A SYSTEM AND METHOD FOR OPTIMIZATION OF A ROBOTIC AUTOMATED WAREHOUSE AND A TASK MANAGER SYSTEM THEREOF

1 . A task manager system for a warehouse, said task manager system comprising:

an input data utility being configured and operable for receiving (i) at least one maintenance task to be performed in the warehouse, wherein the at least one maintenance task comprises at least one of replenishment, consolidation, cycle count, space reduction, warehouse maintenance, recall or replacement of batteries; (ii) a time data being indicative of a predetermined period of time at which the preparation of orders to be prepared using items from the warehouse should be completed, and (iii) warehouse resources to be attributed in the predetermined period of time including at least one of a predefined number of picking stations being associated with a certain number of picker persons and a predefined number of robots;

a processor being configured and operable for:

processing the time data by performing a plurality of simulations on a plurality of optimization parameters for the given time data, and generating a simulation data including a plurality of sets of optimization parameters, wherein the sets of optimization parameters include the warehouse resources and allocation of at least one maintenance task;

determining a selected set of optimization parameters based on the simulation data including the allocation of at least one maintenance task to be completed together with the preparation of the orders and an optimized attribution of the resources of the warehouse to thereby generate a recommendation optimization data regarding an optimization of a warehouse, wherein the recommendation optimization data comprises the selected set of optimization parameters, and an output data utility being configured and operable for provide the recommendation optimization data; wherein the recommendation optimization data enables to control and change in real-time or by anticipation the different attributions of the resources of the warehouse.

2 . The task manager system of claim 1 , wherein said selected set of optimization parameters further comprises at least one maintenance task parameter, wherein said at least one maintenance task parameter comprises at least one of a certain number of at least one of box and item to replenish, a number of cycle count, a number of consolidation and/or recall task.

3 . The task manager system of claim 1 , wherein said processor is configured and operable for receiving order data being indicative of the orders to be prepared using items from the warehouse.

4 . The task manager system of claim 1 , wherein the order data comprises at least one order line or recall data.

5 . The task manager system of claim 4 , wherein each order line comprises at least one order related parameter including an item identifier, a due date data for supplying the item and a quantity.

6 . The task manager system of claim 5 , wherein the due date data comprises an expected delivery due date and/or an indication for a prioritized handling.

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8 . The task manager system of claim 1 , wherein the recommendation optimization data comprises a plurality of options, each option being indicative of a different optimization of the plurality of the optimization parameters.

9 . The task manager system of claim 2 , wherein said order data is received from a customer management system and said time data is received from an operator, the customer management system and the operator being in data communication of the processor.

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11 . The task manager system of claim 2 , wherein the order data comprises predicting data being indicative of at least one of predicted orders enabling to provide a recommendation optimization data being related to special events.

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13 . A method for optimizing warehouse management, the method comprising obtaining, by at least one computerized system, (i) at least one maintenance task to be performed in the warehouse, wherein the at least one maintenance task comprises at least one of replenishment, consolidation, cycle count, space reduction, warehouse maintenance, recall or replacement of batteries; (ii) a time data being indicative of a predetermined period of time by which the preparation of commanded orders should be completed, and (iii) warehouse resources to be attributed in the predetermined period of time including at least one of: (1) a predefined number of picking stations; (2) a number of human pickers associated with each of the predefined stations and (3) a predefined number of robots; generating a plurality of optimization parameters comprising the warehouse resources and allocation of at least one maintenance task, the generating comprising performing a plurality of simulations using different resource attribution parameters; determining a selected set of optimization parameters based on the simulation data, the selected set of optimization parameters including (a) the allocation of at least one maintenance task to be completed together with the preparation of the commanded orders and (b) an optimized attribution of the resources of the warehouse, to thereby generate a recommendation optimization data regarding an optimization of a warehouse.

