Logistics 4.0. Applications, Trends and Challenges


Diploma Thesis, 2018
144 Pages, Grade: 1

Excerpt

Table of Contents

Preface

Acknowledgements

Table of Contents

List of Figures

List of Tables

Nomenclature

Abstract

Επιτελική Σύνοψη

Chapter 1 Introduction
1.1 The Role of Information Technology in Logistics Operations
1.2 Scope and Objectives of the Thesis
1.2 Methodology
1.4 Thesis Outline

Chapter 2 Logistics Operations: Processes and Characteristics
2.1 Introduction
2.2 Supply Chain and Logistics Management
2.3 Warehousing and Storage
2.3.1 The role of a Warehouse
2.3.2 Warehouse Operations
2.3.3 Receiving and Storing
2.3.4 Replenishment and Order Picking
2.3.5 Packing
2.3.6 Dispatching
2.3.7 Warehouse Management System
2.4 Transportation
2.4.1 Transport Modes
2.4.2 Line Haul Transportation
2.4.3 City Logistics/Last Mile Delivery
2.4.4 Fleet Management
2.4.5 Routing and Scheduling
2.4.6 Information Systems in Freight Transportation
2.5 Reverse Logistics
2.5.1 Reverse Logistics Process
2.5.2 Priorities and Issues
2.6 Issues and Challenges
2.6.1 Higher Customer Demands
2.6.2 Organizational Structures
2.6.3 Globalization
2.6.4 Startups and Logistics Industry Disruption
2.6.5 The Rise of E-Commerce
2.6.6 Cybersecurity
2.7 Summary

Chapter 3 Industry
3.1 Background
3.1.1 Industry
3.1.2 Industry
3.1.3 Industry
3.2 Industry
3.2.1 Necessity for Industry 4.0 Technologies
3.2.2 Issues raised from Industry 4.0 Adoption
3.2.3 Issues arising in HR Sectors
3.2.4 New Organizational Structures
3.3 Logistics 4.0 and Emerging Technologies
3.3.1 Internet of Things (IoT)
3.3.2 Big Data
3.3.3 Advanced Robotics
3.3.4 Augmented Reality (AR)
3.3.5 Unmanned Aerial Vehicles
3.4 Summary

Chapter 4 Industry 4.0 on Logistics Operations
4.1 Introduction
4.2 IoT and its Applications on Logistics Operations
4.2.1 IoT in Warehouse Operations
4.2.2 IoT Applications on Freight Transportation
4.2.3 IoT-enabled Last-Mile Delivery
4.3 Big Data in Logistics
4.3.1 Data-Driven Business
4.3.2 Big Data for Greater Customer Service
4.3.3 Big Data Analytics and Fleet Management
4.4 Advanced Robotics in Logistics Operations
4.4.1 Robotics in Warehouse Operations
4.4.2 Robotics revolutionizing Distribution and Delivery
4.5 Unmanned Aerial Vehicles in Logistics Operations
4.5.1 UAVs Intralogistics Applications
4.5.2 UAVs for Security in Large-Scale Facilities
4.5.3 UAVs in Urban Delivery
4.5.4 UAVs in Rural Delivery
4.6 Augmented Reality in Logistics Operations
4.6.1 Augmented Reality in Warehouse Operations
4.6.2 AR in Freight Transportation
4.6.3 AR in Delivery
4.7 Logistics 4.0 Implementation Framework
4.7.1 The Framework
4.7.2 The Emerging Challenges
4.7.3 Implementing UAVs for Inventory Management
4.8 Summary

Chapter 5 Case Studies in Logistics Operations
5.1 Introduction
5.2 Case Study 1: Bobcat and SmartLIFT Technology
5.2.1 The Challenge
5.2.2 The Solution
5.2.3 The Results
5.3 Case Study 2: DHL’s Weighing Forks on a Forklift Truck
5.3.1 The Challenge
5.3.2 The Solution
5.3.3 The Results
5.4 Case Study 3: Vision Picking at the Inter Arizona Distribution Center
5.4.1 Vision Picking vs RF Picking at the Intel Arizona Distribution Center
5.4.2 The Results
5.5 Case Study 4: DHL’s Dynamic Inventory Control
5.5.1 The Challenge
5.5.2 The Solution
5.5.3 The Results
5.6 Case Study 5: The InventAIRy Project by Fraunhofer IML
5.6.1 The Challenge
5.6.2 The Solution
5.6.3 The Benefits
5.7 Case Study 6: Maintenance on Demand (MODE)
5.7.1 The Logistics Challenge
5.7.2 The Solution
5.7.3 The Benefits
5.8 Case Study 7: DHL and the SmartTruck
5.8.1 The Challenge
5.8.2 The Solution
5.8.3 The Benefits
5.9 Case Study 8: UPS Leveraging Big Data Analytics
5.9.1 UPS Big Data Projects
5.9.2 Results and Goals
5.10 Case Study 9: Jack in the Box investing in Delivery Robots
5.10.1 Investment in Autonomous Delivery Robots
5.10.2 Future Investments
5.11 Case Study 10: Amazon’s Drone Deliveries
5.11.1 Investing in UAVs
5.11.2 Advantages
5.12 Summary

Chapter 6 Conclusions
6.1 Main Findings
6.2 Conclusions
6.3 The Way Forward

References

List of Figures

Figure 1.1 A flow chart depicting the methodology followed in the Master thesis

Figure 2.1 Logistics Management as a crucial part of Supply Chain Management. (IIBM LMS, 2018)

Figure 2.2 The functions listed above sorted by chronology (Rightwarehouse.com, 2018)

Figure 2.3 WMS adds the element of automation to warehouse operations, thus increasing productivity and efficiency (Schmidthk.com, 2018)

Figure 2.4 Freight transport mode of choice by percentage worldwide (SAFETY4SEA., 2018)

Figure 2.5 A geographical view of urban logistics, comprised of city logistics, urban goods distribution and last mile delivery (Malindretos, 2015)

Figure 2.6 The reverse logistics process (Bentz, 2015)

Figure 2.7 Global Retail E-commerce sales growth through the years (Vupune.ac.in., 2018)

Figure 3.1 Cost reduction percentage expected for companies investing in digitalization by 2020, grouped by industry (PwC, 2016)

Figure 3.2 Graph showing the amount connected devices, showcasing the fact that there is still a lot more to be seen (Bicheno, 2015)

Figure 3.3 Big Data analytics' worldwide revenue based on a survey by IDC (Shirer and Goepfert, 2017)

Figure 3.4 Projected size of AR market in 2022 compared to 2018 based on a survey conducted by IDC (Murray, 2018)

Figure 3.5 Expected Global Drone Spending for 2017-2021 based on a survey conducted by Goldman Sachs, grouped by Country (Goldman Sachs, 2018)

Figure 4.1 The IoT “ecosystem”, comprised of three main components, which are sensor-embedded objects, wireless networks and information systems

Figure 4.2 The IoT-enabled warehouse, with multiple applications, such as condition monitoring, smart inventory management, smart ventilation etc. (Hector, 2018)

Figure 4.3 An RFID tag stores data regarding the object it is embedded to electronically. The wireless reader tracks and identifies the tag with the use of electromagnetic fields (West, 2017)

Figure 4.4 Displays how IoT revolutionizes transportation operations by featuring all of the advantages and capabilities discussed above: Monitoring of vehicle condition status, the driver’s vitals, shipment ID reporting etc. (Macaulay et al., 2015)

Figure 4.5 Shows how IoT redefines last-mile delivery. Features displayed: a) Automatic order placement, b) flexible address, c) delivery notification, d) returned goods request, e) collection route optimization (Macaulay et al., 2015)

Figure 4.6 The large datasets are decomposed and broken down into smaller datasets in order to be properly processed, which is the mapping process. Mapping is followed by the Reduce phase, where results are combined to produce powerful insights (Ali et al., 2016)

Figure 4.7 The Big Data ecosystem, starting from the retrieval of data from multiple data sources and reaching to powerful insights

Figure 4.8 Goods to picker technology: Kiva moving a collection of items (Kim, 2015)

Figure 4.9 Fetch and Freight enabling full automation of the picking operation and offering a picker-to-goods solution (IEEE Spectrum, 2015)

Figure 4.10 Baxter, designed by Rethink Robotics Company, assists in packing and sorting activities and tasks (Balinski, 2014)

Figure 4.11 Based on electric power to function, exoskeleton support for workers aids them in day-to-day tasks or heavy and large item carrying. Such exoskeleton support is developed by Panasonic (Burgess, 2016)

Figure 4.12 The DHL parcel Robot is a prototype developed by DHL and associates (Bonkenburg, 2016), which assists in unloading and loading of goods (I-scoop.eu, 2018)

Figure 4.13 UAVs developed by MIT researchers can read RFID tags using existing RFID-reading systems in the warehouse, meaning that there is no need for them to carry a reader (Lumb, 2017)

Figure 4.14 An example of the AR headset displaying information regarding shelf number, barcode, aisle, stock numbers etc. (Hci.vt.edu, 2018)

Figure 4.15 Displays the AR headset worn by workers and shows its features, such as the display and the camera (Intel, 2015)

Figure 4.16 The Framework a company should follow in order to successfully implement Logistics 4.0 technologies

Figure 4.17 Displaying the issues and challenges of the Logistics 4.0 implementation (Gialos and Zeimpekis, 2018; Barreto et al., 2017)

