Cyber physical ecommerce logistics system: An implementation case in Hong Kong

Computers & Industrial Engineering 139 (2020) 106170

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Cyber physical ecommerce logistics system: An implementation case in Hong Kong

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Xiang T.R. Konga, Ray Y. Zhongb, Zhiheng Zhaoc, Saijun Shaoa, Ming Lid, Peng Linb, Yu Chenb, ⁎ Wei Wub, Leidi Shenb, Ying Yub, George Q. Huangb, a

Collaborative Research Centre for Supply Chain Innovation, Department of Transportation Economy and Logistics Management, College of Economics, Shenzhen University, Shenzhen, PR China b HKU-ZIRI Lab for Physical Internet, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China c School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, PR China d Institute of Physical Internet, Jinan University (Zhuhai Campus), Zhuhai, Guangdong, PR China

ARTICLE INFO

ABSTRACT

Keywords: Ecommerce logistics Cyber physical system Synchronization Case studies

Space limitation confines cross-border ecommerce logistics development in Hong Kong. Information technologies and practices lagged types are still used in most of small and medium sized enterprises. In order to upgrade the ecommerce logistics by making full use the cutting-edge technologies and principles, this paper proposes a multi-layer cyber physical system-enabled cloud platform to achieve logistics assets virtualization and real-time control, execution, reconfiguration as well as simultaneous-and-punctual process synchronization. In physical world, industrial wearable technology transforms traditional assets into cloud assets. In cyber world, synchronization mechanisms improve the utilization ratio of spaces and resources while reducing waiting and wastage. An implementation of the platform is conducted through two major pilot cases. It shows that this platform can realize modularization of technology application with sufficient productivity improvement and bring about stepchange paradigm for ecommerce logistics.

1. Introduction Cross-border ecommerce is developing rapidly. According to recent report (HKTDC Research, 2015), the number of people carrying out overseas online shopping in China is 35.6 million in 2018, while the value of overseas online shopping transactions jumps to RMB1000 billion. As a special and open region of China, Hong Kong possesses advantages in bringing foreign goods onto the mainland market and may wish to expand its B2B and B2C ecommerce markets. However, fierce regional competitions challenge Hong Kong’s role as an Asiapacific logistics hub since the neighbouring regions develop their logistics industry fast towards higher level of automation and intelligence. Ecommerce logistics park, as a place where goods are physically consolidated, is one of the efficient and effective approaches to alleviate the cross-border ecommerce logistics development in Hong Kong. Enterprises are able to share cost-effective infrastructure and communal services such as managed workspace, distribution centre, transportation, etc. (Qiu, Luo, Xu, Zhong, & Huang, 2014). However, it is difficult to physically build a large ecommerce logistics park considering the

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limited space in Hong Kong (Huang, Chen, & Pan, 2015). New operation models and mechanisms should be established. The concept of “virtual enterprises” is used to develop a system architecture to integrate and control the interoperability of the distributed, heterogeneous and concurrent systems in the participating organizations (Gou, Huang, Liu, & Li, 2003; Park & Favrel, 1999). Virtual ecommerce logistics park platform can thus be designed and developed with analogy to virtual enterprise, which comprises multiple equal-interest companies coming together to form an alliance to exploit shared resources to adapt to fast-changing market. After several years of research efforts, the maturing of physical internet (PI) also offers a solid theoretical support for resource virtualization and sharing of cross-border ecommerce logistics (Pan, Ballot, Huang, & Montreuil, 2017). For example, physical elements of PI could enable fast, efficient and reliable multimodal logistics fulfilments, by allowing ease of transfer of π-containers between combinations of road, rail, water and air transportation (Montreuil, Meller, & Ballot, 2010; Walha, Bekrar, Chaabane, & Loukil, 2016). It is also believed that PI-enabled intelligent planning, coordination and control will facilitate process synchronization in the complicated warehousing operations (Kong, Chen, Luo, & Huang,

Corresponding author. E-mail address: [email protected] (G.Q. Huang).

https://doi.org/10.1016/j.cie.2019.106170 Received 14 April 2019; Received in revised form 21 August 2019; Accepted 8 November 2019 Available online 11 November 2019 0360-8352/ © 2019 Published by Elsevier Ltd.

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• How to create a CPS-enabled virtual ecommerce logistics platform to

2016). New operation model requires the facilitation of advanced system technologies. However, information technologies and practices are still lagged in most of small and medium sized enterprises (SMEs) in Hong Kong due to the capital constrains and technical threshold.

• Lagged IT architecture and solution: the existing IT infrastructure

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is not well integrated with the operation processes to address industrial challenges. Reconfigurable task coordination and control across key stages of ecommerce order fulfillment are still scarcely concerned. Although the enterprise information systems (e.g. warehouse management system and fleet management system), handheld devices and automation equipment (e.g. automated storage and retrieval system) have been applied, the gap between planning & scheduling level and execution level still exists. Traditional data collection and interoperation method: the operations involve intensive labor and paper-based manual data collection. The front-line field information is delayed and even missing sometimes. Traditional handheld devices for frontline operators are not flexible enough to deal with complex situations. The location of large amount of machine-type assets (e.g. forklifts and shelves) cannot be traced and tracked so that delivery delay often occurs. Unsynchronized resource scheduling and order fulfilment process: the unsynchronized sorting may confine the utilization of space in a warehouse where the buffer for holding products is limited. The firstly arrived items may take up the limited space waiting for the later ones in the buffer before dispatching. How to improve the utilization ratio of spaces and resources is becoming even more challenging when the demand is dynamic. Unstructured automation in Hong Kong: full automation solution is usually capital-intensive, equipped with high-tech robotics and facilities. The short terms of warehouse service contracts with high rents and small space in Hong Kong also deter either warehouse owner or user to purchase modern warehousing facility. The warehouse user could not enjoy the full benefit from the advanced facility in a short term, while the warehouse owner may need to discard the facility due to the changing demand of new users (Yang, Lan, & Huang, 2019).

