8 Logistics Logistics

[Logistics5] Too much paperwork

Submitted by admin on Thu, 08/18/2022 - 01:17

Too much paperwork

[Logistics4] Poor driver safety

Submitted by admin on Thu, 08/18/2022 - 01:11

Poor driver safety

[Logistics3] Inefficient management of stock levels and operations

Submitted by admin on Thu, 08/18/2022 - 01:04

Inefficient management of stock levels and operations

[Logistics2] Inefficient delivery process and resource planning

Submitted by admin on Thu, 08/18/2022 - 00:41

Inefficient delivery process and resource planning

[Logistics1] High operating costs

Submitted by admin on Thu, 08/18/2022 - 00:28

High operating costs

5G for Logistics

5G for Energy
5G for Energy

Fueling Smart Deliveries

Pain points in the Logistics industry

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Pain Point 1

High operating costs

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Pain Point 2

Inefficient delivery process and resource planning

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Pain Point 3

Inefficient management of stock levels and operations

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Pain Point 4

Poor driver safety

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Pain Point 5

Too much paperwork

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How 5G-enabled digital solutions can help

Autonomous drones and robots enabled by 5G for seamless last-mile delivery.

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Drones suitable for:
  • Beyond line of sight flying
  • Able to carry freight
  • Drone (e.g., AI) capable of performing first level intervention in case of issues

Step 2: Connectivity

Step 2: Connectivity More Information
  • Images and flight information transmitted to edge and enterprise storage

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • 5G grants continuous feedback of delivery status and ability to make decisions to intervene real-time
  • Handles changes in delivery

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data is stored in enterprise data storage, where data ownership belongs to the company

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Non-critical MV/ML models execution
  • E2E automated processes by default

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Operators are alerted only in cases of issues that are unable to be solved by AI

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Drones to operate on 5G as a first choice assuming complete network coverage, otherwise on 4G network or on satellite communication (features reduced base on network capabilities).
  • Where 5G is used, data can be processed and analysed real-time at the edge using AI (ML) models.
  • Interventions can be done in real-time and therefore have minimum impact on the drone whilst still flying.
  • Both images and other data (weather/flight path info/etc.) will be collected.

Scenario 2

  • Understand built-in features of the drone and capabilities of built-in software: AI (ML/MV); etc. Maximise what can be done here since it is most efficient.
  • Decide what other AI (ML/MV) models need to be added.
  • SME and data scientists as a team will be required to develop these models.
  • It is possible that 2 teams will be required to focus on ML and MV respectively.

Scenario 3

  • Most of the AI work will be Edge-based given the real-time nature of autonomous drones to perform delivery.
  • Be aware that in most countries you need a license for these drones.
  • Take an incremental approach with the number of routes.
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Expected benefits

  • Delivery at last mile through drones reduces dependency on drivers and conditions of road traffic, reducing HSSE incidents
  • Faster deliveries especially in cases of emergencies and rural areas

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

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Key value created

  • Increased delivery efficiency with reduced costs and time spent

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

COGNITE
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How 5G-enabled digital solutions can help

Use of multiple sensors to track packages and delivery trucks in real time, using AI/ML, to optimise for prioritisation.

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Sensors (own and third-party) deployed to track delivery vehicles, routes, weather, ESG, traffic and conditions of packages and temperature

Step 2: Connectivity

Step 2: Connectivity More Information
  • Data transmitted to edge and enterprise storage

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Not time critical at present, however this is expected to change in the future

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data is stored in enterprise data storage, where data ownership belongs to the company

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Non-critical MV / ML models execution
  • Most AI will be done here since initially it is not time critical but that will change over time

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • AI models to provide recommendations to optimise parcel distribution, driving routes, and predict need for additional resources

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Sensors deployed on vehicles and critical packages will provide data to track parcel from warehouse to delivery.
  • Other data should be collected such as resource availability and utilisation of all delivery centres.
  • Environmental requirements such as temperature of the goods.
  • Collect HSSE-related data.

Scenario 2

  • Data collected will provide views such as:
  • Ed-to-end delivery time
  • Conditions of packages in transit,
  • Utilisation of vehicles (vehicle usage and storage capacity of vehicle)
  • Delivery centre utilisation
  • AI (ML) model developed by SME and data scientists as a team to provide insights and recommendations.