Figure 4.18 Framework about UAVs implementation for Inventory Management

Figure 5.1 Showing the locations of the individual supporting technologies on a TELEHANDLER BOBCAT V417 (onestoprentalsales.com, 2018)

Figure 5.2 The RWV weighing forks (Ravas, 2018)

Figure 5.3 The differences between the two picking methods were reported by workers with the flexibility and efficiency that the smart glasses offer being unanimously applauded (Intel, 2015)

Figure 5.4 The information on the right concerns the aisle and the shelf for locating the item, while the information on the left concerns the item code, the quantity to be retrieved and the delivery note to be put on the box (Intel, 2015)

Figure 5.5 The InventAIRy Bonn Test Copter (Ais.uni-bonn.de, 2016)

Figure 5.6 The InventAIRy copter in a Panopa Logistik warehouse (Ais.uni-bonn.de, 2016)

Figure 5.7 Many collaborating partners offered their expertise in developing the MODE project. As seen in this figure, the damper system, the fuel injector and the oil system have been embedded with sensors which send the data to the central system, which sequentially transmits them to a remote user (Avonwood, 2013)

Figure 5.8 The delivery robot, called Happy, developed by DoorDash and Marble (Mashable, 2017)

Figure 5.9 The octocopter utilized for the Prime Air service by Amazon (Spary, 2015)

List of Tables

Table 2.1 A summary of the picking methodologies seen in this chapter (Rushton et al., 2014)

Table 2.2 A comparative table for Voice, Light and RF scanner picking technologies currently used (bcpsoftware.com, 2018)

Table 2.3 Comparing modes of transport across four crucial variables

Table 3.1 History of Industrial Revolutions (Collins, 2017; Hammel Scale, 2018)

Table 3.2 Issues raised from Industry 4.0 adoption (Renjen, 2018)

Table 3.3 Emerging technologies of Logistics 4.0 (DHL, 2015; Oracle, 2018; Malek et al., 2017)

Table 4.1 IoT subsidiary technologies and their uses in Logistics Operations (Macaulay et al., 2015; Zhong et al., 2017)

Table 4.2 Compares RFID tags to Barcodes utilization in the warehouse

Table 4.3 The impact and the results of implementing IoT-based solutions (Newcastle Systems, 2017; Datex, 2018; Zhong et al., 2017; Gregor et al., 2017; Macaulay et al., 2015)

Table 4.4 Describing the impact of IoT technologies on freight transportation (Deloitte, 2018; Macaulay et al., 2015; Malek et al., 2017; Zhong et al., 2017)

Table 4.5 Comparison between Data Warehouse and Big Data

Table 4.6 How Big Data affect the way logistics companies do business (Anshari et al., 2018; Kirkos, 2015; Malek et al., 2017)

Table 4.7 Describing Big Data’s impact on customer service (Jeske et al., 2013; Anshari et al., 2018)

Table 4.8 How Big Data Analytics affect fleet management and enables new features and capabilities (Jeske et al., 2013; Ben Ayed et al., 2015)

Table 4.9 The logistics operations to be discussed, revolutionized by advanced robotics

Table 4.10 Comparative table of three last-mile delivery methods, delivery cars, e-cargo bikes and delivery robots

Table 4.11 How advanced robotics revolutionize Logistics operations (Burgess, 2018; Romeo, 2017)

Table 4.12 Compares conventional inventory management to smart inventory management with the utilization of UAVs

Table 4.13 Displaying UAVs' impact on Logistics operations (DHL, 2014; Sandle, 2017; Trebilcock, 2018)

Table 4.14 The logistics operations to be discussed, revolutionized by AR

Table 4.15 Compares picking technologies and showcases how AR-based vision picking is superior

Table 4.16 Describing the benefits for integrating AR in warehouse operations (Glockner et al., 2014; Stoltz et al., 2017; Merlino and Sproge, 2015)

Table 4.17 Describing how AR revolutionizes freight transportation operations and what are the benefits (Glockner et al., 2014; Merlino and Sproge, 2015)

Table 4.18 Compares GPS to VPS

Table 4.19 Presenting AR's application for last-mile delivery (Glockner et al., 2014)

Table 4.20 Summarizing the technologies that drive logistics operations towards automation and digitalization (Gialos and Zeimpekis, 2018; Noronha et al., 2016)

Table 5.1 Displaying the case studies to be reviewed and which technologies are present in each situation

Table 5.2 Comparing warehouse operations pre and post smart weighing forks installation (Ravas, 2018)

Table 5.3 Displaying how UAVs transform inventory management (Federal Ministry for Economic Affairs and Energy, 2015)

Nomenclature

Abbildung in dieser Leseprobe nicht enthalten

Abstract

Current logistics operations and information systems used cannot deal with the emerging challenges. Globalization, the rise of e-commerce, cyberthreats, cumbersome organizational structures, startups disrupting the business landscape and constantly higher customer demands push companies into adopting emerging technologies which enable them to increase digitalization and automation.

These challenges have been exploiting the limits of currently utilized warehouse technologies and practices, highlighting the inefficiencies that exist. As for freight transportation, fleet management systems and routing software solutions are utilized at a great extend and success already, but one thing highlighted through the case studies analysis is the necessity for real-time monitoring and visibility throughout the goods’ journey from dispatching to the customer.

The fourth industrial revolution, Industry 4.0, enables companies to proceed in digitalizing their operations, as building a flexible organizational structure is a challenge that needs to be addressed and adopting the digital enterprise model is a crucial step before implementing the new age technologies, as companies must add the elements of flexibility and adaptability in order to deal with the challenges at hand.

Logistics 4.0, a term derived from the combination of Industry 4.0 technologies and innovations and their application on inbound and outbound logistics is a narrower concept than Industry 4.0, as it focuses on typical features, such as automation and digitalization. The technologies most commonly utilized are the Internet of Things (IoT), Big Data analytics, Augmented Reality (AR), Unmanned Aerial Vehicles (UAVs) and Advanced Robotics. IoT is the pinnacle of those technologies, as it enables new data streams creation from sources previously being non-exploitable and allows companies to monitor and control mechanizations, fleets etc. by a central system. Big Data analytics provide a powerful tool to companies, as the new data streams generated by IoT produce much greater amounts of data which common software cannot process. Advanced Robotics revolutionize logistics operations due to increasing automation. AR offers numerous advantages for warehouse workers distributors. Lastly, UAVs present a revolutionary technology in many different ways as they possess a wide array of applications, such as facility patrolling, warehouse assistance, stock counting and last-mile delivery.

The Master thesis presents a framework that companies may follow for a Logistics 4.0 technologies implementation. The framework presents five necessary phases for the implementation, enabling the company to properly deal with the challenges that emerge. Resistance to change, high investment costs, HR-related issues, data privacy issues, IT infrastructure requirements, the public’s opinion about revolutionary technologies and regulations are challenges that must be dealt with for the implementation to be smoothly completed.

The case studies analysis that follows showcase the advantages and benefits of implementing Logistics 4.0 technologies. Finally, the outcome of the Master thesis is that the framework may be tested in a real-world environment for further research on the subject.

Επιτελική Σύνοψη

Η υφιστάμενη κατάσταση στον τομέα των λειτουργιών των Logistics και τα πληροφοριακά συστήματα που χρησιμοποιούνται δεν μπορούν να αντιμετωπίσουν τις προκλήσεις που προκύπτουν. Η παγκοσμιοποίηση, η άνοδος του ηλεκτρονικού εμπορίου, οι απειλές εκ του διαδικτύου, οι πολύπλοκες οργανωσιακές δομές, οι νεοσύστατες επιχειρήσεις που διαταράσσουν το επιχειρηματικό τοπίο και οι συνεχώς υψηλότερες απαιτήσεις των πελατών ωθούν τις εταιρείες στην υιοθέτηση αναδυόμενων τεχνολογιών που τους οδηγούν προς την ψηφιοποίηση και την αυτοματοποίηση.

Αυτές οι προκλήσεις φανερώνουν τις αδυναμίες των υφιστάμενων τεχνολογιών που χρησιμοποιούνται στην αποθήκευση. Όσον αφορά τις εμπορευματικές μεταφορές, τα συστήματα διαχείρισης στόλου και οι λύσεις λογισμικού δρομολόγησης χρησιμοποιούνται ήδη σε μεγάλη έκταση και με επιτυχία, αλλά ένα πράγμα που επισημαίνεται στην ανάλυση μελετών περίπτωσης είναι η αναγκαιότητα παρακολούθησης και ορατότητας σε πραγματικό χρόνο καθ’όλη τη διάρκεια του ταξιδιού των εμπορευμάτων μέχρι τον πελάτη.

Η τέταρτη βιομηχανική επανάσταση, εν συντομία Industry 4.0, επιτρέπει στις επιχειρήσεις να προχωρήσουν στην ψηφιοποίηση των λειτουργιών τους, καθώς η δημιουργία μιας ευέλικτης οργανωτικής δομής και η υιοθέτηση του ψηφιακού επιχειρηματικού μοντέλου είναι ένα κρίσιμο βήμα πριν την εφαρμογή αναδυόμενων τεχνολογιών.

