Call for Papers

Special Issue of Production and Operations Management Journal

“Managing Autonomous and IoT-driven Intralogistics Operations”

Guest Editors:

René de Koster, Erasmus University, The Netherlands (rkoster@rsm.nl)

Debjit Roy, Indian Institute of Management Ahmedabad, India (debjit@iima.ac.in)

Yun Fong Lim, Singapore Management University, Singapore (yflim@smu.edu.sg)

Subodha Kumar, Temple University, USA (subodha@temple.edu)

Deadline: December 15, 2020

Managing performance of intralogistics operations, i.e., within facilities such as manufacturing, order fulfillment warehouses, retail stores, hospitals, or terminals, is critical in fulfilling customer expectations. Customer product and service expectations can be volatile. Traditional decision-making for intralogistics operations mostly relies on data collected over long-range intervals with significant delays in processing. However, with Internet of Things (IoT) devices, detailed data can be captured and relayed real-time and systems are geared up for making dynamic decisions in real-time. The advent of new technologies such as smart IoT devices, Artificial Intelligence (AI), and robots allows improving the intralogistics operations by facilitating time-sensitive decisions and reducing costs. All critical resources, though decentralized, are connected to a wider network enabling to capture and process large amounts of data and use these data to improve resource coordination and secure informed data-driven decisions.

For example, e-commerce order fulfilment centers apply new autonomous, robotic handling systems and information-rich technologies to forecast demand, allocate stock, and pick, pack, and ship large numbers of customer orders in very short time frames and deliver them same day in specific time intervals. The autonomous robotic technologies require little space, provide flexibility in managing varying demand requirements, and are able to work 24/7. New categories of autonomous handling systems, such as shuttlebased storage and retrieval systems, robotic mobile fulfillment systems, and autonomous mobile robots collaborating with humans, have evolved. Such systems have a large degree of autonomy, and are used in dynamic interaction with their environment: people, products, locations, and other handling systems, generating large streams of data. Objects, people, storage, and handling systems can all be connected in the IoT warehouse. This generates great challenges for managers to select, manage, and organize systems for performance.

Likewise, tracking real-time stock and people movement in retail stores using IoT devices can help to plan the inventory better and position the store personnel at strategic locations. IoT solutions and connected medical devices allows healthcare providers to monitor patients in real time. This would also eliminate unnecessary visits to the provider, and reduce hospital stay times and readmissions. IoT in container terminals and ports can help minimize traffic, position the containers better in the yard for onward movement, empower their workforces to increase throughput, and decrease carbon emissions while making traffic safer. IoT in production facilities can also track the human movement and improve safety, efficiency, and worker productivity.

Research is needed to leverage unique system features (such as autonomous control, flexible layouts, and networked and dynamic operations). New models and methods are needed to address the management challenges for such systems, in particular, for the integration of subsystems. Facilities with integrated robotic systems, interacting with humans for specific tasks, will form a new category. Vital operations design, planning and control tasks, such as methods to design layout, worker routing, human-robot interfacing, and resource-to-order assignment will have to be revisited for new robotized facilities. In addition, the workers that interact with the IoT-driven facilities require different skills and behavioral traits to operate successfully.

The increasing level of automation in facility processes promises to improve operational flexibility and to cater growing customer expectations. The focused issue on Managing Autonomous and IoT-driven Intralogistics Operations intends to reflect these trends, efforts, and results. The aim is to present original, cutting-edge contributions – methodological and theoretical developments, as well as innovative and insight-provoking applications – that address a wide variety of issues in the management, design, modeling, planning, and organization of intralogistics systems. Topics of interest include (but are not restricted to):

•IoT in facilities such as Retail stores, Healthcare, Warehouses, Terminals, Production facilities

•Data-driven fulfillment models and decisions

•Automation and technology selection

•Operational policies in robotic/ IoT-driven facilities

•Robotized facilities

•Human-robot collaboration

•Use of augmented and virtual reality in fulfillment operations

•IoT aspects in E-commerce

•Human and behavioral factors in automated facility operations

•Safety and security in facility operations

•Planning-feedback process

We welcome submissions that examine operational problems that arise outside the traditional boundaries of intralogistics operations. These include facilities such as manufacturing, order fulfillment warehouses, retail stores, hospitals, or terminals. All submissions must have clear managerial contributions, must be built on rigorous research methods that serve as an appropriate framework to analyze decisions with realtime data: analysis of data, mathematical analysis, analytical models, behavioral theories, etc. We expect the study to address a new (and potentially game-changing) phenomenon, with a sufficient level of rigor that is consistent with the high standard of the journal.

There is no page limit on initial submission. However, you should strive to keep your paper to be no longer than 38 pages double-spaced in a font size of 11. The page limit on the final version is 38 pages. Please follow the detailed submission guidelines provided at http://www.poms.org/journal/author_instructions/.