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integrate and control the interoperability of the distributed, heterogeneous and concurrent resources of participating companies? Industrial wearable technologies are applied to define, connect and (re)configure heterogeneous objects deployed in ecommerce logistics scenarios. Traditional assets are thus upgraded into cloud assets. Cloud asset-enabled smart buffering, smart consolidation and smart patrolling solutions are also proposed. Participating SMEs can easily deploy and use such shared services. How to establish an intelligent coordination system that is able to interact with diverse assets for task execution and collaborative decision making? The cloud assets and job pool management services are introduced to manage the multi-source data collected from the physical space and synchronize them to cyber space. The system can be deployed in both physical and cyber world to offer tactic reasoning and control for all the registered cloud assets with maximized optimization of resource coordination. How to facilitate the process synchronization of ecommerce logistics chain from supply side to demand side with the real-time information provided by CPS technologies? This paper introduces a realtime visibility and traceability dashboards for ecommerce logistics chain with synchronization mechanisms, which consider both simultaneity and punctuality as performance measurements. The mechanisms can be also (re)designed and implemented to deal with both market and system discrepancies.

The remainder of this paper is organized as follows. Section 2 introduces the architecture of the proposed platform and discusses design and development considerations to make the platform into a technical reality. Industrial wearable-enabled cloud logistics assets are also discussed. Two key innovative and enabling components are examined in the following sections respectively, namely iCoordinator and smart operations (Section 3) and iSync services (Section 4). In Section 5, two real-life pilot cases from Hong Kong SMEs are used to demonstrate the necessity and usefulness of presented systems and mechanisms. Section 6 concludes the paper by providing insights gained from implementation and discussing several aspects for improvement. 2. The architecture of CPeLS

A solution with associated driving mechanisms is needed for the upgrade and transformation of Hong Kong’s ecommerce logistics industry. Several cutting-edge technologies can be applied to facilitate agile ecommerce operation management. Cyber physical system (CPS) is defined as transformative technologies for managing interconnected systems between its physical assets and computational capabilities (Baheti & Gill, 2011). By integrating CPS with production, logistics and services in the current industrial practices, it would transform today’s factories into an Industry 4.0 factory with significant economic potential (Lee, Bagheri, & Kao, 2015). Currently, most CPS studies and applications are focused in manufacturing realm (Monostori et al., 2016; Wang, Törngren, & Onori, 2015). Leitão, Colombo, and Karnouskos (2016) presented CPS-enabled industrial automation implementation based on four European innovation projects. The human-centered activities within cyber physical productions are designed, modelled and evaluated to improve the overall factory performance and organization (Fantini, Pinzone, & Taisch, 2018; Kaasinen et al., 2019; Peruzzini, Grandi, & Pellicciari, 2018). Research effort in ecommerce logistics area using CPS technologies is still limited (Boysen, de Koster, & Weidinger, 2018). Based on CPS technologies, this paper proposes a unified Cyber Physical eCommerce Logistics System (CPeLS) framework from realtime field data capturing, through heterogeneous resource coordination and scheduling, to optimal supply chain synchronization decisions. Several research questions and corresponding research approaches are put forward as follows:

2.1. System overview The overall platform is built on the cloud computing architecture to enable three levels of cloud service: Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). The overall architecture is illustrated in Fig. 1, which enables several technologies to be systematically integrated, deployed and shared in logical layers. The proposed platform architecture is consistent with the standard enterprise hierarchy defined by ISA-95 enterprise-control system integration standard (http://www.isa.org). Implementing enterprise information systems to be consistent with this standard hierarchy will ensure the system applicable and extensible for cross-border ecommerce logistics companies. Real-time and seamless dual-way connectivity and interoperability could be also achieved among application systems at enterprise, work floor, work cells and IoT devices. The approach of creating CPS-enabled ecommerce logistics platform is generally applicable when other management standards, strategies or devices are adopted, no matter they replace or complement the existing solution. In the IaaS level, the cloud logistics asset (CLA) is the core technology for transforming physical logistics assets to virtualized cloud agents, which will be further explained in later section. The basic element of CLA is the industrial wearable object (IWO) which combines sensing technologies with industrial wearable devices. These IWOs could be easily and conveniently integrated and deployed on physical assets in most suitable forms and functions to capture real-time filed 2

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Fig. 1. Overall architecture of CPS-enabled ecommerce logistics platform.

information. The mGOS (mobile gateway operating system) is another core technology to achieve the physical assets virtualization and realize the intelligent control in software aspect. It is the lightweight gateway operating system that could be installed on several IWOs to promote the host as the gateway for other IWOs. Through mGOS, IWOs-equipped physical logistics assets could be registered, mapped and managed on the cloud and able to take actions based on command from upper layer or tactical rules for situations in physical world. In the PaaS level, the following two key components are involved: (1) the intelligent coordination system (iCoordinator), as the core technology in execution layer, facilitates the execution of synchronized order fulfillment process. It receives the order commands from the

upper level while coordinating CLAs to fulfil specified operations; and (2) the intelligent synchronization system (iSync) that works in scheduling layer is proposed to solve the synchronization problems in ecommerce logistics parks. It aims at synchronizing resources for related stakeholders to cooperate smoothly with minimum wastage (e.g. waiting time) using intelligent mechanisms/algorithms. In the SaaS level, three services are included. First, a multi-dimension visualization tool is provided for different stakeholders to check their related synchronization information. Second, virtual space management tool incorporates “virtual enterprise” concept while coordinating different ecommerce logistics scenarios in distributed geographical locations with different business objectives. Different 3