Τα Logistics 4.0, ένας όρος που προκύπτει από το συνδυασμό των τεχνολογιών και καινοτομιών του Industry 4.0 και της εφαρμογής τους στις εισερχόμενες και εξερχόμενες λειτουργίες logistics, επικεντρώνεται σε τυπικά χαρακτηριστικά όπως αυτοματοποίηση και ψηφιοποίηση. Οι τεχνολογίες που χρησιμοποιούνται συνήθως είναι το Διαδίκτυο των πραγμάτων (IoT), τα Big Data analytics, η επαυξημένη πραγματικότητα (AR), τα μη επανδρωμένα σκάφη (UAVs) και η προηγμένη ρομποτική. Το IoT επιτρέπει τη δημιουργία νέων ροών δεδομένων από πηγές οι οποίες προηγουμένως ήταν μη εκμεταλλεύσιμες, καθώς και την παρακολούθηση και τον έλεγχο μηχανισμών, στόλων κλπ. από ένα κεντρικό σύστημα. Τα Big Data αποτελούν ένα ισχυρό εργαλείο για τις εταιρείες, καθώς οι νέες ροές δεδομένων που παράγονται από το IoT παράγουν πολύ μεγαλύτερα σετ δεδομένων τα οποία δεν μπορούν να επεξεργαστούν με χρήση κοινού λογισμικού. Η προηγμένη ρομποτική φέρνει την επανάσταση στις λειτουργίες logistics λόγω της αύξησης της αυτοματοποίησης. Το AR προσφέρει πολυάριθμα πλεονεκτήματα στους εργάτες μίας αποθήκης, καθώς και στους διανομείς. Τέλος, τα UAVs διαθέτουν ευρύ φάσμα εφαρμογών, όπως περιπολία εγκαταστάσεων, απογραφές και παράδοση τελευταίου μιλίου.

Η μεταπτυχιακή εργασία παρουσιάζει ένα πλαίσιο το οποίο οι εταιρείες μπορούν να ακολουθήσουν για την εφαρμογή τεχνολογιών Logistics 4.0. Το πλαίσιο αυτό παρουσιάζει πέντε απαραίτητες φάσεις για την εφαρμογή, επιτρέποντας στην εταιρεία να αντιμετωπίσει σωστά τις αναδυόμενες προκλήσεις. Η αντίσταση στην αλλαγή, το υψηλό κόστος επένδυσης, τα θέματα που σχετίζονται με το ανθρώπινο δυναμικό, τα ζητήματα ιδιωτικού απορρήτου των δεδομένων, οι απαιτήσεις σε λογισμικό και υλισμικό, η γνώμη του κοινού σχετικά με τις επαναστατικές τεχνολογίες και οι νομοθεσίες αποτελούν προκλήσεις που πρέπει να αντιμετωπιστούν για την ομαλή ολοκλήρωση της εφαρμογής τεχνολογιών Logistics 4.0.

Η ανάλυση των μελετών περίπτωσης που ακολουθεί μετέπειτα, παρουσιάζει τα πλεονεκτήματα και τα οφέλη της εφαρμογής τεχνολογιών Logistics 4.0. Τέλος, προτείνονται τρόποι αξιοποίησης του πλαισίου που αναπτύχθηκε σε αυτή την μεταπτυχιακή εργασία με τεστάρισμα του σε αληθινό περιβάλλον.

Chapter 1 Introduction

Supply chain management has been continuously becoming more complex (Doz, 2017). There is a need for faster and more individualized services due to the increased customer demand regarding delivery time and availability (Witkowski, 2017). Furthermore, globalization keeps on being a significant drive, security awareness has become a trend due to cyber threats, social and environmental challenges emerge (e.g. the aim for less CO2 emissions) (DHL, 2016) and the rise of e-commerce pushes companies to consider integrating emerging technologies which shall drive them towards digitalization and innovation (Doz, 2017). However, companies should consider making fundamental changes to their organizational structures in order to prioritize the optimization of their logistics operations and add elements such as flexibility and adaptability in order to insert smoothly into the digital age and implement emerging technologies (Noronha et al., 2016). Industry 4.0 and especially Logistics 4.0 (i.e. technologies that support the digital transformation of logistics operations) facilitate those changes and allow companies to completely digitize and automate several operations and processes.

1.1 The Role of Information Technology in Logistics Operations

The role of Information Technology has become more critical nowadays than ever before due to the need for digitalization and innovation being more prominent. Logistics operators and companies with in-house logistics have been using technological aids and systems such as Voice Picking, Warehouse Management Systems, Fleet Management Systems, Routing software solutions, etc., however these technologies and systems cannot always face challenges, such as the aforementioned globalization, cyber-threats, e-commerce’s rise and increased customer demands (Baretto et al., 2017). For example, a worker wearing the voice-picking wearables still has to hold a handheld scanner and wears a ring-scanner in order to confirm his every move, thus reducing his productiveness.

Logistics 4.0 offers a solution, in most cases, as its technologies facilitate greater digitalization and automation in logistics operations, such as the above, thus driving companies towards the digital age with increased capabilities for innovation (Hülsmann, 2015). As a result, Logistics 4.0 can be defined as a data-driven logistics concept in which individual subsystems interwind and communicate in order to create a digital network that enables increased efficiency and productivity (Szymanska et al., 2017). It operates under the same principles as Industry 4.0, but with different component parts, as it utilizes smart means, such as containers, vehicles, pallets, and transportation systems. By creating the digital network, Logistics 4.0 offers supply chain managers, shippers, drivers, freight forwarders etc. real-time visibility and traceability, thus enabling the optimization of logistics operations, such as warehousing and freight transportation (Hoey, 2018). A digital supply chain produces immediate results which can be seen due to real-time data processing offering greater and more responsive insights (PwC, 2016). For example, in an IoT-based warehouse all goods are embedded with sensors, so that managers can monitor their condition (e.g. temperature) and location, which means that if a product was on the verge of being damaged managers would know early enough to develop countermeasures and take precautions (Hoey, 2018).

Other technological applications such as Augmented Reality devices (e.g. for Vision picking) can recognize the surroundings and display visual information to the operator while enabling scanning without a handheld device, thus reducing travel time through the warehouse and decreasing the risk for injury while simultaneously optimizing the worker’s productivity, making vision picking faster than other picking technological aids (DHL, 2015; Goettler, 2018). Another revolutionary technology which was briefly mentioned above is The Internet of Things and its subsidiary technologies, such as sensor technology, with the ability to connect individual components of the supply chain together into a central system in order to enable digitalization and optimize processes (Macaulay et al., 2015). IoT enables the creation of multiple data streams which results in a more massive amount of data being available, which deems Big Data analytics the most suitable solution, as it enables real-time data processing of datasets much bigger in variety, velocity, volume and size, thus optimizing decision making and generating greater insights (Jeske et al., 2013). Advanced Robotics can streamline day-to-day processes and tasks in the warehouse, while they can aid in optimizing package delivery (Bonkenburg, 2016). Finally, unmanned aerial vehicles (UAVs) present an opportunity to totally transform delivery processes, while enabling intralogistics applications, such as facility overwatch and labor assistance (DHL, 2014).

1.2 Scope and Objectives of the Thesis

The main scope of this Master thesis is threefold: a) review the current logistics operations with emphasis on the Information Systems used, b) investigate how logistics operations may be transformed by adopting logistics 4.0 technologies such as IoT, Big Data, Advanced Robotics, Augmented Reality, and UAVs and, c) propose a framework that a company may follow in order to digitally transform its logistics operations and then showcase an application of that framework for an implementation of UAVs in a warehouse.

The individual objectives of the thesis are as follows:

1- Review the current status of warehouse and freight transportation operations.
2- Present current information systems used in logistics operations and examine their inefficiencies, thus highlighting the need for Logistics 4.0 technologies.
3- Make an in-depth explanation of emerging Logistics 4.0 technologies and determine in which way they may revolutionize warehouse and freight transportation operations.
4- Examine ten (10) individual case studies in which companies have successfully implemented the technologies mentioned above and showcase their results.
5- Propose a framework of how warehouse and transport operations can be transformed via Logistics 4.0 technologies and showcase an example of applying the framework for the implementation of UAVs for inventory management and facility patrolling.

1.2 Methodology

The methodology that was followed for the preparation of this Master thesis is as follows:

The first step was to describe all the strengths and weaknesses of current logistics operations, how they are performed and present the information systems used along with their inefficiencies, as well as the technologies utilized. It is evident that warehouse operations are still largely manual in nature with many workers spending valuable labor time in repetitive tasks and activities, thus decreasing productivity and operational efficiency (Bonkenburg, 2016). On the other hand, freight transportation has accepted automation at a faster rate, although implications regarding routing, scheduling and last-mile delivery are still posing as a huge challenge (Malindretos, 2015).

The next step was to present and describe emerging Industry 4.0 technologies and their application on logistics operations (i.e. Logistics 4.0 technologies in warehousing and freight transportation). The emerging technologies mentioned above have the potential to drive the logistics industry towards digitalization and automation, which will sequentially lead to increased productivity and operational efficiency (Noronha et al., 2016).

Then, a framework under which companies need to operate in order to adopt Logistics 4.0 technologies was developed with an example of the framework in a UAVs warehouse implementation. Finally, ten (10) case studies were chosen to be examined, five (5) regarding warehousing and five (5) regarding freight transportation, which showcase the effectiveness and impact Logistics 4.0 technologies have on logistics operations.

Abbildung in dieser Leseprobe nicht enthalten

Figure 1. 1 A flow chart depicting the methodology followed in the Master thesis.

1.4 Thesis Outline

The master thesis is comprised of six (6) main chapters. Each chapter’s content is analyzed as follows:

The first chapter is a general introduction to the main theme of the thesis. The methodology followed throughout the Master thesis is presented.

The second chapter is examining currently performed logistics operations and information technology systems utilized. An analysis of the technologies used was also performed, showcasing their limitations.