Scenario 3

  • AI Models could provide various recommendations based on historical data collected, such as:
  • Changes in parcel route in distribution centres
  • Driver routes and vehicle utilisation changes for optimum efficiency
  • Predict resource needs (vehicles, drivers) during seasonal periods and act accordingly
  • Changes due to traffic
  • Company rules around traffic (such as for FEDEX, no left turns in the route)
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Expected benefits

  • Optimise delivery process and distribution routes for maximum efficiency
  • Efficient and fast deliveries
  • Ability to plan ahead and increase or reduce resources to meet demand

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Optimised cost and improved efficiency of deliveries

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

COGNITE
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How 5G-enabled digital solutions can help

Manufacturing efficiencies can be greatly improved by exploiting AI (ML) to predict the optimum stock levels, utilising automation such as autonomous vehicles, etc.

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Obtain information on stock levels through various sensors, e.g., drones, cameras, systems, etc.
  • Add data to support autonomous vehicles
  • Ideally 5G-based to support real-time

Step 2: Connectivity

Step 2: Connectivity More Information
  • All data collected to be transmitted to cloud
  • Time series data
  • Asset data

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Real-time required for autonomous vehicles and temperature control
  • Not required for stock level monitoring

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data is stored in enterprise data storage, where data ownership belongs to the company

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Both MV and ML models to be developed and operated
  • Predict stock levels on data collected

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Operators are alerted only in cases of issues that are unable to be solved by AI

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Collect data from as many sources as possible, where data sources need to be aligned to get the best information about stock levels.
  • Collect information on stock inflow and outflow trends, and conditions that could influence the trend, e.g., weather, seasons, holidays, market changes, etc.
  • Include all historical information.

Scenario 2

  • Data required for real-time processing will be used at the Edge and all data will be collected in the enterprise storage.
  • Develop the AI (ML) model based on all data gathered.
  • SME involvement working with data scientists is required to develop the models.

Scenario 3

  • Based on learnings from the models, improve the quality of the data sources, review changes of data sources for the model to provide predictions on required stock levels.
  • Over time, stock levels can be reduced as accuracy of predictions improves.
  • Move towards autonomous operations in steps, such as in deployment of AGVs.
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Expected benefits

  • Increase accuracy of present stock and forecasting of demand
  • Optimise resources required and leverage autonomous operations
  • Smaller warehouses required with lower risk and cost in line with reduced stock levels

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Reduction in stocks leads to lower maintenance cost and risk

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

COGNITE
icon

How 5G-enabled digital solutions can help

Use of onboard dashcams and vehicle telematics to monitor driver behaviour in real-time and trigger alerts immediately once any abnormal behaviour is detected.

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Sensors (cameras, etc.) installed within the truck to monitor driver's behaviour
  • Other sensors keep track of speed, driving etc., possibly from standard sensors already in the truck

Step 2: Connectivity

Step 2: Connectivity More Information
  • All data collected to be transmitted to cloud
  • Critical data and AI processing at the Edge compute

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Located within vehicle
  • Most of the data collected will be processed in real-time 🡪 Action in real-time as well

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data is stored in enterprise data storage, where data ownership belongs to the company

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • Refine detection models such as drowsiness, attention to the road, etc.
  • New models deployed back to Edge for real-time automated alerts

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Alert operations only in the case of exceptions

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Most modern trucks collect tracking data, so additional sensors can be added to obtain a complete picture when needed.
  • High-definition camera video with 5G could allow better behavioural detection and real-time feedback loop while driving.

Scenario 2

  • Data required for real-time processing will be used at the Edge, all data to be collected in the enterprise storage.
  • Develop the AI (ML/MV) model based on all data gathered.
  • SME involvement working with data scientists is required to develop the models.
  • Modeling to expand on what is existing within current tracking solution.

Scenario 3

  • Better driver behaviour will allow goods to be delivered safely, reduce accidents and casualties, and improve staff welfare.
  • Models could be further improved to provide pre-emptive alerts to take possible actions (e.g., taking breaks when driving time exceeds limit, alert when entering high accident rate zones) with additional data such as weather forecasts, traffic conditions, and historical road incidents.
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Expected benefits

  • Predicting and avoiding accidents to enhance worker safety
  • Improve reaction time to address incidences

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Reduced accidents and casualties for a safer workforce

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

COGNITE
icon

How 5G-enabled digital solutions can help

Collecting all relevant data in a storage and use reporting/AI/etc. to make end-to-end procedures.