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enterprise legacy systems such as WMS and TMS can be rapidly integrated with CPeLS platform with standardized and open application programming interfaces. As seen in Fig. 1, the abbreviations of CN, ZARA, JD and E3 are different brand of WMS systems and used in distributed locations such as Guangzhou, Hong Kong and Ningbo. CPeLS also separates the running environment for deployment of the subscribed services and provides a safe cloud for enterprise users. Third, value-added data analytics tool stores the theoretical and empirical models for process optimization from supply side to demand side. This article focuses on presenting three key components, namely cloud logistics object, iCoordinator and iSync respectively, which are fundamental enablers of cyber physical system for ecommerce logistics. All traditional logistics resources such as operators, equipment and tools in physical world can be transformed into cloud assets. iCoordinator integrates the physical world and cyber world. The iSync is deployed on cyber level that imports the models in synchronization knowledge to continuously provide decisions for iCoordinator to execute. Disaster recovery and data security functionality are necessary if CPS-enabled ecommerce logistics platform is to realize their full potentials in real-life implementations. CPeLS platform is equipped with disaster recovery capability by integrating a third-party solution such as AnyBackup®. This backup solution combines block-level continuous data protection (CDP) with database consistency processing, together with VMware ESXi, so as to ensure business continuity of application system. CDP refers to the backup of computer data by automatically saving a copy of every change made to that data, essentially capturing every version of the data that the user saves. The procedures of disaster recovery are as below.

mode”. On the right, smart boxes can be attached on machines or materials in ecommerce logistics parks to obtain real-time sensing capabilities. For example, a forklift can be equipped with smart box for warehouse internal movements and data of “who moves, where to move and when to move” will be automatically recorded without human intervention. In the middle, a mobile gateway operation system (mGOS) is deployed, which is an overall mobile middleware solution to manage distributed CLAs. mGOS is actually more of a software solution which inherits the characteristics of mobile operation system (e.g. Android and iOS). Systematic studies for human-centric warehousing and machinecentric warehousing enabled by industrial wearables and mGOS have been examined as follows:

• There is an increasing awareness especially in ecommerce logistics

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(1) Deploy AnyBackup® in business network and install AnyBackup® clients on the production servers to be protected. Ensure that the CDP driver is installed; (2) Add VMware virtual disaster recovery platform via AnyBackup® so that the virtual platform can be the storage platform for production data; (3) Create a disaster recovery job and launch data replication, then the production data can be transferred to VMware ESXI continuously.

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To ensure the data security, all application program interface (API) calls on the proposed system is required to process the identify authentication verification. It can thus dynamically issue certificates for users, allowing them to log on to an active directory environment as if they had a smart card. Furthermore, information tags should be used so that the system could recognize the data sensitivity level when output them as reports. Tags will be shown and printed on the report with the defined 4 levels: P (public), I (internal), S (sensitive) and HS (highly sensitive). The user could define the data sensitivity level and configure tag display format such as the location. 2.2. Industrial wearable-enabled cloud logistics assets With the prosperity of wearable computing and industrial sensing technologies, industrial wearables are widely adopted in industries to collect real-time information, facilitate daily operations, and support frontline decision-making. The physical object (e.g., men, machines and materials) with its attached industrial wearable technologies constitute a CLA. CLA upgrades and transforms traditional logistics objects to intelligent agents that could be able to recognize, sense and interact with each other. The purpose of CLA is to create an interconnection and interoperability of communication environment to make the traditional logistics resources controllable and schedulable. A typical framework of CLA is shown in Fig. 2. On the left, logistics operators or supervisors can carry different industrial wearable devices in different working scenarios to realize “working while scanning with hand-free operation

that human capabilities are fundamental and cannot be easily substituted. Even the industrial automation has well-established in some “unmanned warehouses” such Kiva-style robots, it does not necessarily mean the absence of human beings. Human presence not only can be considered as one type of material handling capability (ability to complete specific jobs by human knowledge and experience), but also contributes to the overall system’s fault tolerant (ability to address unplanned situations and accidents). Kong, Luo, Huang, and Yang (2018) proposed an industrial wearable system (IWS) based on a set of unobtrusive body-worn devices and embedded IoT application. IWS is a human-centric connectivity and interaction system to achieve seamless collaboration among all elements (Man, Machine and Material) and establish the human–cyber–physical symbiosis in industrial field. For some ecommerce warehouses, semi-automation machines and vehicles have been used for many processes such as order put-away and stocktaking. The dynamic location information of the vehicles is neither known nor updated, which thus lead to excessive time was consumed in searching, checking and picking the vehicles in warehouse. To solve this problem, Zhao, Zhang, Yang, Fang, and Huang (2018) presented the proactive tracking system architecture using iBeacon technology and the conception of distributed gateways. A collaborative and distributed tandem tracking approach is proposed to realize tracking efficiency including the accuracy and responsiveness. The mGOS is the core module to deal with the heterogeneity of logistics objects in both human-centric warehousing and machinecentric warehousing to realize mobile edge computing of industrial wearables and dynamic resource reconfiguration to adapt to changing requirements (Li, Xu, Lin, & Huang, 2019). As a mobile middleware solution, three key functions are enabled: (1) connects (wired or wirelessly), hosts and provides a specific channel for a set of smart assets connecting to the cloud; (2) processes, caches and exchanges real-time data and events locally and temporally; (3) provides facilities for service definition, configuration and execution locally at wearable and mobile devices; and (4) makes online/offline control for all the smart devices it hosted.

3. iCoordinator for smart operations Based on the innovative technologies of CLAs, many implemented instances have been developed. Considering the real-world working environments in ecommerce logistics park, three typical CLAs-enabled operations have been created, including smart buffering, smart patrolling and smart consolidation. iCoordinator will enable the interoperability of these smart operations. 3.1. Smart operations Smart buffering defines operational process of warehouse internal movement of stored products from a specified storage location to 4

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Fig. 2. The conceptual framework for CLAs.

