This document discusses how various technologies help solve business problems in logistics. It focuses on retail, transportation, and automotive and describes technologies like blockchain, big data, 3D printing, chatbots, IoT, sharing economy, self-driving vehicles, drones, computer vision, AR/VR, machine learning, and omni-channel. Several case studies are provided for each technology showing real-world applications with companies like IBM, Maersk, Walmart, DHL, UPS, Mercedes-Benz, Amazon, and more.

1. Cases: how technologies help to
solve business problems in logistics
Alex Isachenko, CEO, Managing Partner, CoreTeka +380 93 570-56-28, isachenko@coreteka.com

2. FOCUS
CoreTeka focuses on three main categories: Retail, Transportation, Automotive.
Retail Transportation Automotive

3. CONTENT
• Blockchain
• Big Data
• 3D printing
• Chat-bots
• Internet of things
• Sharing economy
• Self-driving vehicles
• Drones
• Computer vision
• AR VR
• Machine learning
• Omni channel

4. Blockchain

5. BLOCKCHAIN IN LOGISTICS
Blockchain technology in logistics gives the possibility to avoid unnecessary mediators, save costs, reduce the amount of paperwork and
provide security by reducing the number of errors and frauds.
• Smart Contracts
• Tag and track system
• Safe transactions
• Real-time feedback from
consumers
• Supply chain certification
• Integrating payments
• Fraud prevention

6. CASE: IBM & WALMART
Walmart and IBM have collaborated on several pilots to trace goods via the blockchain in an effort to find
bottlenecks, decrease food waste, and enhance food safety.

7. CASE: IBM & MAERSK
IBM and Maersk are using a blockchain built on the Hyperledger Fabric to manage supply chain for container
shipping.
Problem
Solution
One shipment can require
sign-off from 30 unique
organizations and up to 200
communications.
One lost form or late approval
could leave the container stuck
in port.
The entire process can take
more than one month.

8. Big Data

9. BIG DATA IN LOGISTICS
Delivery Route Optimization Package Movement Monitoring On Ground Resource Management
Big Data technology provides the information on the patterns of customer behavior, market trends, and maintenance cycles. It also offers
cost reducing methods, optimal price and processes optimization strategies and considerably facilitates the decision-making process.

10. DHL
As the world leader in logistics, DHL prepares the reports and shares the accumulated knowledge with its customers and everyone who
might be interested in it.

11. CASE: TRANSPORT OF LONDON
Transport of London (TfL) smartcard ticketing system enables a vast amount of data to be collected about journeys that passengers are
taking. The information allows the company to understand load profiles, plan interchanges, ticket facilities, signage and commercial
offering.
Problem
Bridge was closed repair work.
Bus services had to stop either
side of bridge.
Solution
Sent targeted e-mails to provide
customers with information about
alternatives routes.
• Oyster and contactless card
• Traffic information
• Social media
• Bus location data
• Asset data
• Mobile app data

12. CASE: DHL
At the core of the DHL Smart Truck lies the dynamic route planning system. It processes all the information on the road and sends
relevant updates to the vehicle’s on-board computer instantaneously. This allows the delivery to become more efficient, (the
implementation of the Smart Truck reduced the number of miles traveled by 15%).

13. CASE: UPS
Why UPS drivers don’t turn left? UPS started its 2011 initiative for each driver to save one mile per day. Its Big Data analytic approach to
driving performance and route optimization, termed ‘On-Road Integration Optimization & Navigation’ (ORION).
Processed data
Vehicles Tracked 46 000+
Packages Tracked 16,3 million per day
Customers 8,8 million
Results
Miles Saved 85 million per year
Gallons of fuel saved 32 million per year
$ Saved $30 million per year

14. 3D Printing

15. 3D PRINTING IN LOGISTICS
The total transportation spent by a
warehouse may be reduced by up to
85%
Transportation cost may be reduced by
up to 90% as the product is now
manufactured closer to the customer
Supply chain managers can reduce
their inventories to virtually zero while
still maintain 100% item fill rate
Volume Cost per unit Time to market Cost of complexity
Small batch,
Highly customized
High variable costs,
No fixed costs
Very fast (<1 day)
No higher that
simple parts
Large batch,
Not customized
Low variable costs,
High fixed costs
Very slow to
moderately slow
Much higher that
simple parts
3D PRINTING
TRADITIONAL
3D Printing may change the traditional logistics. The technology allows quickly printing of spare parts/details/products with the use only
of electronic library of projects available on the computer and the 3D printer. As a result, transportation and warehousing costs will be
reduced.

16. CASE: MERCEDES-BENZ
Mercedes-Benz launched the printing of metal parts of machines. According to the press service of Mercedes-Benz, the details printed on
the 3D printer passed all the stages of quality control and are in no way inferior to the reliability of metal products produced by traditional
methods.

