Decoupling and modular multi-channel order fulfillment system with control system adaptable to demand-driven flexibility and productivity

Abstract

An order fulfillment system for a warehouse according to the present invention comprises a control system (301), a memory (306), a modular inventory storage system (312) and a reconfigurable workstation (352). A control system (301) controls fulfillment activities of a warehouse (300), manages configuration of a workstation (352) for order fulfillment, inventory import, or order packaging, and records operational data (294) corresponding to the fulfillment activities in the warehouse (300). The control system (301) includes a plurality of workflows selected from a workflow library (304) stored in a memory (306). A memory (306) holds operational data (294). The selected workflow and the configuration of the modular inventory storage system (312) correspond to a current state of the warehouse (301) defined by the selected portion of the operational data (294) and the expected demand.

Description

Technical Field

[0001] This invention relates to a configurable order fulfillment and control system for warehouse environments, particularly by providing a decoupled and modular fulfillment system to dynamically manage the warehouse environment and order fulfillment process during periods of changing demand. Background Technology

[0002] Controlling order fulfillment systems within warehouse facilities with a variety of workers or agents (e.g., human pickers, robotic pickers, goods transport vehicles, conveyors, and other components of the order picking system) is a complex task. Traditional control methods are used to seek various objectives in increasingly complex order fulfillment environments characterized by a large SKU range, order compositions ranging from single to multiple SKUs, and order demands varying significantly in quantity and time scale, coupled with strict delivery deadlines. This complexity is further exacerbated by the fact that traditional warehouse environments have historically relied on "unchanging" automated and manual hardware and processes, where the warehouse environment may be able to handle current daytime order fulfillment operations but its scalability and flexibility are limited in the face of rapidly changing demands and needs. Summary of the Invention

[0003] Embodiments of the present invention provide methods and systems for decoupling and modularizing order fulfillment systems with intelligently coordinated and dynamic workflows to achieve demand-driven flexibility and productivity. Such order fulfillment systems can be used in a variety of environments, such as e-commerce fulfillment centers, warehouses, and micro-fulfillment centers. Exemplary embodiments are configured to dynamically change the way orders are fulfilled in real-time or near real-time based on, for example, customer demand, available resources, and resource optimization via intelligent coordination, thereby flexibly adapting dynamically reconfigurable physical infrastructure and associated workflows to changing demands. This dynamic reconfigurability includes, for example, the flexible addition or reduction of order fulfillment capacity, temporarily or permanently (e.g., reconfigurable workstations, additional inventory storage, human or robotic workers, and flexible automation and control solutions), and the ability to adjust over time to achieve flexible modular expansion / reduction. Exemplary embodiments and methods for multi-channel order fulfillment include combinations of fixed automation, flexible mobile automation, and modular process / control systems. Exemplary fixed automation includes automated storage and retrieval systems (AS / RS storage systems) and unit sorting systems (e.g., cross-belt sorters, sorting mezzanines, and Bombay sorters). Exemplary mobile automation includes bin transportation by autonomous mobile robots (AMRs), such as bin-to-person AMRs, inventory sorting and routing AMRs, and customer-specified solutions (e.g., shelf-to-person AMRs). Exemplary modular process / control systems include dynamically reconfigurable warehouse controllers, control systems or coordinators, fulfillment control and monitoring systems, warehouse management systems (WMS), warehouse execution systems (WES), and supply chain management systems.

[0004] The warehouse order fulfillment system according to the present invention includes a control system, a memory, a modular inventory storage system, and reconfigurable workstations that can be operationally reconfigured, wherein the control system can modify fulfillment operations using the modified system without reprogramming. The control system controls warehouse fulfillment activities, manages the configuration of workstations for order fulfillment, inventory import, or order packing operations, and records operational data corresponding to fulfillment activities in the warehouse. The control system contains multiple workflows selected from a workflow library. The memory stores the operational data. The configuration of the selected workflow and the modular inventory storage system corresponds to the current state of the warehouse defined by the selected portion of the operational data.

[0005] According to one embodiment of the present invention, a method for controlling order fulfillment activities in a warehouse includes controlling the fulfillment activities in the warehouse. The method includes managing the configuration of workstations for order fulfillment, inventory import, or order packing operations. Furthermore, it also controls the configuration of a modular inventory storage system. The method includes recording operational data corresponding to the fulfillment activities in the warehouse. This operational data is stored in a memory. The configuration of the control and storage system for fulfillment activities in the warehouse is defined by a plurality of selected workflows selected from a workflow library. The selection of workflows and the configuration of the modular inventory storage system correspond to the current state of the warehouse defined by selected portions of the operational data and anticipated demand.