Fig. 3. CLAs-enabled smart buffering.

another storage location by forklifts. Various assets such as pallets, forklifts, shelves and storage racks are involved in this operation. These assets currently work independently, which are difficult to manage. Smart buffering contains three main components, they are cloud forklifts, cloud pallets and cloud storage units. The smart buffering will make the physical assets smart because they can be perceived by others and perceive their own surroundings. An overall illustration of the smart buffering is in Fig. 3. Stocktaking is a non-value added and labour-intensive process in warehousing operations. Operators need to travel around the whole

warehouse to check and confirm the stored products. Moreover, refrigerated warehouse or humidity-sensitive warehouse need particular temperature or humidity to keep the stock in good function. A droneenabled smart patrolling solution is proposed to realize the automated patrolling in the ecommerce logistics parks. Smart Box sensing kit with ample sensing library such as HD camera, temperature/humidity sensor and gyroscope can provide real-time onsite information to management-level. Fig. 4 describes the main features of drone-enabled patrolling and sensing. Products are attached with barcodes or QR codes. Drone can extend human reach to every corner of the warehouse under 5

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3.2.1. Cloud assets management module iCoordinator deals with the scalability of executable CLAs in ecommerce order fulfilment. This module manages behaviour and business process of different types of heterogeneous assets and their agents in handling the real-time events and associated data. Resources (agents) may include manual operators, traditional equipment and robotic automation systems. Different kinds of order fulfilment resources can be easily added or deleted based on the varied workflow, and their configuration properties can be adjusted without affecting each other and performed in the way of plug-and-play. iCoordinator can also provide various communication ways of connecting these resources (e.g. wired or wireless). 3.2.2. Job pool management module The workflow of order fulfilment operations in various ecommerce logistics parks may be different. To fulfil these requirements, job workflow and reconfigurable tactics of iCoordinator is worked out along with the following three steps. Firstly, warehouse resource managers define the workflows according to the process planning and indicate the requirements of resource agents that would be involved. Secondly, each activity in the workflow searches for the qualified and available resource agents automatically. Mapping relationship between the executable activity and resource agents is established. In this procedure, iCoordinator also provides graphic interfaces (i.e. business process configurator) for related decision makers to edit the workflow and process. Thirdly, these selected resources will be invoked through the internet, and actions could be taken according to the predefined parameters. The process execution control engine in iCoordinator not only facilitates the real-time execution according to the defined workflow and logic, but also monitor, coordinate and control these agents during the execution process. Meanwhile, the domain specific knowledge could also be easily transferred to the selected resource as rules via iCoordinator, so that it could easily adapt to new working scenario and execute immediately after being invoked.

Fig. 4. Drone-enabled smart patrolling.

various circumstances and also with high mobility and flexibility. Routine inspection conducted by drones can help to save the labour force and operation time. Once any exception occurs, drones can act immediately. As shown in Fig. 5, smart consolidation is designed with several key enabling technologies and composed of picking, sorting and packing. The loading site is prepared for evaluating the readiness and urgency of these orders. Orders are then shortlisted and queued for releasing. A suitable optimization model of container loading must be selected, considering associated parameters of loaded products (e.g. shapes, volume, weight, priority, etc.). Human-centric method is responsible for picking and packing of non-standard items. Real-time data capturing and processing is carried out via wearable-enabled technologies. The robot arm is mainly used to deal with standard items.

3.2.3. iCoordinator management module iCoordinator provides both online and offline control for all the registered cloud assets to further enhance process/operation synchronization in ecommerce order fulfilment. Besides, big data-based intelligence is adopted to actively improve the process management. A huge amount of real-time data will be collected by various assets located in different areas. Countless useful information will be hidden in these data. Data analytics provides ways to mine knowledge from them. Business processes could then be improved simultaneously during execution through the analysis of these knowledge (Zhong, Newman,

3.2. iCoordinator iCoordinator mainly fulfils two main functions as seen in Fig. 6. On one hand, it handles service requests from iSync on the higher cloud level. On the other hand, it collects and distributes real-time notifications from various types of CLAs in smart consolidation, buffering and patrolling operations.

Fig. 5. CLAs-enabled smart consolidation. 6

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Fig. 6. Conceptual model of iCoordinator.

Huang, & Lan, 2016). iCoordinator requires a minimum of setup and configuration to get up and running while providing secure access to the collected data. Last but not least, iCoordinator is easy to operate once deployed, helping reduce the administration and time required and bring immediate benefit to stakeholders in (virtual) ecommerce logistics parks.

minimize total waiting time (simultaneity). There are three major intelligent system sub-components that facilitate the specific synchronization of this most complicated operational process. 4.1. Sync order In Fig. 8, the main inputs are order loading plans as well as arrival and buffer status in the ecommerce logistics centre. The key outputs are synchronized schedule which determines when to process which order with whom. With the sync order module, operation synchronization is conducted as follows: first, all orders that pending for fulfil are imported into iSync through standard API formats or standard Excel files; second, schedulers will sequence and select orders considering order priority and real-time warehousing status to pursue optimal order loading plans. The top prioritized and shortlisted orders are put and managed in a real-time task pool, which is to facilitate the scheduling operations; third, the selected orders are dragged into sync engine for further processing. Drag-and-drop editing is adopted to facilitate these procedures. Synchronization rules and mechanisms will be used based on various working scenarios. Orders in the pool can be also visualized and managed through mobile devices that informs who processes which task on which equipment at what time.