The third chapter is a historic review of the industrial revolutions and a more comprehensive introduction to the Logistics 4.0 technologies mentioned above. Each industrial revolution is described, leading up to Industry 4.0.

The fourth chapter is a more in-depth analysis of how Logistics 4.0 technologies revolutionize warehouse and freight transportation operations. A framework for Logistics 4.0 adoption was also developed with an application displayed, regarding the implementation of UAVs for inventory management and warehouse patrolling.

In the fifth chapter, ten (10) case studies were analyzed, five (5) dealing with warehouse operations and five (5) regarding freight transportation. The outcome of implementing Logistics 4.0 technologies is reviewed in each case.

Finally, the sixth chapter summarizes the advantages of implementing these emerging technologies and reviews the conclusions of the Master thesis, as well as the way forward for the logistics industry.

Chapter 2 Logistics Operations: Processes and Characteristics

2.1 Introduction

Technology is evolving in a very fast rate and along with it supply chain and logistics management need to constantly adapt in order to enable the integration of new technologies and practices. Current logistics operations have their advantages, but the increasingly higher customer demands, globalization, the need for reformed organizational structures, startups constantly innovating with new business models to disrupt the logistics industry, the rise of e-commerce and cybersecurity awareness are all great issues demanding attention, thus challenging the way logistics companies do business.

In this chapter we will do a thorough review of the way warehouse and transportation operations and processes are handled, the information systems that connect those processes together and enable better flow of information and the technologies that accompany those information systems, leading in improved efficiency in warehouse and transportation operations. Finally, we will bring forth the issues that have emerged in the last decade, specifically the ones above, and explain how they increase the need for companies and organizations to incorporate Logistics 4.0 technologies and practices.

2.2 Supply Chain and Logistics Management

Logistics, as a term, was first used in military operations. “Strategy is art of handling troops in the theatre of war; tactics that of handling them on the field of battle… The French have a third process, which they call logistics, the art of moving and quartering troops…” (Lummus, Vokurka and Krumwiede, 2001). Today we use that term in a different sense. We define logistics as the management of the flow of goods from the point of origin to the point of consumption, given that the requirements of the consumer are met, with the involvement of information processing being a lot more prominent these days.

Supply chain management (SCM) is a much broader term including all the logistics processes mentioned above and is used to define all inbound and outbound logistics processes, linking all the different departments of the company and external partners (e.g. 3PLs), information systems providers, suppliers and carriers. It is a network of organizations and companies, dependent on each other, utilizing their combined expertise in order to manage and monitor the flow of goods and information from the supplier to the end user (Christopher, 2011), coordinating processes across finance, marketing, sales, production and information technology (IT) (CSCMP, 2018).

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Figure 2.1 Logistics Management as a crucial part of Supply Chain Management. (IIBM LMS, 2018).

For industries, logistics support the optimization of production and distribution processes based on a variety of resources through management techniques for promoting the efficiency and competitiveness of enterprises (Tseng, Yue, & Taylor, 2005). Logistics can be described as a two-parter channel as follows:

1. The physical channel

Logistics services support the movement of materials and products from the point of production to the point of consuming, as well as associated waste disposal and reverse flows. These services are comprised of physical activities (e.g. receiving, storing, order picking, transportation etc.) (Galindo, 2016).

2. The information channel

The uninterrupted flow of goods is naturally dependent on the correct flow of information, ranging from the procurement procedures to last-mile delivery processes (Galindo, 2016). The physical and the information channels are interdependent and that is why physical activities would be unable to be completed without information processing, which showcases the connection between the two and their importance in today’s digital world.

2.3 Warehousing and Storage

The warehouse has evolved from the perception of being a repository to forming an integral part of the supply chain, as it is involved in numerous stages of sourcing and production, all the way up to distribution and delivery, ranging from the handling of raw materials to the distribution of finished products to the end customer (Rushton et al., 2014).

Warehouses can be grouped by type, depending on their importance and nature within the supply chain (Christopher, 2011) as seen below:

1- Their Function
2- Segmentation
3- Stage in the Supply Chain
4- Product Type
5- 3PL owned or Private owned
6- Covering Area
7- Whether they are Manual or Automated in Nature
8- By Height

2.3.1 The role of a Warehouse

The prime objective of a warehouse is to support the uninterrupted movement of goods through the supply chain to the end customer (Rushton et al., 2014). In past decades, warehouses were viewed as stockholding points in an attempt to match supply and demand, while also acting as a buffer between manufacturers and wholesalers, resulting in limited stock visibility and a slow flow of information (Richards, 2018). This resulted in companies and organizations keeping excess amounts of stock in warehouses, with a negative effect on operational, holding and logistic costs.

Holding inventory is a crucial role of the warehouse as it affects a number of operations and activities, such as better customer service and prevention of the fluctuation of demand affecting production and sales, while also being of great importance to the costs written above. This leads us to another role a warehouse performs, which is the role of the consolidation center, bringing together several product lines which customers would rather have delivered together than separate (Richards, 2018). Warehouses also perform as distribution centers, which can be defined as specialized buildings stocked with products which are to be distributed to retailers, costumers etc. (Supply & Demand Chain Executive, 2008).

Another vital role a warehouse performs is to serve as a trans-shipment point, basically used for serving outlying regions of a country. Small warehouses are used for sortation into small vehicle loads, which are then ready for delivery (Ballou, 2014).

Finally, the role of the returned goods center is vital to reverse logistics operations and processes, handling returned goods in an efficient and environment-friendly way. Reverse logistics have been of a continuously increasing importance due to the rise of e-commerce, along with a drive for environmental legislation (Bentz, 2015), in which product lines, single products or a batch of goods sometimes are retrieved from a point within the supply chain as damaged, expired, or to be re-manufactured (Rosier and Janzen, 2008).

2.3.2 Warehouse Operations

For a warehouse to perform efficiently, nine principles should be followed (Malindretos, 2015):

1- Automation
2- Customer Service
3- Ergonomics
4- Flexibility
5- Identification of Demand
6- Space Utilization
7- Systems Control
8- Unit Load
9- Work Productivity

Typical functions, seen among manual and automated warehouses are as follows:

1- Receiving: Incoming transported goods are received and identified, with the support of an information system.
2- Put-Away: Goods are then transferred to pre-defined, or not, reserve storage areas, which normally hold the largest amount of inventory.
3- Order Picking: The process of extracting goods from picking slots.
4- Sorting: When multiple orders are received, it is beneficiary to pick them all at once and have them sorted out later, before dispatching.
5- Packing: Goods need to be assembled or packed together after picking. This process may involve added value services, such as kitting and labelling (Malindretos, 2015).
6- Dispatching: Goods are marshalled together to form vehicle loads which are then loaded to outbound vehicles in order to move onto the next node in the supply chain (Rushton et al., 2014).

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Figure 2.2 The functions listed above sorted by chronology (Rightwarehouse.com, 2018).

2.3.3 Receiving and Storing

Warehouse operations can be paralleled to a chain. This means that if all subsequent activities are successful, then processes are carried out more efficiently. Receiving processes is the first piece of that chain of processes and should be carefully planned out, as several tasks need to be done with precision and agility (Ballou, 2014). The prime objective of a correctly designed receiving process is to proceed to the put-away process with minimum effort and time spent, which is why logistics companies are so keen on constantly innovating and optimizing their practices and methods.

Upon unloading, goods are checked for their condition (e.g. temperature), quantity and quality. Poor quality (e.g. for loose packages) is dealt with by re-palletizing. A common method used is the transmitting of an advance shipping notice (ASN) by electronic data interchange (EDI) in order to be linked to the corresponding purchase order. The goods are then cross-checked against the ASN for that vehicle (Rushton et al., 2014). It should be noted that most warehouses book incoming vehicle loads in advance in order to support the correct allocation of resources to the activity and optimize receiving processes.

Storing is the next step after goods have been received and sorted. Unit loads must be checked before put-away (e.g. Palletized products are weighed, and dimension checked) to exclude pallets that don’t fill the requirements and send them for manual rectification (Rushton et al., 2014).

2.3.4 Replenishment and Order Picking

The process that succeeds receiving and put-away processes is the replenishment of the picking face. This process’s effect on accuracy and efficiency is of great importance, as an order depends on the replenishment of the picking slots for the operations to proceed as they would (Rushton et al., 2014). Should the replenishment process not occur, the order requiring the stock keeping unit (SKU) cannot be completed (Rushton et al., 2014). Various methods of checking the quantities left can be used for replenishment to take place, although defining an exact amount of quantity of goods left as a trigger point increases the risk of either replenishing too soon, or too late. That is the kind of situation in which a real-time computer system aids in replenishing at the right time with the right amount of quantity.

Storage is followed by order picking, a key warehouse operation that accounts for about 55% of the labor costs (Aalhysterforklifts.com.au., 2013). Its main objective is the extraction of specific goods from inventory to form a shipment with three key principles in mind: accuracy, good or higher quality and punctuality (Rushton et al., 2014). In very specific cases (e.g. an order of pallet quantities), the goods are directly pulled from the reserve storage areas and moved directly to the marshalling area.

In terms of what percentage each operation is still manual, order picking comes first by far, as it has the higher percentage of manual effort out of all the warehouse operations. That is why many technological advancements have been centered around aiding in the order picking processes, such as voice-picking and light-picking, technologies which are utilized alongside a warehouse management system and other information systems in an attempt to boost productivity and accuracy.