[0006] In one aspect of the invention, the order fulfillment system includes a unit sorting system comprising a plurality of autonomous mobile robots (AMRs), each AMR configured to move inventory items from one location to the next desired location.

[0007] In another aspect of the invention, the modular inventory storage system incorporates one or more different storage technologies. Specific storage technologies can be used to add or remove additional storage modules to the modular inventory storage system, or to add or remove additional storage resources from modules of the modular inventory storage system, depending on current or anticipated needs.

[0008] In another aspect of the invention, the workflow control module includes one or more function calls, each function call being a microservice.

[0009] In another aspect of the invention, the reconfigurable workstation can perform one of the following operations: order fulfillment, inventory import, or order packaging. The reconfigurable workstation can also be configured for use by humans and / or robots.

[0010] In another aspect of the invention, the control system is capable of determining or identifying the priority of newly received orders. If the priority of a newly received order is higher than that of a previously received order, inventory allocated to one or more previously received orders can be reallocated to the newly received order as needed to satisfy the customer service level agreement (“SLA”) for the newly received order.

[0011] Therefore, the present invention provides an adaptive system and method for order fulfillment activities within a warehouse facility, configured to dynamically adapt to current operating conditions and / or anticipated needs. By using a modular storage system, reconfigurable workstations, and a control system employing optional workflow control modules selected from a library of workflow control modules, order fulfillment activities can adapt to changing conditions in real-time or near real-time. Such adaptations include dynamically increasing or decreasing inventory storage space, reconfiguring workstations to perform selected order fulfillment activities or inventory import / dispensing operations, and updating selected workflow control modules chosen from the library of workflow control modules. These and other objects, advantages, uses, and features of the invention will become apparent upon reading the following description in conjunction with the accompanying drawings. Attached Figure Description

[0012] Figure 1A This is a schematic top view of an exemplary configurable order fulfillment and control system according to the present invention;

[0013] Figure 1B This is a block diagram illustrating an exemplary aspect of a fulfillment / warehouse facility employing a control system according to the present invention;

[0014] Figure 2 This is a block diagram illustrating components of an exemplary order fulfillment system for a warehouse facility according to various aspects of the present invention;

[0015] Figure 2A This is a block diagram illustrating the operation and control components of an exemplary order fulfillment system;

[0016] Figure 2B This is a block diagram illustrating components of another exemplary order fulfillment system for a warehouse facility according to the present invention;

[0017] Figure 3 This is a block diagram illustrating the components of an exemplary order fulfillment system and a method for controlling a related control system according to the present invention;

[0018] Figure 4 This is a block diagram illustrating the architecture of an exemplary order fulfillment system according to the present invention;

[0019] Figure 5 This is a perspective view of an exemplary storage system of the order fulfillment system according to the present invention;

[0020] Figure 6A and Figure 6B This is a flowchart illustrating the steps of a method for operating an exemplary import / goods-to-person (GTP) workstation for controlling an order fulfillment system according to the present invention;

[0021] Figure 7This is a flowchart illustrating the steps of a method for performing picking verification at a workstation using an order fulfillment system according to the present invention;

[0022] Figure 8A This is a block diagram illustrating the functional control steps of the tasks to be performed in the order fulfillment system according to the present invention;

[0023] Figure 8B This is a block diagram illustrating the functional control steps of another task to be performed in the order fulfillment system according to the present invention;

[0024] Figure 9 This is a flowchart illustrating the steps of a method for reallocating inventory from one order to another based on order priority according to the present invention; and

[0025] Figure 10 This is a schematic diagram of the user interface of the control system according to the present invention. Detailed Implementation