4. iSync for smart processes iSync is responsible for working out optimal task allocation plans and onsite schedules for the operation and process within the ecommerce logistics parks using advanced mathematical models or solution algorithms. The key users might be centre managers, planners and schedulers. As seen in Fig. 7, the iSync service comprises of supply synchronization, operation synchronization and order synchronization, which correspond to the supply process, warehouse consolidation process and delivery process respectively. Different users are able to use customized synchronization tools and user-friendly interfaces to fulfil their daily operations and make decisions. The developed operation mechanisms and optimization methods are consistent with all these synchronization scenarios. This article focuses on illustrating the operation synchronization service. Fig. 8 shows the proposed operation synchronization service. There are two major decisions. At the beginning of each time horizon-T, the centre manager makes the upper level operation planning. The realtime statuses of all stages (i.e. receiving stage, consolidation stage, dispatching stage) are collected as one of decision input. Information of real customer orders is another input. The aim of operation planning is to balance workload for all stages in each day while achieving the highest punctuality and considering the due date of each order. During every T, each stage manager or scheduler makes the local stage schedule. The real-time machine, manpower and material status in this stage are obtained as decision inputs. The output of upper level is also regarded as the input for operation scheduling. The aim of stage scheduling is to finish all jobs assigned from upper level scheduling and to

4.2. Sync engine Sync engine aims to achieve synchronized warehousing and transportation (SWT) for warehouse and transportation service providers in ecommerce logistics park by taking advantage of resources sharing and cooperative synchronization mechanisms. SWT can be further divided into macro and micro synchronization mechanisms (Tamura, Nagai, Nakagawa, Tanizaki, & Nakajima, 1998). In sync engine, certain rules or mechanisms must be checked and followed automatically during the manual editing process. Any violations must be flagged to warn the planner and scheduler. Micro synchronization mechanism works within the scope of 7

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Fig. 7. Overall synchronization scenarios in ecommerce Logistics Park.

centralized ecommerce warehouse. This problem can be formulated as a multi-stage assembly flow-shop system. The tasks for handling each order are regarded as jobs and processing resources are regarded as identical machines. Order fulfilment simultaneity seeks to ensure all jobs belonging to a same customer order are simultaneously completed. Shipment punctuality attempts to satisfy orders’ individual shipment due dates. A synchronised scheduling model is developed by balancing the two criteria using linear weighted sum method (Chen, Huang, Luo, & Wang, 2015; Wang, Zhang, & Shang, 2013). Macro synchronization mechanism works within the scope of production-logistics synchronization in ecommerce logistics parks (Lin et al., 2018; Luo, Wang, Kong, Lu, & Qu, 2016). The logistics service

providers offer different types of transportation service to manufactures, including “milk-run”, “direct line” and “on-call” transportations. Each transportation mode has its respective advantages and weakness in terms of price, capacity, and flexibility. Various material delivery requirements arise from different production modes. For example, the manufacturers with assembly line need continue and smooth components replenishment to each workstation. Three effective synchronization approaches have been presented by Qiu et al. (2014), considering leader-follower relation (e.g. either manufacturers or logistics service providers take the leading role). Bilevel optimization model is usually employed. Xu, Shao, Qu, Chen, and Huang (2018) further extend synchronization mechanisms to city logistics scenario

Fig. 8. Operation synchronization service. 8

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with auction-based methods.

government.

4.3. Sync dashboard

5.1. A case of manufacturer

The purpose of sync dashboard is to display expedition information to high-level managers and onsite supervisors in different functional teams via real-time visualized reports. The process of inbound truck arrival, internal operations and outbound truck delivery should be also traced, tracked and monitored in this service. In detail, it usually involves the following main functions:

5.1.1. Case company The Union Gas Appliances (Holdings) Limited (UG, for short), is a famous local gas appliances provider in Hong Kong, which provide the highest quality of safety gas appliances and services to consumer. Key products (e.g. gas cooker and gas water heater) and most of the spare parts are manufactured in their factory, which locates in Zhongshan, mainland China, and then transported to warehouse in Hong Kong for retailing and repair services. There are also some special parts which need to be supplied from Japan and UK and shipped to Hong Kong respectively. They can also produce OEM products and export to other countries. The warehouse in Hong Kong is around 1000 square meter and also serves as a distribution centre to fulfil the local services. UG needs a package solution to manage its supply logistics and inventory management in Hong Kong.

• List and select the tasks assigned; • Reprioritize the tasks based on dynamic situations; • Get real-time data and availability status of execution resources (e.g. forklifts, robots); • Assign specific tasks to available working groups with the highest simultaneity; • Monitor the progress of individual task, operator and equipment group status;

5.1.2. Problems identified Lack of real-time data collection and interaction

It is important to note that some medium or large-size ecommerce logistics enterprises have several storage aisles and more than one consolidation sites. Each area may have several working teams with different levels of automation. For example, some advanced logistics enterprises have used Kiva-type robots for order picking and sorting. This complexity can be absorbed by using this service as it follows the rule that only one optimal task is selected and assigned for one team at each time. Furthermore, if the actual execution is disrupted or reorganized in some way, the same negotiation process between these service modules or among particular execution resource agents (e.g. operators) will still take place and hence the system is relatively robust to change.

• Its warehouse is hard to manage various and large volume of spare •

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5. Case study The implementation of CPeLS platform is conducted in close collaboration with both mainland and Hong Kong business partners from manufacturing, logistics, and retailing industries. More specifically, there are two modes of pilot implementation, including configuration mode pilot for SME enterprises and customization mode pilot for representative global enterprises. Yu, Wang, Zhong, and Huang (2017) and Kong, Li, Yu, Zhao, and Huang (2017) have discussed customization mode using a case in furniture industry. This article will focus on the SMEs implementations in Hong Kong under configuration mode to demonstrate the platform reconfigurability and scalability. As seen in Fig. 9, CPeLS platform realizes modularization of technology application. Each innovative component can operate and use independently. Just like Lego building blocks, SMEs can choose which blocks to use and (re)configure the selected blocks based on their own working scenarios and workflows. In addition, CPeLS platform adopts “virtual enterprises” philosophy and supports the interoperability of the distributed, heterogeneous and concurrent systems in the participating organizations. Even if the enterprises are not fixed in a common physical space (e.g., an ecommerce logistics park), all of their operations and decisions can still be managed through the platform effectively. Two major pilot cases in Hong Kong will be discussed, which marked with five stars in Fig. 9. This platform is developed with fund from HKSAR Innovation and Technology Support Program. All enterprises participating in the project can use hardware and software facilities of CPeLS platform without any charges. To realize the success of cutting-edge technology applications and large-scale commercialization, the local government can be the main operator of CPeLS platform. Platform services could be paid per annum with leasing basis to overcome financial burdens of SMEs. If successfully implemented, application users can also get some incentive of cash rebate (a certain percentage of total investment) from local

