS, we apply a machine learning (ML) (i.e., Q-learning) approach on a newly proposed tier-to-tier SBS/RS design, redesigned from a traditional tier-captive SBS/RS. The novelty of this paper is twofold: First, we propose a novel SBS/RS design where shuttles can travel between tiers in the system; second, due to the complexity of operation of shuttles in that newly proposed design, we implement an ML-based algorithm for transaction selection in that system. The ML-based solution is compared with traditional scheduling approaches: first-in-first-out and shortest process time (i.e., travel) scheduling rules. The results indicate that in most cases, the Q-learning approach performs better than the two static scheduling approaches

    Integrated Models and Tools for Design and Management of Global Supply Chain

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    In modern and global supply chain, the increasing trend toward product variety, level of service, short delivery delay and response time to consumers, highlight the importance to set and configure smooth and efficient logistic processes and operations. In order to comply such purposes the supply chain management (SCM) theory entails a wide set of models, algorithms, procedure, tools and best practices for the design, the management and control of articulated supply chain networks and logistics nodes. The purpose of this Ph.D. dissertation is going in detail on the principle aspects and concerns of supply chain network and warehousing systems, by proposing and illustrating useful methods, procedures and support-decision tools for the design and management of real instance applications, such those currently face by enterprises. In particular, after a comprehensive literature review of the principal warehousing issues and entities, the manuscript focuses on design top-down procedure for both less-than-unit-load OPS and unit-load storage systems. For both, decision-support software platforms are illustrated as useful tools to address the optimization of the warehousing performances and efficiency metrics. The development of such interfaces enables to test the effectiveness of the proposed hierarchical top-down procedure with huge real case studies, taken by industry applications. Whether the large part of the manuscript deals with micro concerns of warehousing nodes, also macro issues and aspects related to the planning, design, and management of the whole supply chain are enquired and discussed. The integration of macro criticalities, such as the design of the supply chain infrastructure and the placement of the logistic nodes, with micro concerns, such the design of warehousing nodes and the management of material handling, is addressed through the definition of integrated models and procedures, involving the overall supply chain and the whole product life cycle. A new integrated perspective should be applied in study and planning of global supply chains. Each aspect of the reality influences the others. Each product consumed by a customer tells a story, made by activities, transformations, handling, processes, traveling around the world. Each step of this story accounts costs, time, resources exploitation, labor, waste, pollution. The economical and environmental sustainability of the modern global supply chain is the challenge to face

    Feasibility analysis of using microcircuit technology in logistics applications/radio frequency (MITLA/RF) to support equipment maintenance management

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    This thesis presents the background, criteria, and baseline recommendations for a Microcircuit Technology in Logistics Application/Radio Frequency (MITLA/RF) proposal to support developing maintenance management doctrine. Its main thrust is a preliminary feasibility analysis of MITLA/RF to identify key issues with regard to maintenance operations within emerging Operational Maneuver From The Sea (OMFTS) concepts. This thesis surveys current requirements, information systems initiatives, test/evaluation results, implementation issues, and technology tradeoffs. It offers alternatives to reliance on manual record keeping and frameworks for enhancing horizontal/ vertical information flows, explores several near real-time interactive decision making tools, and suggests doctrinal improvements through a fusion of procedural and high-tech approaches. This study is an outline for melding policy change with the state-of-the-art technology required to successfully support emerging Combat Service Support (CSS) operations.http://archive.org/details/feasibilitynalys1094539655Major, United States Marine CorpsCaptain, United States Marine Corps.Approved for public release; distribution is unlimited
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