征集论文

生产与运营管理特刊

“管理自主和物联网驱动的内部物流运营”

特邀编辑：

René de Koster, 伊拉斯姆斯大学, 荷兰(rkoster@rsm.nl)

Debjit Roy, 艾哈迈达巴德印度管理学院, 印度(debjit@iima.ac.in)

Yun Fong Lim, 新加坡管理大学, 新加坡(yflim@smu.edu.sg)

Subodha Kumar, 天普大学, 美国(subodha@temple.edu)

截止日期：2020年12月15日

管理内部物流运营即在制造、订单履行仓库、零售店、医院或终端等设施内的绩效，对实现客户期望至关重要。客户对产品和服务的期望值是不稳定的。传统的内部物流运营决策大多依赖于长时间间隔收集的数据，处理过程中存在严重延迟。然而，通过物联网（IoT）设备，可以实时捕获和传输详细的数据，并且系统可以实时地进行动态决策。智能物联网设备、人工智能（AI）和机器人等新技术的出现，通过促进对时间敏感的决策和降低成本，可以改善内部物流运营。所有关键资源虽然分散，但都与一个更广泛的网络相连，能够捕获和处理大量数据，并使用这些数据来改善资源协调，确保以数据为导向的明智决策。

例如，电子商务订单履行中心应用新的自主、机器人处理系统和信息丰富的技术，在极短的时间内预测需求、分配库存、挑选、包装和运送大量客户订单，并在特定的时间间隔内于同一天交付。自主机器人技术需要的空间很小，能够灵活地管理各种需求，并且能够全天候工作。自主处理系统的新类别已经逐步发展，例如基于穿梭机的存储和检索系统、机器人移动履行系统以及与人类协作的自主移动机器人。这样的系统具有很大程度的自治性，并用于与环境：人员、产品、位置和其他处理系统的动态交互，生成大量数据流。对象、人员、存储和处理系统都可以在物联网仓库中连接。这给管理者选择、管理和组织系统以提高绩效带来了巨大的挑战。

同样，使用物联网设备跟踪零售店中的实时库存和人员流动有助于更好地规划库存，并将门店人员定位在战略位置。物联网解决方案和联网医疗设备允许医疗保健提供商实时监控患者。这也将减少不必要的就诊，减少住院时间和再入院。集装箱码头和港口的物联网有助于最大限度地减少交通量，更好地将集装箱放置在堆场内，以便向前移动，增强其劳动力的能力，提高吞吐量，减少碳排放，同时使交通更加安全。生产设施中的物联网还可以跟踪人员流动，提高安全性、效率和工人生产率。

需要进行研究以利用独特的系统特性（如自主控制、灵活布局、网络化和动态运营）。需要新的模型和方法来解决这些系统的管理挑战，特别是子系统的集成。具有集成机器人系统的设施，与人类进行特定任务的互动，将形成一个新的类别。重要的运营设计、规划和控制任务，如设计布局、工人路线、人机接口和资源到订单分配的方法，必须针对新的自动化设施进行重新审查。此外，与物联网驱动设施互动的工人需要不同的技能和行为特征才能成功运作。

设施过程自动化水平的不断提高有助于提高运营灵活性并满足不断增长的客户期望。管理自主和物联网驱动的内部物流运营的特刊旨在反映这些趋势、努力和结果。其目的是展示独创、前沿的贡献-方法和理论发展，以及创新和启发洞察力的应用-解决内部物流系统的管理、设计、建模、规划和组织中的各种问题。感兴趣的主题包括（但不限于）：

•零售店、医疗保健、仓库、终端、生产设施等设施中的物联网

•数据驱动的实现模型和决策

•自动化和技术选择

•机器人/物联网驱动设施的运营政策

•自动化设施

•人机协作

•在实现运营中使用增强和虚拟现实

•电子商务中的物联网方面

•自动化设施操作中的人和行为因素

•设施运行的安全保障

•计划反馈过程

我们欢迎提交调查在内部物流运营传统边界之外出现的运营问题。这些包括设施如制造、订单履行仓库、零售商店、医院或终端。所有提交的材料必须有明确的管理贡献，必须建立在严谨的研究方法之上，这些方法可以作为一个适当的框架，用实时数据分析决策：数据分析、数学分析、分析模型、行为理论等。我们期望这项研究能够解决一个新的（而且可能改变游戏规则的）现象，具有足够的严谨程度，与期刊的高标准一致。

初次提交没有页数限制。但是，你应该努力保持你的论文不超过38页，双倍行距，字体大小为11。最终版本的页数限制为38页。请遵循网站上提供的详细提交指南http://www.poms.org/journal/author_instructions/。