17. CASE: UPS & FAST RADIUS
UPS and Fast Radius has strategically located its 3D printing factory just minutes from the UPS global air hub. The value of this end-of-
runway location is that orders can be manufactured up to the 1 a.m. pickuptime and be delivered anywhere in the U.S. the next morning.

18. Chatbot

19. CHATBOT IN LOGISTICS
Quality control
Easier production planning
Instant connect departments
and workflows
Quickly respond to
customers demand
Reduce waste by tracking
inventory
Order/shipments tracking
Chatbots allow the business to exchange the necessary information with customers, suppliers and employees.

20. CASE: UPS
UPS has launched the chat-bot, an artificial-intelligence-enabled platform that mimics human conversation to help users easily find UPS
locations, get shipping rates and track packages. The UPS chat-bot available through Facebook Messenger, Skype and Amazon platforms.

21. CASE: FRANK TAXIBOT
Frank is a friendly bot that proves that ordering a cab is as easy as chatting on Facebook. Customer can order a taxi anywhere around the
world, just by writing to him on Facebook. Its aim is to create an international partnership of mobile taxi apps.

22. IoT

23. IoT IN LOGISTICS
Real-time fleet management
Predictive maintenance
Cargo integrity monitoring
Smart labels
Storage conditions control
Inventory tracking & analytics
End-to-end visibility into delivery
process
Optimized warehouse workloads
With the use of IoT technology, logistics providers can achieve high levels of operational efficiency in regard to fleet management, cargo
integrity monitoring, and automated warehousing operations.

24. CASE: MAERSK & ERICSSON
Maersk operates in 343 ports across 121 countries. Back in 2012, the Danish giant teamed up with Ericsson to install real-time monitoring
across its fleet with Ericsson’s mobile and satellite communication technology.
• Reduction delivery preparation time
• Fast changes of routes
• Reduced fuel consumption
• Higher ship productivity
• Information on temperature and
stability of a container

25. CASE: OCADO
Grocery store Ocado is leveraging IoT and robotics to improve inventory management. The technology enables Ocado to control and
co-ordinate the movements of hundreds of thousands of crates containing millions of grocery items, in real-time and in parallel.

26. Sharing
economy

27. SHARING ECONOMY IN LOGISTICS
$0.97
Incremental
change
$0.63
A world of car
sharing
$0.46
The driverless
revolution
$0.31
A new age of
accessible
autonomy
Cost per mile, by future mobility state
Personal SharedAutonomusDriver
1 2
43
• Truly Shared Warehousing
• On-Demand Staffing
• Logistics Data Sharing
• Community Goods On-demand
• Logistics Asset Sharing
• Transport Capacity Sharing
• Urban Discreet Warehousing
Sharing economy gives new opportunities for classical logistic business in the sphere of warehousing, transportation and delivery of "the
last mile".

28. CASE: FLEXE
American Seattle-based startup Flexe has also developed a marketplace for excess warehouse space that includes a network of over 370
warehouses across 45 markets, creating access to over 400,000 rentable pallet spaces in North America.

29. CASE: UBER FREIGHT
The first product from Uber Freight is a marketplace to connect a shipper with a truck, much like the Uber app connects drivers and
riders.

30. Self-driving
vehicles

31. SELF-DRIVING VEHICLES IN LOGISTICS
Warehousing operations Outdoor logistics operations Line haul transportation Last-mile delivery
• Autonomous loading and
transport
• Assisted order picking
• Assisted highway trucking
• Convoying systems
• Parcel station loading
• Autonomous shared cars
• Self-driving parcels
• Improve safety in yards
• Automated containers, unit
load devices (ULD)

32. CASE: PELOTON
Peloton is a connected and automated vehicle technology company. Peloton uses vehicle-to-vehicle communications and radar-based
active braking systems, combined with sophisticated vehicle control algorithms, to link pairs of heavy trucks.

33. CASE: KNAPP OPEN SHUTTLE
Open Shuttle developed by KNAPP provide autonomous transportation in the warehouse. Using laser navigation technology, this free-
moving vehicle can be deployed for transport and picking activities involving cartons and containers – this makes it ideal for many kinds
of low-throughput transportation.

34. Drones

35. DRONES IN LOGISTICS
Point To Point Delivery
Asset/Inventory Tracking
Inspection
Urban First and Last Mile
Rural Delivery
Drones provide new solutions to problems in the logistics field, such as сosts reduction, eliminating "human" mistakes, delivering goods
to hard-to-reach places, monitoring and protecting transport routes.

36. CASE: AMAZON PRIME AIR
Amazon Prime Air — a delivery system designed to safely get packages to customers in 30 minutes or less using unmanned aerial
vehicles, also called drones.
Drone features
• Delivery in 30 minutes or less
• Flying below 120 m
• Drones weighing less than 25 kg
• Use of «Sense and Avoid» technology
• Travel distance up to 20 km

37. CASE: MERCEDES-BENZ VANS
Van manufacturer Mercedes-Benz Vans has unveiled its strategic future initiative adVANce for the transport industry. The Vision Van
features a fully automated cargo space, integrated drones for autonomous air deliveries and a state-of-the-art joystick control.