Data flow

Step 1: Devices

Step 1: Devices More Information
  • Sensors and input devices required to collect relevant data
  • Where needed, add sensors to collect more data
  • Interfaces to more systems

Step 2: Connectivity

Step 2: Connectivity More Information
  • All data collected to be transmitted to cloud
  • Critical data and AI processing at the Edge compute

Step 3: Edge Compute

Step 3: Edge Compute More Information
  • Data collected required for real-time processing, hence the importance of 5G

Step 4: Cloud Compute & Storage

Step 4: Cloud Compute & Storage More Information
  • All data is stored in enterprise data storage, where data ownership belongs to the company

Step 5: Applications & Services

Step 5: Applications & Services More Information
  • AI activities applied on historical data to improve planning and operations
  • New models deployed back to Edge for automated alerts

Step 6: Inform Decision Makers

Step 6: Inform Decision Makers More Information
  • Alert operations only in the cases of exceptions

Step 7: Support Decision Making

Step 7: Support Decision Making More Information
  • End of process

Application logic

Scenario 1

  • Identify relevant data sources required and sensors required for data collection.
  • Sensors could be of such as cameras or scanners to automate data collection.
  • Define and implement E2E business workflows to stop and minimise paper flows.

Scenario 2

  • Integrate data and determine storage location (edge and/or cloud storage), and also evaluate:
  • Automation of flow of information
  • Methods to link data sources
  • Methods to integrate use of mobile devices with rest of information flow
  • Advantages that 5G-Edge could provide
  • Based on all data collected, the flow of information is created.

Scenario 3

  • Based on the flow of information, AI (ML/MV) models to be developed.
  • Right SME expertise together with data scientists required to build a proper model.
  • Incremental approach – start with simple tasks and expand over time.
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Expected benefits

  • Improve productivity by reducing data entry work
  • Accurate information collection
  • Data collection in real-time enabling immediate action

Note: 

iconAI – Artificial Intelligence

iconML – Machine Learning

iconMV – Machine Vision​

iconSME – Subject Matter Expert

iconP&ID - Piping and Instruments Diagram

iconGHG - Greenhouse Gas

iconIT - Information Technology

iconOPAF - Open Process Automation Forum

iconOT - Operational Technology

icon

Key value created

  • Increased work efficiency

Email us at:

enterprise@digital-nasional.com.my

Phone number:

0123456789

Potential

COGNITE

Cross-industry solutions

Autonomous robots and aerial drones can traverse harsh and dangerous environments and reduce hazard risks for human workers. Such technology will provide enhanced monitoring and safety upkeep for facilities. They can be fitted with various sensors geared towards the purpose they are meant for and by using 5G, we can deploy them in real-time whereby the data collected can be sent directly to an AI application for investigation and immediate further action.

Wearable technology allows security and medical personnel to conduct background and health checks efficiently. Of course, they have a much broader focus and can be used in many different industries where clothing has been enriched with wearable technologies. Wearables are also able to collect extra information for a 5G-enabled digital service.

Sensors are crucial for capturing real-time data and insights and pave the way for more informed decision-making. Sensors will be the data collection point for every 5G-enabled digital service and therefore will have to cover a broad spectrum of types of information to be collected and the way they are connected to the DNB 5G network.

XR is set to take work and play to the next level with cutting edge technology never seen before. These devices have the potential to boost productivity and enhance entertainment, changing the way we experience our reality through digital transformation. There is an increasing broad spectrum of devices available for both consumer and enterprise markets, making it increasingly important for each user experience.

DNB Ecosystem

Disclaimer of Endorsement

All information provided on potential 5G-enabled solutions and potential vendors is provided for information purposes only and based on our awareness of the available 5G-enabled solutions and potential vendors in the market. It does not constitute endorsement, recommendation or favouring by DNB. It is your responsibility to verify and evaluate such 5G-enabled solutions and potential vendors. DNB is not an agent or legal representative of any of such 5G-enabled solutions and potential vendors, is not associated or endorsed by such potential vendors, has no authority to act on behalf of any such potential vendors, and will be an independent party if you enter a business relationship with such potential vendors. Third party links included are for convenience only and are not under DNB’s control. DNB does not assume any responsibility or liability for your use of such third-party links.

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