parts, especially the old spare parts due to high variety in types. Each individual spare part is attached with handwritten code. No barcode coding system was established. There is no effective way to confirm the unique identification of goods and codes. Workers still have to paste handwritten codes during warehouse receiving, then conduct paper-based recording for location, product and associated information. Several hours and even more efforts are needed to input data into its ERP system (just having fundamental financial system module). Such delayed information capturing and transmission lead to high error rate. Management level cannot do informed decisions due to the lack of real-time useful data. The reporting mechanism is also extremely delayed (usually around one month) and several raised issues cannot be solved timely. Mutual conflict of different departments is inevitable. Lack of operation and process synchronization

• The

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supply logistics and ecommerce warehousing processes are decoupled nowadays and the cross-border logistics of finished products and spare parts from mainland China usually arrive at Hong Kong warehouse out of sync. It thus leads to a great waste on time, spaces, and resources during the ecommerce order fulfilment. High warehouse holding cost and unfriendly customer experiences are usually caused. The real-time visibility and traceability of heterogeneous asset in the logistic processes (e.g. real-time forklifting data, stock level) cannot be monitored and controlled, which poses vital influences on the overall performance and productivity. However, the current system has no way of knowing how severe the impact is and how to remedy it. Decision optimization in order delivery and customer caring processes is still the major concern for ensuring the customer satisfaction. Short delivery time/response time and logistics/manpower cost are always the dilemma to balance. Important KPIs need to be rebuilt to establish a more flexible performance measurement and benchmark system.

5.1.3. Solution implementation Based on the practical requirements, modular components of CPeLS platform are delivered for UG including industrial wearable-enabled smart put-away, smart order picking and supply synchronization services. 9

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Fig. 9. CPeLS platform for SMEs under configuration mode.

(1) Industrial wearable-enabled smart put-away and picking in UG raw material warehouse

goods needed in the predetermined time window should be loaded into vehicles in synchronized sequences. Secondly, on-route trajectory can be monitored and controlled real-timely via supply sync Kanban. Thirdly, the activities and dynamic conditions of customs passing can be traced and tracked to avoid unnecessary delays. Fourth, arrival time and location information will be updated real-timely once vehicles arrive at UG Hong Kong warehouse. The tracking devices can be recycled and reused to reduce the total costs.

Fig. 10 shows the reengineered workflows of the UG spare parts warehouse. First, planners would import receiving notes to the web in the office and release the receiving tasks to operators after auditing the notes. In the receiving area, workers use the industrial wearable to obtain tasks and select them for their duty. Then, they use wearable smart gloves to scan the barcode attached with each box of spare parts. It should be illustrated that the same kind of parts in the same batch share the same barcode or QR code. During the put-away process, the QR code of storage rocks will be bounded with counted parts also through smart gloves. When the planner gets an order from customers, he will import the order picking file to the web and release orderpicking tasks to operators after auditing. With order-picking tasks received, operators go to the location of target objects and use the smart gloves to scan the QR code of parts for picking. They will pick in the same way until all the tasks get completed. Next, parts would be taken to the packing area for further process. Fig. 11 presents real-life system implementations and applications in UG warehouse.

5.1.4. Evaluation and reflection Improvements have been made to the UG in several aspects. Firstly, the data required by the Hong Kong warehouse, Zhongshan factory and those exchanged with other stakeholders has become more accurate, real-timely and reliable. The paper-based records were subsequently freed for many processes and industrial wearable-enabled smart operations are running effectively. Secondly, UG adopts supply synchronization services to realize full-chain tracing, tracking and control function for visualizing delivery of high-value spare parts and crossborder transportation has become more efficient. The waiting time is largely reduced via synchronization optimization, which further minimize holding costs in Hong Kong warehouse. Lastly, historical information of key performance indicators stored in the CPeLS platform can be used and analysed for future operational improvements. Besides qualitative improvements, quantitative improvements are also significant. From the pilot run of the CPeLS in the case study, Table 1 presents a statistical analysis from the comparison of before the first pilot run (1 May 2018–30 August 2018) and after the first pilot run (1 September 2018–20 January 2019). From Table 1 it can be seen that for order picking, warehouse inbound and warehouse outbound stages, data collection and transmission has been greatly improved by using the industrial wearables with improvements at 500%, 400% and 500%

(2) Supply synchronization from UG Zhongshan factory to UG Hong Kong warehouse UG warehousing space in Hong Kong is extremely limited. The supply synchronization aims at synchronizing the cross-border transportation of spare parts that manufactured in Zhongshan to maximize the throughput time and minimize holding costs of warehousing in Hong Kong. The overall supply synchronization process is divided into four steps (see Fig. 12). Firstly, goods, vehicles and tracking device are bound with other in Zhongshan factory. The same batch of goods or 10

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Fig. 10. Workflow of smart put-away and picking in UG raw material warehouse.

respectively. More importantly, the use of CPeLS solutions make a stepchange improvement for stock-tacking stage and full-chain visibility and traceability for UG Company.