Picking productivity is mostly relying on four main factors (Rushton et al., 2014):

1- Information Technology
a. -Information Systems in the Warehouse
b. -Technological Aids such as Voice Picking or RF-scanner

2- Equipment
a. -Type of Trucks
b. -Whether there is Ground-Level or high-Level Picking
c. -Category of Picking Process (e.g. picker-to-goods or goods-to-picker)

3- Management
a. -Replenishment and Storage
b. -Industrial Relations
c. -Workload Balance
d. -Leadership

4- Operational Requirements
a. -Scale of Operation
b. -Size of Items
c. -Product Range
d. -Specific Requirements (e.g. barcodes)
e. -Items per Order

Various picking methodologies have been applied through the years, each being suitable for specific order requirements such as size, volume and product characteristics (Ballou, 2014). Discrete order picking is the most common for its simplicity mostly, where the picker pulls one order, one line at a time. Orders are not scheduled and may be picked anytime during a shift on a particular day. Although simple and easy to understand, this method has a serious disadvantage when it comes to travel time, deeming it inefficient in most cases (Wheeler, 2018).

Zone picking is a methodology in which the warehouse is split in zones, where order pickers are dedicated to their respective zone. Typically, a warehouse management system (WMS) examines each order line and identifies where the picking the face for that specific SKU is located (Rushton et al., 2014). A serious disadvantage of this method is the possibility of one zone being overwhelmed with a great amount of orders received, which creates work imbalances among the different zones (Rushton et al., 2014).

Close control management of warehouse operations such as marshalling is enabled by the wave picking method (Myerson, 2015). Wave picking is very similar to discrete picking in that one picker picks one order, one SKU at a time. The main difference between the two is the scheduling window. In wave picking, orders may be scheduled to be picked at specific times of the day, which is usually done to coordinate and maximize the picking and shipping operations.

Batch picking is when the picker picks multiple orders at the same time, one SKU at a time. The advantage in the method is the fact that when multiple orders include the same SKU, the picker only needs to travel to the location of that specific SKU once. This results in a boost in productivity and efficiency (Myerson, 2015).

Cluster picking is a methodology of picking into multiple order containers at a time. The containers could be either totes containing order batches, discrete order shippers, or discrete order totes (Myerson, 2015).

Combinations of the different methodologies such as zone-batch picking and zone-batch-wave picking are less commonly used. Following is a table which summarizes the eight most commonly used picking methodologies.

Table 2. 1 A summary of the picking methodologies seen in this chapter (Rushton et al., 2014).

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Order picking equipment, suitable for the methodologies above, can be classified under three main categories, which are picker-to-goods, goods-to-picker and automated systems.

Picker to goods has the picker travel to the goods in order to pick them. Three factors come into play here (Rushton et al., 2014):

1- Storage Equipment (e.g. shelves, flow racks or push back racks)
2- Equipment the picker picks to (e.g. trolleys)
3- Equipment the picker picks on to (e.g. wooden pallet)

For ground-level picking, trolleys and roll-cage1 pallets are usually utilized and, although manual in nature, tend to achieve high pick rates under the appropriate circumstances. Higher level picking is achieved through the use of free-path high-level picking trucks, which with the use of an elevating cab position, lift the picker to the ideal height for picking (Rushton et al., 2014). The disadvantage of high-level picking is that they achieve lower picking rates when compared to ground-level picking effectiveness. An upgrade to free-path high-level picking trucks are the fixed-path trucks, which run on a bottom rail and are guided by a top rail, thus allowing for faster processes. Pick cars are one step ahead, essentially being special fixed-path high-level picking trucks that straddles a horizontal conveyor2 running the length of the aisle (Rushton et al., 2014).

Picker to goods is the standard working concept, but costs a lot of time and resources, which means that a significant reduction of time and money spent could potentially lead to greater efficiency and profit.

Moving goods to picker is a picking methodology that allows for greater efficiency because it enables automation and warehouse control systems to be fully utilized. Goods to picker systems are always best approached holistically, with process driving equipment selection or automation, not the other way around (Stone, 2015).

These solutions rarely work for every area of a facility, or for every SKU in the distribution center. It’s all about blending the right solutions. Automated systems have proved to be a catalyst for logistics companies, as it greatly increases potential productivity, efficiency and accuracy in warehouse operations (Rushton et al., 2014).

Carousels include a range of types including horizontal, vertical, and vertical lift modules. They can be tied into enterprise resource planning (ERP) systems, WMS and warehouse control systems whether the carousel is in a large integrated system or a point of automation within a larger operation. They are usually deployed for component or item level picking. Manual picking can’t match carousels for speed (about 600 lines per hour), but they come at a cost, as they are expensive, but less costly than comparable automation. They are best paired with voice or light directed picking systems (Stone, 2014).

An automated storage and retrieval system (AS/AR) ties the entire facility together, usually connected to an ERP system or a WMS, with a big range of capabilities like tying into conveyor systems and the control of sorting transfer and automated guiding vehicles (Voortman, 2004).

In the last decade or so, the industry has been changed by the proliferation of goods-to-picker robots such as Kiva Systems or automated sorters like A-frame Sorter. These systems tend to deliver storage units along complex paths, to stationary pickers (Stone, 2015). They usually operate without human intervention.

The systems reviewed above are typically equipped with technological supporting technologies. New order picking technological aids have been introduced since the third industrial revolution. Paperless picking is making things easy in terms of labor work and cost and comes without the increased possibility of errors due to the lack of paper. The cheapest solution, as seen in Table 2.2, is the Ring/Finger scanner, a gadget that can be used in conjunction with a smartphone or a terminal, offering completely hands-free capabilities. RF systems eliminate the data entry and all paper-handling tasks (Lucasware.com, 2018). Pick by light is a picker-to-goods technological aid that leads the picker with the use of led panels mounted on the shelves, displaying the exact quantity that needs to be picked. Pick by voice technology is using voice recognition, allowing the pickers to communicate with the WMS and as a result get all the details they need with the use of a microphone and earphones (Zeimpekis, 2018). A portable terminal which is always connected to the WMS through a W-LAN is necessary for pick-by-voice technology to be utilized. However, since scanning may add an additional verification step in every task, some warehouses actually lose in productivity when moving from paper-based picking to a scan-based process, especially among top performing pickers (Lucasware.com, 2018).

Table 2. 2 A comparative table for Voice, Light and RF scanner picking technologies currently used (bcpsoftware.com, 2018).

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2.3.5 Packing

After order picking is completed, goods are packed and added-value services like labelling, kitting and assembly take place. Goods are picked simultaneously and then get sorted, in order to bring them together for packing (e.g. Items picked are conveyed to a sorter that brings various goods together for a specific order and then conveyed to an individual packing station) (Saghir, 2004).

Packing stations are specifically designed to boost the worker’s efficiency, due to packing taking a lot of time to be completed. The table on which the work is done is adjusted to the appropriate ergonomics, while mechanical equipment, like conveyors, and computer systems provide details through a monitor aid in the process (Rushton et al., 2014). Automated equipment, usually integrated into the conveyors, such as labelers, sealers and closing machines are enabling immediate follow-up processes like sealing and labelling. Another technological aid which helps lower transport costs, is the specialist packing machines. These machines construct cartons to perfectly fit different customer orders. When packing is done, goods are sent to yet another sorter in order to sort postcodes, carriers, regions or vehicle loads (WERC, 2007).

2.3.6 Dispatching

What follows is the dispatching of the goods, which have been placed in or onto unit loads. This is an operation that can be completed with a manual, or an automated way. Goods are moved to the marshalling areas which are allocated based on the outgoing vehicle schedule (Rushton et al., 2014).

Vehicles mostly leave at the same time of day, according to the schedule, which means that loading is an activity that needs to be completed with speed, reliability and accuracy. Pre-loading drop trailers and swap bodies help workers catch up with less hurry, resulting in a smaller possibility of errors to occur (Malindretos, 2015). Another quite important factor to take under consideration is coordination, where good coordination results in better area usage, so that the load doesn’t take up extra marshalling space.

Equipment necessary for dispatch processes to proceed range from boom conveyors to automated loading systems. Below is a list of handling equipment (Malindretos, 2015):

1- A boom conveyor, which extends into the vehicle or the container, where warehouse staff is tasked with lifting the goods off the conveyor.
2- Pallet trucks, which are best utilized for rear loading.
3- Fork-lift trucks ideally used for side unloading (e.g. curtain-sided vehicles).
4- Automated loading and unloading systems that can load and unload all pallets on the vehicle at the same time.
5- Automated tote bin loaders are only applicable when goods are dispatched in tote bins (e.g. A telecommunications company being supplied with smartphone accessories).

Loading bays equipment usually used (Loading Bay Equipment, 2018):

1- Dock levelers are permanently fitted at each bay, forming a minor inclination slope to match the height of each vehicle. Dock levelers need to be as long as the biggest vehicle expected to arrive at any given time.
2- Doors retracted above the opening when in use and normally fitted with windows so that they enable workers to see if there is a vehicle in the bay or not.
3- Dock shelters and seals offer weather protection in order to prevent any goods damaging, like getting full of dust or wet, depending on the situation.
4- Bumpers are almost always used to minimize the shock load to the building structure when a vehicle reverses up to the bay.
5- Lights are commonly used to give the driver indications as to the readiness of a vehicle to drive away, which results in a reduction of accidents, and provide illumination at night.
6- Vehicle restraints are used to restrain the wheels of a vehicle until it is safe to drive away.
7- Bollards are used to assist the driver in parking as centrally in the bay as possible.

