Autonomous supply and distribution chain

• US 10,380,534 B2
• Filed: 12/20/2017
• Issued: 08/13/2019
• Est. Priority Date: 03/11/2016
• Status: Active Grant

• Current Assignee: Route4Me, Inc.
• Original Assignee: Route4Me, Inc.
• Inventors: Khasis, Dan
• Primary Examiner(s): Elchanti, Hussein
• Application Number:
  US15/849,643
• Publication Number:
  US 20180158020A1
• Time in Patent Office: 601 Days
• CPC Class Codes: G01C 21/3415 Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
• CPC Class Codes: G01C 21/343 Calculating itineraries, i.e. routes leading from a starting point to a series of categorical destinations using a global route restraint, round trips, touristic trips travelling salesman problem G06Q10/04; optimisation of routes G06Q10/047
• CPC Class Codes: G01C 21/3453 Special cost functions, i.e. other than distance or default speed limit of road segments
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities

Abstract

Methods and systems for an autonomous supply and distribution chain management network are disclosed. A server may control and coordinate the processes involved in distributing a product from suppliers to the customers, including generation of purchase orders and payment of invoices. A defined set of interactions may occur in a particular sequence and at designated times that may permit the chain to be synchronized between a customer and a supplier. Unlike a regular supply and distribution chain, in which human beings decide vehicle or asset compatibility types, the autonomous chain of the present invention may maintain a compatibility database within the platform, as well as detailed information about each asset and how it can function interactively with the others. The invention may also allow for dynamic modification of transit operations to alter one or more destinations of the inventory while it is in transit to a new location at any time.

Claims

1. A machine-implemented method, comprising:

coordinating at least one of a sourcing procedure, a procurement procedure, a conversion procedure, a logistic procedure, and a collaboration procedure,

wherein the coordinating is of an autonomous mode or a semi-autonomous mode,

wherein the autonomous mode does not include operator intervention,

wherein the semi-autonomous mode permit operator intervention;

receiving a customer demand;

analyzing the customer demand to determine whether the customer demand is valid, wherein a valid customer demand comprises compliance with a contract term;

determining inventory within supplier capacity;

receiving an asset'"'"'s telematics data;

calculating duration for one or more destinations;

calculating estimated arrival times of the destinations; and

determining one or more routes to the destinations based on at least one of an asset compatibility data, a financial constraint, an environment constraint and a geographic constraint;

wherein the route comprises assets arriving at a bottleneck location at a predetermined interval for preventing delays at the bottleneck location, and wherein the bottleneck location comprises a multi-modal facility.

2. The method of claim 1, further comprising:

wherein the asset compatibility data comprises operational constraints, and

wherein the operational constraints comprise a driver constraint, a vehicle constraint, a road constraint, a building constraint, and an environmental constraint.

3. The method of claim 1, further comprising:

wherein the asset compatibility data comprises mapping and analyzing one or more relational databases.

4. The method of claim 1, further comprising:

wherein determining the route comprises assigning the one or more destinations to the asset based on the duration of the one or more destinations.

5. The method of claim 1, further comprising:

re-routing the asset to a remaining assigned or unassigned destination after completion of each destination based on data of the remaining destination.

6. The method of claim 1, further comprising:

continually receiving the asset'"'"'s telematics data, calculating duration for one or more destinations, calculating estimated arrival times of the destinations, determining a delivery route to the destinations at predetermined intervals; and

altering the one or more destinations of the route while the route is in progress.

7. The method of claim 1, further comprising:

incorporating a business intelligence data into the determining of the route, and

wherein the business intelligence data comprises an additional amount of risk and cost data.

8. The method of claim 1, further comprising:

using artificial intelligence to determine underperforming assets based on the telematics data.