38. Computer
vision

39. COMPUTER VISION IN LOGISTICS
Reading of 1D and 2D barcodes
Identification of uncoded text (Optical
Chatacter Recognition)
Verification of the presence of the logo
Quality control
Automatic sorting packages
Automation of logistic operations becomes more complicated and requires new solutions for effective use of production capacities. Laser
devices do not always cope with their tasks. Computer vision comes to rescue them.

40. CASE: COGNEX
Code readers using computer vision can be used just like standard laser scanners, stationary or handheld. An example of the executive
stationary readers is DataMan 500 by company Cognex, which is based on its own chip technology for computer vision, Cognex VsoC
(Vison System on a Chip).
Speed shooting: up to
1000 frames per second
Total:
270 readings per second

41. CASE: AMAZON
Amazon already operates a mobile Kiva robots which outweigh high shelves unit with goods. These robots based on the automated
instructions take him to the destination. They move in a specially reserved area and for orientation using computer vision, because on the
route are QR codes at regular intervals stationed on the floor, according to which then orientate where they must turn onto.

42. AR VR

43. AR VR IN LOGISTICS
Warehousing operations Transportation optimization
Enhanced value-added
services
Last-mile delivery
• Warehouse Planning
• Pick-by-Vision: Optimized
Picking
• Assembly and Repair
• Customer Services
• Parcel Loading, Drop-off
• Last-meter Navigation
• AR-secured Delivery
• Completeness Checks
• Dynamic Traffic Support
• Freight Loading

44. CASE: DHL
DHL will expand its “Vision Picking” solution, establishing a new standard in order picking for the industry. During the pilot, productivity
increased 15% on average. The smart glasses provide visual displays of order picking instructions along with information on where items
are located and where they need to be placed on a cart, freeing pickers’ hands of paper instructions.

45. CASE: VOLKSWAGEN
Volkswagen rolls out 3D smart glasses as standard equipment. Plant logistics personnel are to use these glasses for order picking. The
objective is to further improve process security in production.

46. Machine
Learning

47. MACHINE LEARNING IN LOGISTICS
Demand forecasting
Supply forecasting
Production planning
Stock analytics
Recommendations in drop
shipment business
Inventory planning
Price planning
Speech recognition
By means of machine learning technology the computer may be taught to reveal certain regularities and to perform certain operations,
for example, calculation of the shortest delivery route of delivery, instant calculation of the transportation cost and optimization of
schedules, fleet.
Order aggregation
Effective route planning
Accidents predictions
Schedule optimization

48. CASE: DHL
DHL introduced supply chain risk management platform called DHL Supply Watch. The platform uses machine learning and natural
language processing to detect disruptions in a company's supply base before they cause financial losses or long lasting reputational
damage.
Supply Watch monitors some 140 different
risk categories including financial,
environmental and social factors
The system analyzes data of up to 30 million
posts from more than 300,000 online and
social media sources to detect potential
supply chain disruptions

49. CASE: UBER
Uber’s Head of Machine Learning Danny Lange confirmed Uber’s use of machine learning for ETAs for rides, estimated meal delivery
times on UberEATS, computing optimal pickup locations, as well as for fraud detection.

50. Omni-
channel

51. OMNI-CHANNEL IN LOGISTICS
High-performing, cost-effective
omni-channel fulfillment network
• Flexible dynamic omni-channel warehouses
• Leveraging warehouses as showrooms
• Logistics marketplaces and real-time
consumer engagement
Enhance speed, flexibility and
convenience in last-mile delivery
• Anytime, anywhere delivery models
• Range of omni-channel value-added
services
• Increasing microwarehouses
Building an omni-channel sales model is completely new task for the retailer. Omni-channel strategy includes two interrelated blocks:
marketing / sales and logistics. In case of the first block, the tasks are solved relatively easily, where the logistics for most retailers
becomes a serious challenge.

52. CASE: WALMART
Walmart debuted its Walmart Pickup Grocery service to registered customers. The test concept, which is a free service, allows customers
to place their orders online any time and pick them at special stations.

53. CASE: TMALL.COM & JACK & JONES
China’s largest B2C website Tmall.com is exploring a ‘bricks-and-clicks’ delivery system with Jack & Jones, a Danish male apparel retailer.
When Tmall.com receives an online order, the IT system analyzes merchandise availability and dispatches from the store that’s closest to
the customer.

54. THANK YOU FOR ATTENTION!
Alex Isachenko, CEO, Managing Partner, CoreTeka +380 93 570-56-28, isachenko@coreteka.com