[0026] The invention will now be described with reference to the accompanying drawings, wherein the numbered elements in the following written description correspond to the same numbered elements in the drawings. While conventional warehouse environments (e.g., order fulfillment systems) traditionally rely on "fixed-state" automated and manual hardware and processes, where various components or subsystems are configured for specific, dedicated operations and are not adaptable, exemplary order fulfillment and control systems are configured to provide adaptable operational capabilities to avoid this "fixed-state" characteristic. Embodiments of the invention provide a method and system for decoupling and modularizing an order fulfillment facility with intelligently coordinated and dynamic workflows to achieve demand-driven flexibility and productivity. Exemplary embodiments are configured to dynamically change the way orders are fulfilled in real-time / near real-time based on, for example, customer demand and resource optimization via intelligent coordination, thereby flexibly adapting a flexible physical infrastructure and dynamically reconfigurable workflows to changing demands. Exemplary facilities include reconfigurable subsystems that are substantially automated and multifunctional for item storage, carton forming, receiving, picking, import / distribution, sorting, consolidation, and packaging. These different subsystems involve (but are not limited to) item storage, receiving, packing / importing, picking, sorting, packing trailer control, and carton forming. This dynamic reconfiguration capability includes the ability to flexibly increase or decrease order fulfillment capacity temporarily or permanently (e.g., reconfigurable multi-purpose workstations (e.g., picking, packing / importing, and / or packing), adding / reducing inventory storage to modular storage systems, human or robotic workers, and flexible automation solutions), and the ability to adjust over time, enabling flexible modular expansion / reduction. Such reconfigurable subsystems are controlled by a control system that selects operational workflows from a workflow library, chooses specific operational configurations for reconfigurable workstations, and adaptively controls inventory storage in the modular storage system without requiring reprogramming of the control system based on current operating conditions and expectations. Exemplary methods for multi-channel fulfillment include combinations of fixed automation, flexible mobile automation, and modular process / control systems. Exemplary fixed automation includes automated storage and retrieval systems (AS / RS) and unit (i.e., single item) sorting systems (e.g., cross-belt sorters and sorting mezzanines). Exemplary mobile automation includes box transport systems (e.g., box-to-person AMRs), sorting and inventory routing AMRs, and customer-specified solutions (e.g., shelf-to-person AMRs). Exemplary modular process / control systems include warehouse controllers, control systems or coordinators, fulfillment control and monitoring systems, warehouse management systems (WMS), warehouse execution systems (WES), and supply chain management systems.

[0027] The warehouse management system of the exemplary order fulfillment facility or master facility contains order information provided to the control system. As described herein, the control system controls the execution of orders (e.g., the aggregation and controlled release of orders (and the timing of these orders), inventory allocation to fulfill orders (including considering the reallocation of inventory to fulfill high-priority orders)) for fulfillment within the facility. The exemplary order fulfillment system contains multiple order channels. Each order channel can be defined based on its specific downstream resources and / or needs. For example, released orders may be used to pick items that are about to be sent to the downstream “sorting wall”, or to pick items placed in a grid by a large store or retail establishment. Other order channels include single-unit e-commerce, multi-unit e-commerce, retail / store, value-added services (VAS), etc.

[0028] Figure 1A and Figure 1B An exemplary warehouse environment or aspect thereof in the course of order fulfillment is illustrated. It should be understood that an order fulfillment system employing the control system according to the invention can be configured and used in various ways and environments using various configurations and different material storage and handling systems. Therefore, the following discussion... Figure 1A and Figure 1B The discussion of the system should be understood as non-restrictive and for illustrative purposes only.

[0029] refer to Figure 1A An exemplary configurable warehouse or storage facility for order fulfillment, used in conjunction with a control system according to various aspects of the present invention, is disclosed. As shown, the order fulfillment facility includes an inbound operation area A, an inbound flexibility area B, an order fulfillment area C, a consolidation and packout zone D, and a shipping operation area E. Figure 1A The various "zones" are defined / outlined with corresponding dotted lines. Inbound operation zone A includes receiving operation zone 102, which is configured to deliver items to parcel sorting zone 104 and offline / manual storage zone 106. Offline / manual storage zone 106 is part of order fulfillment zone C. Inbound flexibility zone B includes cross-docking zone 108 and receiving operation zone 102. (The text repeats itself here.) Figure 1A As shown, the receiving operation area 102 is part of both the inbound flexible area B and the inbound operation area A. The cross-docking area 108 receives items from the receiving operation area 102 and transports the items to the shipping execution area 110 of the shipping operation area E.

[0030] Order fulfillment area C includes an Automated Storage and Retrieval (AS / RS) shelf area 112 and a manual / offline storage area 106. AS / RS shelf area 112 and manual / offline storage area 106 are configured to store inventory items. As described herein, inventory items are picked from AS / RS shelf area 112 and manual / offline storage area 106, respectively, by picking areas 114 and 116, to fulfill orders. Order fulfillment area C also includes an "item" sorting area 118 for conveying items (e.g., individual items) from picking area 114 to pre-pack consolidation area 120. Figure 1A As shown, picking area 116 is configured to transport items to pre-packaging consolidation area 122. In one embodiment, single-item picking area 118 may also be configured to provide order line import (e.g., picking multiple identical SKUs). Figure 2B The distribution of sorted (individually sorted) items 282 in warehouse environment 200 is shown.