The warehouse’s layout plays a huge part in how successful receiving and dispatching processes are. Parameters that need to be taken into account are all external areas within the perimeter fence, such as vehicle roadways, parking areas and ancillary areas (Zeimpekis, 2018). There are three possible ways the loading/unloading bays can be laid out (Ballou, 2014):

1- A through flow can allow for better flow of goods within the warehouse, with goods sequentially moved from receiving to storage, then to picking, then to sortation, packing and dispatch. A through flow is commonly used when the number of bays is too great to fit on one side. It’s best suitable for live storage3 racking.
2- U-flow is ideal for cross-docking and drive-in racking4, as it minimizes the distance goods need to travel. This major advantage U-flow of goods is best seen in an inventory-holding warehouse where receiving and dispatching happens at different times of the day.
3- Finally, the L-flow allows for receiving and dispatching areas to be forming an L-shape layout among them, suitable mostly for back to back5 and very narrow aisle (VNA) racking6.

Vehicle bays must be designed in a way that facilitates loading and unloading, so that they can optimize warehouse receiving and dispatching processes. When a vehicle bay is level intake, it enables better unloading for side-unloading vehicles. This process may take place inside the building, with a precaution for fumes and rising temperature, or outside (e.g. under a canopy). Another design that is commonly seen is the raised dock. With it, the floor is at the same level as the bed of the vehicle, allowing for direct access of a truck (e.g. a lift truck) (Rushton et al., 2014). This design is suitable for end-unloading, while a minor adjustment to the degrees between raised docks and the building is needed to enable side-unloading too. Receiving and dispatching areas in total, need to be designed in a way that it perfectly communicates with both suppliers and customers, as it represents a direct physical interface.

2.3.7 Warehouse Management System

Managing large warehouses with a very complex network of activities and processes is quite challenging. Information technology’s role throughout the supply chain has proved to be one of the most important ones and its involvement in warehouse management is as crucial nowadays as ever. All different processes and tasks completed day-in and day-out are becoming more challenging as years pass, and information systems in the warehouse are able to fully support warehouse operations, enabling workers to complete tasks and activities with greater efficiency.

A WMS interfaces with the company’s ERP or legacy system in order to access valuable information, such as purchase orders, thus increasing the efficiency of warehouse operations, by storing all kinds of information (e.g. goods received or dispatched) and giving access to warehouse staff at any given time (Rushton et al., 2014). Another capability of the system is to give instructions to subsidiary systems like voice picking equipment or an AS/AR control system (Malindretos, 2015).

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Figure 2.3 WMS adds the element of automation to warehouse operations, thus increasing productivity and efficiency (Schmidthk.com, 2018).

Warehouse management systems have a wide range of functionality with the added benefit of enabling users to turn on or off for specific applications (e.g. In electronics, batch traceability of components is providing workers valuable information). Warehouse activities are covered by WMS’s capabilities and functionality as shown in the examples below (Rushton et al., 2014):

1- Receiving: Advanced shipping notes (ASNs), quality sampling, dimension and weight checking
2- Put-away: Best storage location algorithms
3- Replenishment: Trigger points, order-based replenishment
4- Picking: Picking route optimization
5- Added value services: Kitting, labelling, assembling
6- Packing: Correct carton size identification
7- Cross-docking: Planning, labelling
8- Sortation: Grouped by order, vehicle, geographic destination
9- Dispatching: Marshalling lane control, documentation, ASNs transmitting
10- Stock counting: Full count

Data capturing is another quite important factor for greater efficiency in warehouse operations and bar codes are the most common way of doing that. A bar comprises of a number of vertical or horizontal bars of varying thickness and each combination of bars represents a number or a letter. These codes are specifically designed, so that the first few bars indicate the symbology, a term commonly used among organizations for various purposes (Ballou, 2014). The next few bars indicate the national coding authority, the manufacturer, the product number and finally a check digit. Scanners are used to read bar codes for direct input of information in computer systems. Common applications of bar codes are bar code checking when picking and reading labels when sorting.

Radio frequency identification (RFID) is seeing a growth in popularity, despite being available for decades. Its main purpose is the identification of items with the use of radio waves (Rushton et al., 2014). Some common applications for RFID are the tracking of unit loads, and other item level purposes. The four components of an RFID system are:

1- Tags affixed to the goods or containers, comprised of the combination of microchips and an antenna with a battery most of the times.
2- Antennas receives the data from the tag.
3- Readers read the data transmitted by the antenna.
4- Host stations contain the application software and relays the data to the server.

Without information technology in the warehouse, logistics and supply chain management would not have evolved at all. In order to have an uninterrupted flow of goods, data capturing and processing play a vital role.

2.4 Transportation

Transportation is the next step in supply chain operations and one of the main reasons for civilization evolution and commerce growth through the years, as the transportation of goods isn’t just a service to be taken lightly. Many different processes and activities need to be perfectly coordinated in order for transportation to be successful.

2.4.1 Transport Modes

There are 5 transport modes currently used for freight transportation:

- Maritime Transportation
- Air Transportation
- Pipeline Transportation
- Rail Transportation
- Road Transportation

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Figure 2.4 Freight transport mode of choice by percentage worldwide (SAFETY4SEA., 2018).

1- Sea-freight has been around for thousands of years and is the oldest mode of transportation, while still retaining the number one spot for the mode of choice internationally. In this mode of transport both the conventional load and the unit load (container) are relevant. Sea-freight has its advantages, but they come along with some disadvantages that other transport modes have resolved, as listed below (Rushton et al., 2014):

a. Cost. Sea-freight is the cheapest way of transporting goods, as cargo ships can carry quite large packaged consignments that are going long distances.
b. Availability. Services are widely available.
c. Speed. Maritime transport is the slowest mode of freight transport.
d. Delay problems. Unexpected delays due to bad weather, pre-shipment delays and delays at discharge ports are the three major delay factors to be seen.
e. Damage. This mode is more prone to damage for products and packaging.

2- Pipeline transportation is the mode of choice when it comes to oil and gas transportation as 70% of domestically produced petroleum products in the U.S. are transported by pipeline (Hansen and Dursteler, 2017). Pipelines are large projects and have high upfront costs while it can also take significant time to obtain necessary permits. Even after construction is completed, pipelines can be costly to maintain (Smith and Christopher, 2014). The characteristics of pipeline transportation are as follows:

a. Cost. Quite costly.
b. Availability. Services not widely available.
c. Speed. One of its strongest points.
d. Delay problems. Usually none.
e. Damage. Pipeline transportation is the safest transport mode.

3- Air freight has grown rapidly in recent years. Improved handling systems, greater cargo space, integrated unit loads, and scheduling have skyrocketed air freight as the mode of choice. Still, its high costs have kept it low at 3.6% when compared to sea-freight’s 46.0%, as seen in figure 2.3 (SAFETY4SEA, 2018). A list of the characteristics of air freight can be seen below:

a. Cost. The most expensive mode of transport and air freight’s greatest disadvantage.
b. Availability. Air freighting of products allows for great market flexibility as any number of countries and markets can be easily reached.
c. Speed. Air transport is the quickest mode of transport, but that advantage can be lost due to delays. Ideal for short-life products and emergency supplies.
d. Delay Problems. Airport congestion, paperwork delays, customs delays and bad weather (e.g. fog) can be delay factors.
e. Damage. Over the years air-freight has grown into one of the safest modes of transport.

4- Rail transport is the most conventional form of transport. International trade trains cross Europe at relatively low speeds, while having the advantages of safety and being a non-polluting means of transport. The railway infrastructure covers a large part of the European union (EU) and that is why the EU did take an important initiative in March 2003, enabling private operators to exploit the existing infrastructure and to compete with state-owned railway companies for freight services transport (Malindretos, 2015). Its characteristics are listed below:

a. Cost. Costs are relatively high due to the need for more than one transport mode.
b. Availability. One of its greatest disadvantages due to lower flexibility of its itinerary.
c. Speed. Quite slow, but relatively faster than sea-freight.
d. Delay problems. One of its strongest advantages, because of very low chances of a scheduling department getting delayed.
e. Damage. A safe transport mode.

5- 42.7% of freight transport happens via road freight transportation (SAFETY4SEA, 2018). One of the most important transport modes for national movements within individual countries. Road freight is always the mediator when it comes to intermodal transport due to its flexibility and adaptability to land transportation and a fully-grown road network. Roll-on roll-off services (RORO) enable road freight in the UK for example (Rushton et al., 2014). Its characteristics are as follows:

a. Cost. Low costs with a caution for fuel management and empty-body movement.
b. Availability. As previously stated, road transport is the mode of choice when it comes to nationwide freight transportation, but it shows its limitations when it comes to international freight transportation, where it needs to be combined with one or more different modes.
c. Speed. This variable is quite complex to determine, as the factors having a role in road freight’s speed of transportation are numerous.
d. Delay problems. With the use of fleet management systems which will be examined later in the chapter, and routing algorithms, drivers can now avoid delay problems created (e.g. road congestion).
e. Damage. Another variable that can clearly be said to have been dealt with due to more efficient packaging processes.

Below is a comparative table of the transport modes (excluding Pipeline transport):

Table 2. 3 Comparing modes of transport across four crucial variables.