5.2.2. Solution overview and implementation Tigers’s innovative smart consolidation solution involves three key components as follows:

• Industrial wearable-enabled smart consolidation hardware facilities-

5.2. A case of warehouse service provider 5.2.1. Case company Tigers (HK) Co Ltd. (Tigers, for short) is a global logistics and transportation company that specializes in bespoke supply chain solutions, e-fulfilment and transportation by air, sea and road. Tigers provides comprehensive B2B, B2C, and e-Retail 3PL (third-party logistics) solutions to customers. Currently, Tigers has a warehouse in Hong Kong, which handles around 400–600 orders per day. Tigers has several legacy systems, such as SmartHub, WebStore, Kewill, etc., for order management, tracking and tracing, and inventory management. Kewill is an operational and monitoring system to support warehousing operations. Operators can use mobile terminal to access the Kewill system via telnet applications and interact by inputting text commands. However, some warehousing activities, such as order picking, are not covering by the mobile terminal. Moreover, Tigers still adopts basic order picking scheme (picking by order) without zoning and batching. We thus propose a solution using industrial wearable, iCoordinator and synchronization service to promote the user experience and operational interaction.

•

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industrial wearable devices such as SmartGlove and SmartGlass have been deployed and used in two main stages of smart consolidation (i.e., order picking and order sortation). As shown in Fig. 13, operators will wear wearable terminals and carry a mobile consolidation trolley during order picking to execute the assigned tasks. Operators only needs to follow digital routing guidance to visit prescribed aisles and storage locations to pick SKUs (StockKeeping Units) in right quantity and put them into the right location in mobile consolidation trolley. The picking rules are determined backend and sort-after-pick is suitable for Tigers. In order sortation stage, operators will sort, weight and package all SKUs that belonging to same order. Synchronizing order picking sequence across different picking zones is thus important to avoid unnecessary waiting and resource under-utilization. iCoordinator for managing multiple heterogeneous assets-different smart logistics assets will be used in Tigers warehouse such as mobile consolidation trolley, cloud storage units, fixed consolidation stations and a series of industrial wearables attached on operators. To adapt to dynamic order fulfilment, real-time information

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Fig. 11. Real-life system deployment and application in UG warehouse.

•

collection, sharing and control should be managed effectively via iCoordinator. Moreover, along with changing business requirements and workflows in Tigers warehouse, distributed logistics assets can be flexibly reconfigured to minimize the impact of discrepancies on warehousing performance. Multi-round laboratory testing has been completed before real-life pilot implementation as seen in Fig. 14 for hardware robustness testing, user acceptance testing and integrated function testing. Operation sync for optimizing zone-based parallel order pickingplanner will first import and select the orders for synchronization. The chosen orders are clustered into a group with detailed order information such as priority and due dates. Orders are further divided into jobs based on synchronization mechanism automatically. A job is a group of orders in the same picking wave that will be assigned to the same mobile consolidation trolley in the same picking zone. An order may contain jobs from different trolleys in multiple zones. Operation sync will ensure pickers in different areas of the warehouse work on the same order at the same time while considering work balance. All jobs are digitalized in a job pool and sent to frontline pickers or a working group with optimized routing information. Finally, operators transfer the synchronized SKUs to sortation area for further processing. The cartons are then consolidated and/or re-packed. The task and inventory status will be real-timely transmitted to upper-level system for monitoring.

enable an adaptive decision mode. Such mode potentially results in better efficiency and quality of material movement and inventory management, especially when external market and internal system dynamics (e.g. order changes, inventory stockout) appear which entail coordination from the execution process. 6. Conclusion This paper presents a CPS-enabled platform solution for addressing pain-spot issues in (virtual) ecommerce logistics chains. Problems in the traditional ecommerce logistics parks in both Hong Kong and mainland China have been identified. An innovative multi-layer cloud system architecture has been established to sense, process and manage realtime events in the complicated ecommerce logistics scenarios. Core technological innovations, as main components of CPeLS platform, have been examined with design and implementation considerations. Case studies from Hong Kong SMEs are used to demonstrate the necessity and usefulness of presented systems and mechanisms. Several contributions are significant in this study as follows:

• First, industrial wearable-enabled cloud logistics assets transform •

5.2.3. Evaluation and reflection The system has been continuously tested in the pilot sites for a month. Each observation period is 10 days. Three different picking strategies with associated solutions have been implemented as well, as seen in Table 2. Ratings have been reported from both management and frontline operators (5-star is the highest rating and 1-star is the lowest rating). Most of users prefer to use the proposed smart consolidation solution (zone-based sort-after-pick policy) due to high system speed, robustness, accuracy, scalability and reconfigurability, although it also leads to higher costs. In smart consolidation, real-time operation synchronization further closes the loop of planning and control and thus

•

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traditional assets in ecommerce logistics into intelligent agents with real-time sensing, communication and cognition capabilities. mGOS also provides management tools to (re)configure these decentralized assets to work collaboratively. Second, three typical smart operation solutions are established with CPS-enabled hardware and software to further instantiate the realworld operations of physical assets, including smart buffering, smart consolidation and smart patrolling. iCoordinator provides both online and offline control for all the registered cloud assets in the smart operations to further enhance process synchronization in ecommerce order fulfilment. Third, synchronization tools and mechanisms are designed especially for (virtual) ecommerce logistics chains, which aims to address “early and late arrival/departure” issues to ensure maximized resource utilization, sharing and optimization. Data analytics in

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Fig. 12. Supply synchronization for UG cross-border transportation.