14 . The method of claim 13 , further comprising one or more of the following: receiving together with the time data an order data being indicative of orders to be prepared using items from the warehouse; receiving historical data being indicative picking parameters including averaged picked-up time; receiving a predicting data being indicative of at least one of predicted orders enabling to provide a recommendation optimization data being related to special events.

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20 . The method of claim 13 , wherein the order data is received from a customer management system and said time data is received from an operator, the customer management system.

21 . The method of claim 13 , wherein generating the recommendation optimization data comprises generating the recommendation optimization data before the preparation of the orders including the day at which the orders are prepared or at least one day before the preparation of the orders or in real-time during the preparation of the orders.

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25 . At least one non-transitory computer readable medium that stores instructions that once executed by a computerized system causes the computerized system to execute a process for optimizing a warehouse management according to claim 13 .

26 . An automated warehouse that comprises:

a storage configured to store multiple items, wherein the multiple items are stored in item containers;

a plurality of picking stations that comprise at least one picking station;

one or more robots that are configured to convey item containers to the plurality of picking stations; and

the task manager system of claim 1 .

27 . An optimization system for use in automatic warehouses comprising: a plurality of independent management modules, wherein each management module is configured and operable to manage different warehouse tasks including at least one of items location or one or more optimization tasks and to generate a recommendation optimization data for a selected period of time comprising a plurality of optimization parameters; and a processing unit being configured and operable to control a-said plurality of independent management modules, providing prioritization between the independent management modules and an optimal operation of each management module in order to enable at least one of: maximal number of orders to be prepared per the selected time period, performing in the selected time period at least one maintenance task.

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30 . The optimization system of claim 28 , wherein the processing unit is configured and operable to receive the recommendation optimization data generated by each independent management module to selectively operate one or more of the independent management modules, to optimize the timing of the different warehouse tasks and to provide an optimal recommendation optimization data of each independent management module taking into consideration the recommendation optimization data provided by the other management modules.

31 . The optimization system of claim 28 , wherein the plurality of independent management modules comprises at least two of the following modules: a mission planner management module configured and operable to process task data and generate based thereon recommendation optimization data being indicative of prioritization between the plurality of tasks to be performed: an order management module configured and operable to generate recommendation optimization data being indicative of prioritization between item containers to be moved to one or more picking stations based in accordance with a due time data: an inventory management module for processing at least one item container data and warehouse map data for generating a recommendation optimization data including an optimal location data being indicative of a specific optimal location at which the at least one item container is to be positioned on the storage: robot navigation management module configured and operable for receiving request data being indicative of a change of location of at least one robot and generating recommendation optimization data indicative of an optimal path for the at least one robot, wherein the optimal path includes at least one of a fastest path, shortest path, and most energy efficient path, and a task management module.

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36 . The optimization system of claim 31 , wherein the optimal location data is determined in accordance with one or more location optimization parameters including at least one of location history data of items, weather, and accordingly temperature at different locations in the warehouse, or discounts on items.

37 . The optimization system of claim 31 , wherein the optimal location data comprises data being indicative of at least one of a proximity to a picking station or a height from the ground.

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41 . The optimization system of claim 27 , wherein the processing unit is configured and operable to selectively operate the independent management modules by applying one or more optimization algorithms on the plurality of the optimization parameters including simulations on the plurality of the optimization parameters and applying different weights on each independent management module.

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44 . The optimization system of claim 41 , wherein the processing unit is configured and operable to divide the selected time period into a plurality of sub-time periods, and wherein the applying of different weights on each independent management module comprising changing the different weights on each independent management module on each sub-time period.

45 . The optimization system of claim 41 , wherein the one or more optimization algorithms comprises clustering optimization, classification, artificial neural networks, deep neural network, reinforcement machine learning, or deep reinforcement learning in combination with minimization of a weighted cost function.

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47 . The optimization system of claim 27 , wherein the processing unit is configured and operable to control the plurality of independent management modules in real-time to selectively operate an adequate management module performing the optimal warehouse task at the optimal time.

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