[0031] The consolidation and packing operation area D includes pre-packing consolidation areas 120 and 122 (which are considered part of both the consolidation and packing operation area D and the order fulfillment area C). While pre-packing consolidation area 120 transports items (e.g., in totes) to the order tote transport unit 124 for delivery to the packout area 126 (where items in totes are loaded into containers), pre-packing consolidation area 122 transports items (in totes) directly to the packout area 126. Finally, the shipping operation area E includes a shipping container sorter 128 and a shipping execution area 110. The shipping container sorter 128 receives shipping containers from the packout area 126, sorts them, and transports the totes / containers of the items to the shipping execution area 110.

[0032] refer to Figure 1B The exemplary repository environment includes several different agents: 202, 204, and 206. Each type of agent has different characteristics, goals, and capabilities. Figure 1BThe agents shown include human pickers 202, robotic pickers (typically in the form of autonomous mobile robots (AMRs) 204), and item transport vehicles in the form of automated guided vehicles (AGVs) or autonomous mobile robots (AMRs) 206, configured to transport items picked by human pickers 202 and / or robotic pickers 204. Alternatively, AMRs configured to transport the picked items can be used instead of AGVs. The overall logistics of the warehouse will be distributed across agents 202, 204, and 206. Other agents will include fixed automated assets within the warehouse and fulfillment management systems (e.g., WES, WCS, and WMS). Agents 202, 204, and 206 are assigned and / or assigned to one or more order channels within the warehouse (managed by the order fulfillment system).

[0033] Multi-channel fulfillment:

[0034] An exemplary multi-channel order fulfillment system 300 is configured to meet a variety of customer order expectations (a wide range of product options, next-day or same-day delivery, streamlined returns and exchanges, and competitive pricing). These customer order expectations are expected to change over time, increasing the complexity of the multi-channel fulfillment system 300. That is, the best or optimal way to fulfill an order at one point in time (such as today) may not be the best or most efficient way to fulfill an order at another point in time (such as tomorrow (or some future day), or even another time within the same day). Therefore, the infrastructure technology used in the order fulfillment system (and the associated fulfillment control system) will change as warehouse / order fulfillment system technology evolves. Furthermore, customers are expected to continue to change their buying habits and expectations, forcing companies to “keep up” to remain competitive.

[0035] Therefore, as companies need the ability to rapidly adapt their operations to customer needs and expectations, their order fulfillment systems will require the ability to change how tasks are completed within their respective systems, and the capacity to seamlessly integrate different technologies into their operations as needed. Furthermore, companies (and their fulfillment systems) need to leverage their data to better understand their operational performance, predict customer demand, and move towards a more autonomous, adaptive, and self-healing supply chain. To achieve this, the exemplary multi-channel order fulfillment system 300 requires a robust, reconfigurable supply chain control solution that provides configurable workflows leveraging (current) best-in-class distribution capabilities. The exemplary multi-channel order fulfillment system 300 optimizes and “coordinates” the work of any combination of people and machines, providing a holistic view of the facility, surrounding areas, and the entire supply chain, enabling data-driven autonomous decision-making.

[0036] refer to Figure 1A , Figure 2 and Figure 2A An exemplary multi-channel order fulfillment system 300 includes a control system 301, which is implemented by various hardware and software constituting one or more computer systems or servers, such as those operating in a network, including hardware and software, including one or more programs, such as programs for collaborative interoperability. For example, an exemplary embodiment may include hardware such as one or more controllers or processors configured to read and execute software programs. Such programs (and any associated data) may be stored and / or retrieved from one or more storage devices. The storage devices may be implemented as software-based, hardware-based, and / or hardware-and-software-based storage devices. The hardware may also include power supplies, networking devices, communication devices, and input / output devices for communicating with local and remote resources and / or other computer systems. Such control system embodiments may include one or more computer systems and optionally be communicatively coupled to one or more additional computer systems with local or remote access. Certain computer components of the exemplary embodiments may be implemented through local resources and systems, remote or “cloud”-based systems, or a combination of local and remote resources and systems. Software executed by a computer system of an exemplary embodiment may include or access one or more algorithms for directing or controlling the execution of a computer-implemented process, such as in an exemplary warehouse order fulfillment system. As described herein, such algorithms define the sequence and coordination of process steps performed by the exemplary embodiment. Also as described herein, improvements and / or refinements to the algorithms will improve the operation of the process steps performed by the exemplary embodiment based on the updated algorithms. The control system 301 of the order fulfillment system described herein may include a warehouse control system (WCS). As described herein, control system 301 may include an order fulfillment control and monitoring system 302, a warehouse management system (WMS) 303, a warehouse execution system 304, and a supply chain management system 305. Although Figure 2A The components of the warehouse control system 301 are shown, but these components may be grouped in different ways or implemented as separate components.

