Iit mumbai first and last leg optimization
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IIT Mumbai – First and Last Leg Optimization. CONFIDENTIAL May, 2012. Freight Flow -1 . Pickup. Delivery. CFS/ Destination Warehouse. Destination Port. Customers. Freight Flow -2. Seller. CFS. Origin Port. Freight Flow - 3. Trucking Industry Level Challenges.

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IIT Mumbai – First and Last Leg Optimization

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Iit mumbai first and last leg optimization

IIT Mumbai –First and Last Leg Optimization

CONFIDENTIAL

May, 2012


Freight flow 1

Freight Flow -1

Pickup

Delivery


Freight flow 2

CFS/

Destination

Warehouse

Destination Port

Customers

Freight Flow -2

Seller

CFS

Origin Port


Freight flow 3

Freight Flow - 3


Trucking industry level challenges

Trucking Industry Level Challenges

  • Infrastructure Issues and Challenges

    • Congestion

    • Operational inefficiencies

    • Non standard trucks

    • Under utilization of infrastructure available.

    • Supply demand mismatch

  • Institutional Issues

    • Highly Fragmented industry

    • Manual, non-uniform or discrete processes across the industry

    • Non-availability of Quality manpower

  • Technological Issues

    • Old technology

    • Adoption of new technologies is expensive

    • No clear Return on Investments for New Technologies

    • Manual processes leading to operational inefficiencies


  • Solutions and strategies largely capital intensive

    Solutions and Strategies (Largely Capital intensive)

    • Vehicle Size and Delivery Time Regulations

    • Load Consolidation and Load Factor Efficiency (Load consolidation, or co-loading)

    • Urban Distribution Centers

    • Freight Villages - Different from urban distribution centers, but similar in concept. Freight villages are planned unit developments specifically designed for multi-modal freight transfer within a secured perimeter.

    • Delivery Tunnels - In Helsinki, freight tunnels for underground trucking are planned

    • Dedicated freight corridors – are they really helping urban areas ?


    Inefficiencies in the current process

    Inefficiencies in the current process

    • Pickup driver has to visit the terminal to collect the list of pickups

    • Planning for linehaul, cross-docking, resource requirements, delivery plans etc are not possible till the goods reaches to the terminal

    • There is no update on the status of delivery till the driver reports back to the terminal.

    • This process is time consuming and lead to inefficiencies such as

      • missed pickups and missed appointments,

      • excessive waiting times during pickups and deliveries resulting in additional driver hours and under utilization of trucks

      • postponing pickups

      • additional kilometers operated by drivers thus additional fuel consumption and choking of traffic

      • no clue on the traffic situation on the network – no route guidance


    Solution components and business model

    Solution Components and Business Model

    • Solution Components

    • Vehicle Tracking System - Telematics

    • Pickup and Delivery Management System – to plan the pickups and deliveries

    • Handheld Mobile devices – Scanner, data logger etc

    • Route Planner to generate optimal routes

    • Central Server and communication systems

    • Transportation Management System

    • Platform based solution

    • Benefits

    • From Trucking companies Perspective

    • Trucking company can register with minimum fee

    • Trucking companies can pay as per use

    • Opex and No capital investments – Transaction based

    • Can withdraw when not required

    • No technology skills required

    • Improved visibility of shipments, high asset utilisation, less fuel costs and customer satisfaction

    • From Service Provider perspective

    • Multiple trucking companies can be hosted on single software platform.

    • Other services such as reports, performance indicators can be sold as value added services

    • From City/Governance perspective

    • Less Pollution and congestion

    • Real time and accurate data for traffic alerts

    • Trustworthy and huge volume of data for / Freight Modelling/ infrastructure planning and real time decisions


    Overview an example for auto route generation

    Overview – An example for Auto Route Generation

    9


    As is routes

    As-Is Routes

    • Features considered

    • Routes are planned for a region.

    • A truck will be assigned/reserved for route

    • Static route is generated by the route planner

    • Dispatcher assigns new stops to the route manually as and when new orders are to be handled

    Parameters for comparison

    10


    To be routes

    To-Be Routes

    • Features considered

    • No region based routes

    • Routes will be developed as per the order/stop locations

    • Algorithm based route generation

    • Optimises the number of trucks required rather than the truck-km

    Parameters for comparison

    11


    Data for analysis

    Data for Analysis

    • Available Data for Analysis

    • Driver Data

    • Equipment Data

    • Order Data

    • Trip Data

    • Stop Data (including Stop to Stop Distance Data)

    • Output Expected

    • Optimized Route with route parameters

    12


    Business benefits

    Business Benefits

    • Reduced P&D Costs (They represent around 30% of total cost in the case of road based movement)

    • Improved Route Planning

    • Effective Equipment utilization

    • Effective Utilization of Drivers

    13


    Thank you

    Thank You

    http://www.tcs.com

    CONFIDENTIAL

    May, 2012


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