• •

synchronization tools can also provide ways to mine knowledge from the collected data and further improve ecommerce business processes. Fourth, CPeLS platform realizes modularization of technology application. All the proposed technologies are integrated in a systematic platform and capsulated as services which can be invoked by different users easily and rapidly like using water and power in everyday life. Finally, the implementation of CPeLS platform is conducted through two major pilot cases in Hong Kong under configuration mode with both qualitative and quantitative evaluations.

possible way is to inform the industry of the potential in an effective way to achieve its wider applications. The scenarios identified in this work, animated later using FlexSim, can serve as a vehicle for better communicating the potential of CPS/IoT to logistics practitioners. Besides, the cost-benefit analysis of proposed platform is not covered in this study. There are two practical reasons. First, this project is funded by HKSAR Innovation and Technology Support Program. All enterprises participating in the project can use hardware and software facilities of CPeLS platform without any charges. Second, the pilot implementation in the proposed study is still in a small scale. The analysis of return on investment (ROI) of implemented services will be conducted in a later stage. To make continuous improvements to the CPeLS platform, it is recommended that future research should be carried out from several

In spite of its great potential, CPS and IoT technologies are slowly adopted in Hong Kong SMEs of ecommerce logistics industry. One Table 1 KPIs comparisons in UG case (before and after). KPIs

Before

After

Improvement

(1) (2) (3) (4) (5) (6) (7) (8)

5 min (fax and print) 5 min 2 min Handwriting 6.1% 1 Day 5 min > 1% No

1 min (check on the phone) 1 min 30 s Autowear recording < 0.03% Real-time 1 min < 0.03% Yes

500% 500% 400% Step-change Step-change 500% Step-change Step-change

Average time to record receiving orders Average time to do outbound Average time to do inbound Inbound order error rate Stocktaking time Order picking time Picked item error rate On-route tracing and tracking

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Fig. 13. Modular CPeLS solution and implementation for Tigers.

Fig. 14. Laboratory testing of smart consolidation solution before implementation.

aspects. First of all, it should create an effective and feasible business model in addition to technical improvements. Game theory-based revenue management approaches should be studied considering diverse stakeholders’ benefits in (virtual) ecommerce logistics chains. Secondly, a huge amount of transaction and operation data could be captured and collected during platform implementations. Such data carry rich implicit information and knowledge, which requires advanced technologies such as Big Data Analytics to give managerial insights and real-life practical guidance. Thirdly, the concepts and core technologies from this research could be extended into other industries such as pharmaceutical and retailing logistics, both of which could benefit from the efficiency, synergy and resource sharing philosophy offered by this innovative cloud solution. Lastly, the impact of new policies and regulations on CPeLS platform is also noteworthy. The cancel of geo-

blocking in European Union aims to make a stronger integrated European region. After the policy enforcement, prices of the same product tend to be the same in the European market. It will facilitate cross-border ecommerce, especially for SME enterprises. Under this new policy, CPeLS platform can be transplanted from Asia to Europe, which has already empowered logistics companies and shippers that serve cross-border ecommerce in Hong Kong. It can guarantee full logistics chain quality and timeliness; meanwhile, the management difficulty is also greatly reduced. It would be much better if effective trading mechanisms could be designed in CPeLS platform in future to directly match buyers and sellers, and hence a cross-border ecommerce ecosystem can be created finally.

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Table 2 KPIs comparisons from three deployed picking strategies in Tigers case. KPIs

Picking by order

Picking by order using industrial wearable

Smart consolidation

(1) Productivity speed (2) Operational accuracy (3) Data capturing capacity (4) Flexible and scalability (5) Hands-free operation (6) System costs (7) Progress tracing and tracking (8) Workflow reconfigurability

☆☆ ☆☆ ☆☆ ☆ ☆ ☆☆ ☆

☆☆☆ ☆☆☆ ☆☆☆☆ ☆☆☆ ☆☆☆☆☆ ☆☆☆ ☆☆

☆☆☆☆☆ ☆☆☆ ☆☆☆☆☆ ☆☆☆☆☆ ☆☆☆☆☆ ☆☆☆☆☆ ☆☆☆☆

☆

☆☆☆

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Acknowledgments This research is supported by the HKSAR ITC/LSCM R&D Center through the Innovation and Technology Support Program (Project Reference: ITP/079/16LP), the National Natural Science Foundation of China under grant 71801154 and Science Foundation for Youth Scholars of Shenzhen University under grant 2019070 & 189692. Acknowledgments are also given to Zhejiang Provincial, Hangzhou Municipal and Lin'an City Governments for partial financial supports. The Research Team is also grateful to the Federation of Hong Kong Industries, Hong Kong Logistics Association, Red Star Macalline Group Co. Ltd., Tigers (HK) Co. Ltd., The Union Gas Appliances (Holdings) Ltd. and several other pilot companies for supporting and participating in this research through the application of real projects. References Baheti, R., & Gill, H. (2011). Cyber-physical systems. The Impact of Control Technology, 12(1), 161–166. Boysen, N., de Koster, R., & Weidinger, F. (2018). Warehousing in the e-commerce era: A survey. European Journal of Operational Research.. Chen, J., Huang, G. Q., Luo, H., & Wang, J. (2015). Synchronization of production scheduling and shipment in an assembly flowshop. International Journal of Production Research, 53(9), 2787–2802. Fantini, P., Pinzone, M., & Taisch, M. (2018). Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems. Computers & Industrial Engineering.. Gou, H., Huang, B., Liu, W., & Li, X. (2003). A framework for virtual enterprise operation management. Computers in Industry, 50(3), 333–352. HKTDC Research (2015). Mainland cross-border e-Commerce opportunities for Hong Kong businesses. September 2015. http://china-trade-research.hktdc.com/businessnews/article/Research-Articles/Mainland-Cross-border-E-Commerce-Opportunitiesfor-Hong-Kong-Businesses/rp/en/1/1X3AYEO6/1X0A3HYN.htm (accessed on 10 Sept 2015). Huang, G. Q., Chen, M. Z., & Pan, J. (2015). Robotics in ecommerce logistics. HKIE Transactions, 22(2), 68–77. Kaasinen, E., Schmalfuß, F., Özturk, C., Aromaa, S., Boubekeuer, M., Heilala, J., ... Mehta,

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