[0037] like Figure 1A and Figure 2As shown, an exemplary multi-channel order fulfillment system 300 includes inbound and outbound functional areas controlled by relevant process controls. The inbound functional area includes subsystems (inbound operations and inbound flexibility), which include material handling modules (e.g., receiving operation area, inventory sorting area, and storage strategy area; and return operation area; and cross-docking area, respectively). The outbound functional area includes subsystems such as order fulfillment area, consolidation and packing operation area, and shipping operation area. These subsystems include material handling modules (e.g., packing area (robotic and manual packing), automated storage and retrieval system (“AS / RS”) area (e.g., Dematic Multishuttle® system (“DMS”), or Autostore® warehouse system, etc.)), picking functions (e.g., robotic and manual picking), and “single item” picking (AMR-based); order tow box / shipper sorting machine (AMR-based), pre-packaging consolidation area, carton forming area, and packing operation area (automatic and manual packing operations, respectively; and shipper container sorting (AMR-based) and shipping execution, respectively).

[0038] Figure 2B An alternative arrangement of components for a multi-channel order fulfillment system running in an exemplary warehouse environment 200 is shown. Figure 2B An exemplary warehouse software subsystem is shown, which is connected to a fulfillment control and monitoring system (e.g., control tower subsystem 214), an inbound operations subsystem, an order fulfillment subsystem, and a transportation subsystem (see also...). Figure 1A Communication. For example... Figure 2B As shown, the warehouse software subsystem includes microservices associated with the mechatronic modules implicit in each module box. As described herein, the warehouse software subsystem receives process optimizations from control tower subsystem 214 based on data 294 collected from various subsystems of warehouse environment 200. Control tower subsystem 214 may be a cloud / on-premises enterprise network configuration or other forms of off-site or hybrid cloud network configuration. The inbound operations subsystem includes receiving / dock door registration 216, serviced by trailer unloading 222 (including container fluid unloading and pallet unloading). Note that receiving / dock door registration 216 provides dock door registration for trucks unloading at their respective dock doors. Unloaded pallets 262 and containers 260 (from trailer unloading 222) are sent to receiving 220, which delivers pallets / containers 262, 260 to cross-docking 224 (including static conveyors and manual forklifts) and then to teaching area 228. Please note that receiving 220 also delivers container 260 to container storage area 218, which provides container storage space within the inbound operations subsystem. As described herein, container storage area 218 also delivers full containers 270 to manual sorting area 230 of the order fulfillment subsystem and target assembly area 254 of the shipping subsystem. Figure 2BAs shown, cross-warehouse 224 bypasses the order fulfillment subsystem and transports pallets 262 (via manual forklifts) and boxes 260 (via static conveyors) directly to truck loading service 256 (including box liquid loading and pallet loading) and target assembly area 254 (respectively) within the transport subsystem. Figure 2B The system also demonstrates how the "teach" area 228 within the order fulfillment subsystem transports the container 260 and pallet 262 to the manual dispensing area 230 and the manual pallet storage area (using a manual forklift) 232, respectively. The container storage area 218 also transports the container 260 to the manual dispensing area 230.

[0039] like Figure 2B As shown, the manual repackaging area 230 also receives mixed SKU tote boxes 266 from the return route management office, which receives mixed SKU tote boxes 266 from return processing and return storage. The return storage in the inbound operations subsystem receives mixed SKU tote boxes 266 from return processing. Return storage provides empty tote boxes 268 to return processing and mixed SKU inventory 264 to receiving 220.