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2.4.2 Line Haul Transportation

Line haul transportation is the transportation of goods from one location to the next, which typically happens via semi-trailer trucks or rail cars. There is a great variety of line haul vehicle types, as seen below, depending on the cargo (wewilltransportit.com, 2015):

1- Refrigerated Freight – Used for moving goods that need to be refrigerated.
2- General Freight – A basic container used to ship anything.
3- Livestock Hauler – Used to transport live animals from one location to another with safety.
4- Grain Hauler – Grain haulers are used to transport grain from a farm to a processing facility.
5- Tankers – Used to transport anything in liquid or gas form.
6- Doubles – A semi-trailer truck hauling two freight containers.
7- Triples – A semi-trailer truck hauling three freight containers.
8- Turnpike Duty or Double – Another method of pulling two containers with a single semi-trailer truck.
9- Bulk Hauler – Used to transport milk or smaller dry foodstuffs in bulk.
10- Auto Hauler – A carrier used to transport multiple automobiles.
11- Flat-bed – A flat shipping surface use to ship cargo that cannot fit in a container.

In order for line-haul transportation and transportation in general to be performed successfully, end-to-end visibility is to be considered as one of the most crucial factors for monitoring transportation and distribution. Monitoring shipments enables visibility through the supply chain and the only way this was happening through the years was due to data capturing from multiple systems and sectors of the supply chain (Savi, 2013). As a result, companies were unable to monitor and control costs relative to inventory, manufacturing, transportation etc.

Monitoring the location and the movement of containers is the way to obtain visibility into each distinct logistics process (Savi, 2013). Three areas benefitting from container management are inventory, replenishment and cost monitoring. Companies carry inventory in the form of raw materials, work-in-progress (WIP) and finished goods (Rushton et al., 2014). With real-time visibility into the location and condition of the containers, as well as the inventory they hold, companies can achieve greater confidence in supplier delivery schedules, inventory consumption and finished goods production schedules. (Ballou, 2014).

Another benefit of end-to-end supply chain visibility is in the management and control of the reusable containers themselves. Let’s use an automotive manufacturing company as an example. Manufacturers use specialty racks for shipping automotive parts. Not only are these racks expensive, but they are also essential for moving parts and finished goods (Savi, 2013). If the right container is not available at the right location at the right time, it can lead to expensive last-minute transportation (relocation) costs and in extreme circumstances, not having these specialty racks available can even stop the assembly line (Savi, 2013).

Unfortunately, these assets are also prone to misuse and loss. Some industry estimates state that between 15-20% of the total container stock is stolen and/or lost each year (Savi, 2013). With better visibility of the container stock and their locations, companies can better utilize these assets through faster relocation and fulfillment. This improved asset utilization will help companies optimize their processes, meaning fewer total assets are required to maintain and run their operations (Antich, 2013).

2.4.3 City Logistics/Last Mile Delivery

The interest in transportation and distribution services in non-urban areas is a given, but an increase in these services in urban areas has been declared in the last decades due to a massive shift towards urbanization (Taniguchi, 2012). City logistics is a term first defined by Taniguchi in 1999, as “the process for totally optimizing the logistics and transport activities by private companies in urban areas while considering the traffic environment, the traffic congestion and energy consumption within the framework of a market economy”.

The transport mode of choice in urban areas and cities is dominantly road freight, while other alternative methods have been utilized through the years, such as rail, underground systems and rivers (Tadic et al., 2015). The issues and challenges here are many and there has been an impressive amount of research and development in the city logistics area of research. Environmental awareness and road congestion have been the most difficult obstacles to overcome (Cardenas Barbosa, 2017).

Facility location for example, is a crucial factor, as many different variables depend on it (e.g. distance to be covered and accessibility) (Savelsbergh and Woensel, 2016). The better the network, the better the performance, meaning better distribution and delivery times, reduced carbon footprint and smaller probability for road congestions (Cardenas Barbosa, 2017).

The intra-city transport of goods is performed with the use of lighter and smaller vehicles in order to reduce the carbon footprint and increase agility within the city structures, while bigger and heavier vehicles are used outside the city limits (Visser and Binsberger, 2018). Distribution centers strategically located around the city enable for this method of transportation to be utilized. The larger vehicles arrive at the distribution centers, goods are then marshalled and sorted, with the next step being loading them in the smaller vehicles in order to distribute the goods within the city (Trebilcock, 2015).

Last-Mile Delivery is the final step in city logistics. It is a term derived from “last mile”, which is borrowed from telecommunications network, and delivery, the act of delivering something (e.g. goods, letters etc.). The importance of the term comes from the multi-hub-and-spoke networks topology which can be compared to the structure of a tree (Faccio and Gamberi, 2015). As the network advances to the final customer, it becomes more populated and inefficiencies are easier to occur. There are indications that as much as 28% of the transport costs can be related to the last mile delivery or first mile pickup (Cardenas Barbosa, 2017). As a result, we define last mile delivery as the final leg of transporting the goods to the point of consuming.

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.5 A geographical view of urban logistics, comprised of city logistics, urban goods distribution and last mile delivery (Malindretos, 2015).

As previously stated, research and development on city logistics and urban distribution is continuously getting traction. Fleet management systems currently used for these operations enable better distribution and delivery, not just for urban areas, but also for inter-urban and international transportation.

2.4.4 Fleet Management

Fleet management is the function that coordinates and facilitates various transport related activities with the aim of reducing operational costs through the management of assets used in each of the transport modes (White, 2015):

1- Ships
2- Aircrafts
3- Vehicles for work purposes
4- Rail Cars
5- Commercial Motor Vehicles

Through the years fleet management information systems have been developed in order to enable managers to efficiently monitor, control and administer transport operations. Specialized database packages have also been developed with the goal of optimizing fleet management processes and related activities (Rushton et al., 2014). Functions that depend on those databases and extract information from the data are:

1- Maintenance Scheduling. Monitoring the condition of mechanical parts of a vehicle, managing its carbon footprint, scheduling repairs and maintenance checks based on service history and analyzing costs based on maintenance or repair routines (Rushton et al., 2014).
2- Vehicle Parts Control. Enabling the oversight of stock quantity for various spare parts requirements, including the stock location and stock reports.
3- Fleet Administration. This function is always included in packages in order to ensure the legality and worthiness of vehicles (White, 2015).
4- Fleet Costing. A function that provides information related to fleet and vehicle costs.
5- Tachographs. These are used for monitoring the driver’s hours of driving and resting, the distances travelled by individual vehicles, speed ranges throughout travels and fuel consumption (Guide to Digital Tachographs, 2006).

Digital tachographs are fitted on goods vehicles that are subject to tachograph rules and have been brought into service since 1 May 2006. It is a digital version of the analogue tachograph system. The digital system records information on a range of vehicle and driver activities. Data is stored in the vehicle unit memory and on driver cards (Guide to Digital Tachographs, 2006). Information extracted are used to produce key performance indicators (KPIs) for the vehicle fleet (e.g. tonnes per mile, fuel costs, miles/kilometers per gallon etc.).

Another way of monitoring and controlling fleets is through telematics, which can be defined as the combination of telecommunications systems and information technology. A very well-known application of telematics is the global positioning system (GPS), which aids in navigation of commercial vehicles while also boosting security due to enabling administrators to know the exact location of the vehicle (Rushton et al., 2014). Instructions may be given to remote assets regarding the vehicle’s temperature, fuel consumption and parts performance, thus allowing drivers to avoid damages and reduce vehicle emissions as well as improving efficiency (The Ultimate Guide to Fleet Telematics, 2018).

2.4.5 Routing and Scheduling

Vehicle routing and scheduling are fleet management capabilities, which have been a topic worth of research and discussion. Through the years a huge number of algorithms have been developed to offer solutions but the number of parameters one must consider are far too great in number.

Usual routing and scheduling problems are:

1- Resource Planning. Refers to requirements regarding the transport fleet.
2- “What if” Planning. Identification and measurement of the effects of change on logistics operations (Rushton et al., 2014).
3- Planning fixed-route Schedules. Involves the longer-term aspects of routing and scheduling for regular deliveries of products (e.g. retail delivery operations and milk delivery) (Rushton et al., 2014).

Various methods are used for routing and scheduling problems, depending on the nature and complexity of each individual problem. Such methods include algorithms used to optimize transport operations by providing smallest-distance solutions for cost efficiency and maximum profits.

In order for said algorithms and information systems to be able to provide the best possible solutions for routing and scheduling problems, data have to be extracted from multiple areas such as distance factors, driver constraints, vehicle restriction, route factors, average speed on a variety of roads, unit loads and demand data (Rushton et al., 2014).

2.4.6 Information Systems in Freight Transportation

As previously stated, fleet management information systems assist managers in monitoring, controlling and administering vehicle fleets effectively. Other information systems and applications utilized for freight transportation are:

1- International Trade Management Systems. Specialist software packages available to control the international movement of goods, including features to assist with documentation requirements, finance and monitoring of progress (Ballou, 2014).
2- Supply Chain Event Management Systems. Systems monitoring the progress of orders and warning managers for possible potential issues (Rushton et al., 2014).
3- Electronic Point of Sale (EPOS). A common application used in retail stores around the world, used to facilitate easier payment processes (Rushton et al., 2014). Goods marked with bar codes are scanned and then the system tallies the price and records the transaction.
4- Proof of Delivery (POD). It is an essential component of the delivery process as it serves as an important acknowledgement to mark that the delivery has been completed (CarPal Fleet, 2018). By using the POD feature, not only do companies have the assurance that packages were successfully delivered, but also track the progress of the delivery. This aids companies in identifying potential issues before they become major liabilities (CarPal Fleet, 2018). Recipients must sign for receipt of the mail indicating the date when the mail item was delivered to them. A copy of the Proof of Delivery receipt is provided to the sender.