[0040] The manual dispensing area 230 receives boxes 260 from the box storage area 218 and the "teach" area 228, and receives pallets 262 from the manual pallet storage area 232. It then fills turnover boxes 272 (received from storage area 242) as pure or mixed SKU turnover boxes 272 and conveys them to the dispensing storage area 238 (including a static conveyor belt) for final delivery to storage area 242 (including various storage methods, such as DMS). The manual dispensing area 230 receives empty turnover boxes 268, mixed SKU turnover boxes 266, and boxes 260 and pallets 262. Storage area 242 also sends / receives pure SKU 272 turnover boxes and mixed SKU 272 turnover boxes to / from import station 244 (including manual import and robotic import). Import station 244 also returns empty turnover boxes 268 to storage area 242. Import station 244 delivers inventory items (e.g., single items or individual sorted pieces 282) to unit sorter 246 (e.g., Tompkins T-Sort and other sorting systems), which then delivers the single-item sorting results 282 to pre-packaging consolidation 248. Manual pallet storage area 232 delivers pallets 262 to manual sorting area 230, "single-item picking / forwarding" picking face storage area (including trolleys / carts and totes / containers) 234, and the shipper sorter 252 (of the shipping subsystem). Single-item picking / forwarding picking face storage area 234 delivers totes 276 (not sorted by trolleys) to drop wall (non-sortable) 236 and receives empty trolleys / containers 280. Both drop wall (non-sortable) 236 and manual pallet storage area 232 transport inventory to packing area 240. Manual pallet storage area 232 transports non-transferable (non-sortable) inventory 274 to packing area 240, while drop wall (non-sortable) 236 transports individually sorted (single-sorted) items 282 to packing area 240. Manual pallet storage area 232 and drop wall (non-sortable) 236 transport their inventory to manual packing in packing area 240. Automatic packing in packing area 240 receives order turnover boxes 284 from pre-packaging consolidation 248, while automatic packing (in packing area 240) transports empty boxes 268 to pre-packaging consolidation 248. Note that pre-packaging consolidation 248 also transports individually sorted items 282 to manual packing in packing area 240.

[0041] The shipping subsystem includes shipper transportation (static conveyor belt) 250, shipper sorting (cross-belt sorter) 252, destination assembly area (pallet building and Gaylord storage area) 254, and truck loading (box fluid loading and pallet loading) 256. For example... Figure 2BAs shown, shipper transport 250 receives automatically or manually packaged orders 286 from packing area 240 and automatically bagged orders 288 from the automatic bagging machine (at the delivery wall) of pre-packaging consolidation 248. Shipper transport 250 transports packaged orders 290 to shipper sorting station, which then transports them to target assembly area 254. Target assembly area 254 also receives pallets 262 from manual pallet storage area 232 and full cases 270 from case storage area 218. Consolidated packaged orders 292 are transported from target assembly area 254 to truck loading 256. Truck loading 256 also receives cases 260 and pallets 262 (from static conveyor and manual lift truck, respectively) from cross dock. Truck loading 256 receives cases 260 and pallets 262 for container liquid loading and pallet loading, respectively. Truck loading 256 delivers pallets 262 and containers 260 to dispatch (terminal gate registration) 258 for truck loading at the appropriate terminal gate. It should be noted that dispatch terminal 258 includes terminal gate registration for trucks already received at dispatch terminal 258 (via truck loading 256).

[0042] While many existing or traditional warehouse solutions can be categorized as “flexible, scalable, and modular,” these traditional solutions fail to deliver the desired efficiency for day-to-day operations, and also lack the modularity of a fulfillment system—the ability to add new material handling modules / technologies to the fulfillment system temporarily or quarterly to meet growing / changing demands, and to scale down as needed to save costs when demand is low. Exemplary multi-channel fulfillment systems are also configured to dynamically meet changing operational needs by adding or removing physical fulfillment infrastructure modules and modifying operational workflows, without involving technical resources and rewriting process controls, thereby maximizing productivity, throughput, and capacity at low cost. That is, additional fulfillment resources can be added as expected and then removed; or existing surplus fulfillment resources can be temporarily added as needed and then deactivated. The physical placement and removal of fulfillment resources can be used for anticipated large-scale additional fulfillment demands (e.g., during anticipated holiday demand surges), while the activation / deactivation of surplus resources can be used for more frequent (and more unpredictable) short-term increases and decreases. As used herein, “module” is used to describe discrete components of physical infrastructure or processes or functions (e.g., control system 301). In other words, as described herein, while the control system 301 comprises an architecture decomposed into interchangeable and reconfigurable components, the physical infrastructure of the order fulfillment system 300 is also divided into discrete components or modules. For example, multiple configurable workstations 352 can be reconfigured for specific order fulfillment activities (and portions of their control system 301 corresponding to the specific microservices controlling their operation are added to or updated to the control system 301). Therefore, the multi-purpose workstations 352 can adapt the process as needed.

[0043] According to various aspects of the invention, the multi-channel fulfillment system 300 is capable of altering the operating parameters of a given subsystem (e.g., picking station, placement station, repackaging station, etc.) to operate in other ways, such as reconfiguring the operation of a picking station to that of a placement station, including by changing from manual operation to robotic operation. Furthermore, such subsystems may include, for example, reconfigurable workstations that can be selectively configured (and selectively reconfigured as needed) to any of a variety of configurations, such as order fulfillment operations, inventory import, order packaging, etc. Such subsystems may also include storage modules of a modular inventory storage system configured to store inventory items. Such storage modules may incorporate one or more different storage technologies. The configuration of the modular inventory storage system may also include adding and / or removing additional storage modules in the modular storage system based on current and / or anticipated demand (e.g., daily or weekly). Furthermore, the control system is configured to monitor order fulfillment demand in the warehouse and manage the reconfigurable warehouse subsystem to optimize order fulfillment operations, wherein the control system accordingly changes the control of specific subsystems and the configuration of storage modules in the modular storage system by selecting workflows from a workflow library and selectively configuring reconfigurable workstations. The selection of such workflows, the configuration of reconfigurable workstations, and the configuration of storage modules in modular storage systems are all performed by the warehouse control system without the need for additional programming or reprogramming.

[0044] The exemplary multichannel fulfillment system 300 provides warehouse logistics operations, including inbound operations, storage and inventory, order fulfillment operations, and outbound operations, as well as supply chain functions such as global inventory management and distributed order management. The exemplary multichannel fulfillment system and method allow warehouse capacity and capabilities to scale and change flexibly over time to meet fluctuating and seasonal demand. It is characterized by its ability to be adjusted quickly and easily without customization or redesign, thus enabling cost-effective adjustments as operations progress. The exemplary multichannel fulfillment system and method also utilize real-time or near real-time data to intelligently coordinate inventory and order flows in the warehouse / fulfillment center by controlling the automated portions of the warehouse / fulfillment center and providing recommendations (decision support) to warehouse managers and operators regarding current performance and how to configure workflows.

[0045] refer to Figures 2-4An exemplary embodiment of the multi-channel order fulfillment system 300 avoids the traditional "unchanging" characteristics by avoiding strictly defined facility layouts and dynamic control processes. Instead, the exemplary order fulfillment system 300 includes multiple reconfigurable solutions for controlling order fulfillment, comprising reconfigurable infrastructure subsystems and associated control systems with modular architectures. This multi-channel order fulfillment system can scale up / down in a dynamic, adaptive manner over a day / week / month timeframe in real-time (or near real-time). The exemplary multi-channel fulfillment system 300 includes a modular physical architecture in which a centralized sorting system 318 connects one or more general-purpose storage types 404, 406, 408 (regardless of the storage technology and / or techniques used) and associated picking surfaces 314 to manual and robotic multipurpose workstations 352 (each configured to adapt its order fulfillment process and / or operation based on workflow changes) and a transport system using an AMR 354 for transport and buffering. Figure 2A As shown, the exemplary modular order fulfillment system 300 includes a dynamically reconfigurable warehouse controller, control system or coordinator 301, fulfillment control and monitoring system 302, warehouse management system (WMS) 303, warehouse execution system (WES) 304, and supply chain management system 305. The warehouse controller (control system) 301 is communicatively coupled to a memory 306, which stores operational data 294 and a microservice library 304 (i.e., an API library). The memory 306 may contain one or more hardware and / or software components, such as memory modules. In one embodiment, the WMS 303 and the supply chain management system 305 are implemented as independent systems within the warehouse control system 301; alternatively, the WMS 303 may be a sub-component of the supply chain management system 305.

[0046] Exemplary centralized sorting system 318 (see Figure 3 and Figure 4 The sorting system 318 is configured to receive inbound items from other subsystems, such as inventory storage locations, receiving subsystems, and sorting / importing subsystems. The sorting system 318 receives the items and moves them to the correct "next" location. An exemplary sorting machine may be described in commonly assigned U.S. Patent No. 7,086,519, published August 8, 2006, which is incorporated herein by reference in its entirety. As described herein, the exemplary sorting machine 318 may be configured as an extension system of a conveyor belt, or may use an AMR. In one embodiment, the exemplary sorting machine 318 may include a cross-belt sorter, a sorting mezzanine, and a Bombay-style sorter.