2.5 Reverse Logistics

Up until now we have seen current logistics operations and information systems utilized regarding forward logistics, meaning the transportation of goods from the point of origin to the consumer. Reverse logistics refers to the process of planning, implementing and controlling flows of raw materials, work-in-progress and final products from a manufacturing, consuming or distribution point, to the point of recovery or disposal (Rosier and Janzen, 2008). The different categories of returns are (Malindretos, 2015):

1- Commercial Returns. Returns for which there is an immediate demand at another market location or segment (e.g. customer dissatisfaction, catalogue sales, and overstocks etc.).
2- Repairable Returns. Defects and suspect components from field repair activities or products under warranty. Customer is usually entitled to a replacement product.
3- End-of-use Returns. Returned products/components which are no longer of use to the original owner, but for which new customers can be found.
4- End-of-life Returns. Items of no remaining use, which are processed due to contractual or legislative obligations.
5- Recalls. Products recalled by the manufacturer due to a condition or defect that could affect its safe operation.

2.5.1 Reverse Logistics Process

Returned goods go through the following activities based on the return type (Rosier and Janzen, 2008):

1- Product is retrieved from the market. Factors that should be monitored are quality, timing, quantity and composition of the returned goods.
2- Transportation, consolidation, transshipment and storage are examples of processes that need to be followed backwards and transport the goods to the point where the repair or disposal shall take place (Malindretos, 2015). Quality and composition are the two factors that indicate the route the returned goods will take within the supply chain network.
3- The type of recovery will be decided (e.g. re-use, repair, recycling etc.) (Bentz, 2015).
4- The materials, work-in-progress items or goods return into a forward supply chain.

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.6 The reverse logistics process (Bentz, 2015).

2.5.2 Priorities and Issues

Recently, reasons for the process of re-processing are piling up, which essentially include the actions of recycling, reselling and scrapping (Bentz, 2015). Because of various investigations having shown that various products, such as electrical appliances, are of economic and environmental interest, reprocessing and recycling routes should be followed. The natural priority is to reduce waste. Then the goal is to exhaust all possibilities for reprocessing and re-using, and finally for recycling, as raw material or WIP products in order to re-manufacture the goods and put them back in the forward supply chain (Malindretos, 2015).

Some major issues that have arisen lately are summarized below:

1- The electricity consumed during the recycling process is important. Renewable energy can be a solution for energy spent in the recycling process.
2- The water spent to clean the materials at recycling centers can reach several tons daily.
3- Fuel consumption is required to transport the materials to the Recycling Centers. This issue is a major field of research for Reverse Logistics.

Therefore, the question of recycling should be approached holistically, as the final process of organization management of returned goods, because recycling is not an end-to-end goal.

2.6 Issues and Challenges

The logistics industry has been growing rapidly for quite some time now and technology, while having a high growth rate, has always been an integral part of logistics operations (Scriosteanu and Popescu, 2018). Nowadays various issues and challenges have emerged, that push logistics companies to re-organize how they do business. Issues may be external to logistics, such as deregulation, or derive from changes within logistics, such as the integration of information technology (Rushton et al., 2014). Higher customer demands, the rise of e-commerce, globalization and urbanization, cybersecurity and new business models driven by startups are just some of the issues that need to be addressed. Warehouse and transportation operations reviewed earlier in this chapter, need to be evolved in order to resolve these issues and drive the logistics industry forward.

2.6.1 Higher Customer Demands

Customer service is one of the most important factors in a company’s growth and prosperity. Competitive success is greatly influenced by customer satisfaction and companies that fail to recognize that are in danger of being unsuccessful. Service is a factor of differentiation that has proved to be the key to a customer’s decision to choose one brand over the other (Rushton et al., 2014). The ability to satisfy customer requirements is a challenge that all companies must face (Rushton et al., 2014). Major factors contributing to the rise of this challenge are listed below:

1- A rapid growth in customer expectations through the years.
2- Buyers recognize the importance of customer service.
3- Markets have become service-sensitive.
4- Immediate product availability has become vital.
5- Customer relationships have become a priority for most companies.

2.6.2 Organizational Structures

For many years logistics was not recognized as a discrete function within organizational structures, resulting in problems surfacing through processes such as distribution and storage. In addition to that, many companies could not re-organize their structure in order to integrate logistics as a discrete function, leading to major problems within (Jan, 2016). Companies and organizations which successfully recognized the logistics sector, did so in a way that was rendering the communication lines unclear (Rushton et al., 2014). This issue resulted in inefficiency and higher operational costs, while proving to be damaging for their reputation.

Incorporating new business models within their business strategies and recognizing the importance of logistics is the first step towards a successful supply chain (Galindo, 2016). The way logistics operations are organized has to be process-oriented and not structure-oriented, with key changes like emphasizing on the customer and the internal processes needed to be optimized in order to achieve customer satisfaction, while a reduction in operational costs will be immediately felt within company walls (Jan, 2016).

2.6.3 Globalization

Logistics will be greatly influenced by a global shift in the economic power of the emerging seven countries over the next years as well as regional changes, especially in Asia-Pacific which has quickly grown to now account for 50% of international trade (Noronha et al., 2016). Key developments worth highlighting are the major investments being made by the Chinese government in trade lanes to Europe.

Logistics will also experience a systemic change in terms of workforce and technology adoption, as it will be challenged by increasing competition as well as a growing shortage of skilled workers. Macroeconomic volatility and shifts in trade patterns will result in the rebalancing of global logistics and trade. In addition, structural changes in terms of workforce demographics and technological innovation will determine the shape and the rate of evolution within logistics (Grapht, 2018).

2.6.4 Startups and Logistics Industry Disruption

Logistics can be confidently said to be the backbone of international trade, but at the same time has been a fragmented industry with a slow adoption rate of new technologies. The underdeveloped market potential along with the potential of harnessing technology advancements makes this industry a target for disruption (Utterback and Acee, 2003). Established companies are often left with legacy IT systems that make globally streamlined IT services quite difficult to achieve.

In summary, whether startups are able to disrupt established industry giants or not, remains to be seen. It has already been felt in some service segments, but logistics providers do not have to take a reactive approach to startups (Noronha et al., 2016). Some are already partnering with startups, while others are acquiring startups or are even breeding their own startups in in-house incubators (Grapht, 2018). Thus, they themselves can drive rapid innovation and disrupt the logistics industry.

2.6.5 The Rise of E-Commerce

E-commerce presents a fundamental shift in how business is done. Instead of the traditional way of companies pushing goods to physical stores, e-commerce allows customers and consumers to customize their baskets according to their needs and have it delivered to their favored destination (Monahan and Hu, 2018). In bottom line, customers need companies to be quick and increase their logistics performance more than ever before, evidenced by the continuous rise of e-commerce, as seen in figure 2.8 (Robinson, 2018). This has created a structural forced change in underlying logistics operations and processes, forcing logistics companies and organizations to consider the integration of technologies that will bring them towards digitalization and automation, such as the Internet of Things and Advanced Robotics, technologies which will be reviewed in a later chapter.

Abbildung in dieser Leseprobe nicht enthalten

Figure 2.7 Global Retail E-commerce sales growth through the years (Vupune.ac.in., 2018).

[...]


1 A trolley, or a pick-cart, usually has a shelf or shelves upon which the picker places the goods. Roll-cage pallets are normally taller and have wire mesh on three sides with an optional mesh door on the fourth side. Low-level order picking trucks (LLOPs) are electrically powered trucks usually used for picking from ground floor pallet locations (Rushton et al., 2014).

2 A conveyor is a mechanical system that aids workers in goods handling, moving them from location to location. It is ideal for the handling of heavy/large items.

3 In live storage racking goods are handled according to the FiFo principle (First in-First out). The goods are loaded into the rack on one side and unloaded at the other side. This provides a very satisfactory flow of goods (e.g. for handling goods with a limited storage life). The live storage racking is fitted with brake rollers at regular intervals so that goods can be safely transported (Eab.info, 2018).

4 This system is based on the storage by accumulation principle, which enables the highest use of available space in terms of both area and height. Drive-in racking is designed for the storage of homogenous products. It accommodates a large number of pallets for each SKU (Mecalux.com, 2018).

5 Back-back Racking Systems are built by putting two modules back-to-back and interconnecting them together. Each pallet can easily be placed and transported independently. It allows operating a forklift. Bay height and beam length adjusted Back-to-Back Racking System’s satisfy customer’s need and expectations, which has the widest range of use from the smallest warehouses to the largest up to complex logistics centers (Temesist® Endüstriyel Depo Ve Raf Sistemleri, 2018).

6 Very Narrow Aisle racking commonly referred to as VNA is an effective method of increasing pallet storage with in a given area with the advantages of selective racking. This system requires a special fork lift which reduces the aisle space by a minimum of 40% compared to traditional fork lifts. This system still provides 100 % product selectivity and utilizes the vertical space for pallet storage (Konstant.com, 2018).

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Details

Title
Logistics 4.0. Applications, Trends and Challenges
College
University of the Aegean
Grade
1
Author
Year
2018
Pages
144
Catalog Number
V490856
ISBN (eBook)
9783668981096
Language
English
Tags
logistics, applications, trends, challenges
Quote paper
MSc. in Management Engineering Dimitris Karampourniotis (Author), 2018, Logistics 4.0. Applications, Trends and Challenges, Munich, GRIN Verlag, https://www.grin.com/document/490856

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