[0047] like Figure 2AAs shown, the exemplary control system 301 of the multi-channel order fulfillment system integrates the order fulfillment control and monitoring system 302 with the traditional WMS 303, WES 304, and WCS 305 functions into a single solution. This solution allows for modular, customized deployments tailored to each customer's needs, while fully leveraging standard and evolving warehouse and supply chain functionalities. The exemplary control system 301 utilizes standard warehouse and yard functions that perform all warehouse activities, from receiving, storing, picking, sorting, packing, shipping, and inventory control. These warehouse and yard functions exist as “microservices,” which, as described herein, can be configured into customer-specific configurable workflows designed to meet each customer's needs (see [link to documentation]). Figure 8A and 8B As used herein, a “microservice” refers to a “building block” or component of a software architecture that divides a program or application into multiple components based on the services provided or performed by these individual components (microservices). In other words, a microservice is a component of an application that provides one or more services to the application. Each individual service in the example microservices will be developed and maintained as independent and discrete software. This arrangement allows microservices (and their services) to be viewed as “plug-and-play” components of a larger application or program (e.g., control system 301). When multiple microservices exist (each with its own independent service), these microservices can interconnect and communicate with each other via application programming interfaces (“APIs”). The advantage of a microservices architecture for control system 301 is that additional (or updated) microservices can be easily created and added to control system 301 without rewriting code, thus reducing the time and effort required to implement and adapt these workflows. Just as a traditional WMS allows warehouse tasks to be accomplished in multiple ways (e.g., RF, voice, light, paper), flexible fulfillment allows the use of a variety of fixed and flexible automation technologies and software solutions to be incorporated into the customer’s configurable workflows.

[0048] In one embodiment, an exemplary dynamic control process includes a process solution for controlling a multi-channel order fulfillment system. This dynamic control process is built with a modular architecture comprising a set of microservices selected from a microservice library. The modular architecture of optional microservices can provide maximized productivity, throughput, and capacity within the multi-channel fulfillment system. The dynamic control process includes intelligent coordination or system control that uses end-to-end inventory fulfillment logic to coordinate (or control) inventory and resources to efficiently fulfill customer orders. As described herein, the process for dynamically configurable workflows is built via a user-friendly software interface using drag-and-drop or user-selectable configuration, supporting a real-time configurable dashboard to inform warehouse managers and operators of warehouse status and anomalies, and to provide recommendations on root causes and suggested actions, including suggested workflow configuration changes (see [link to documentation]). Figure 10 The exemplary process for scaling up / down flexible modular infrastructure components is also based on “plug-and-play” infrastructure material handling components (e.g., reconfigurable workstations, multiple inventory storage methods (regardless of their specific storage technology), transportation methods, and automated storage systems). These components are available through a pre-built infrastructure integration catalog and enabled by standardized microservices, such as those found in an exemplary automation marketplace containing API libraries (see [link to documentation]). Figure 10 For example, one or more picking stations can be selectively added or removed, wherein the picking stations can be easily structurally and electronically connected to a control system 301 including a software interface containing a set of selected microservices required to perform the services / functions required by the picking station, the software interface being configured to easily add or remove such picking stations without programming.

[0049] As described herein, the exemplary fulfillment control and monitoring system provides monitoring and machine learning and artificial intelligence capabilities for predictive analytics of the fulfillment process within a multi-channel order fulfillment system, such as changes in operational performance, order or item demand, and potential automated system maintenance issues. Therefore, a customer's entire supply chain can be managed by managing global inventory across their entire distribution network, including managing inventory positioning based on predicted customer demand, and managing global customer orders and distributing them to appropriate fulfillment centers to ensure customer commitments are met. The fulfillment system can autonomously update configuration changes, adjust business rules, and adjust resource allocation within fulfillment centers or throughout the supply chain based on evolving business conditions.

[0050] An exemplary multi-channel fulfillment system 300 with a flexible architecture decouples the fulfillment workflow (executed by the warehouse control system 301) from the technology and can dynamically change how orders are fulfilled in real time or near real time based on customer needs and resource utilization (via intelligent coordination of the warehouse control system 301), thereby flexibly adjusting capabilities over time (flexible module expansion / reduction).

[0051] refer to Figure 2A , Figure 3 and Figure 4 An exemplary multi-channel fulfillment system 300 includes: a flexible fulfillment physical architecture; a control system 301 configured to control execution within the multi-channel fulfillment center 300 and throughout the supply chain; processes for intelligent coordination (located in the warehouse control system 301); processes for dynamically configurable workflows; and processes for flexible modular expansion / reduction via autonomous marketplaces of modular subsystems (physical inventory handling and storage subsystems and logical subsystems). Exemplary autonomous marketplaces include one or more of the following: subsystems and configurations for material handling, sorting, inventory storage, transportation, and reconfigurable workstations.

[0052] Flexible physical architecture for implementation:

[0053] like Figure 2A , Figure 3 and Figure 4 As shown, an exemplary flexible physical architecture for order fulfillment in a warehouse environment includes: 1) a storage system 312 (having one or more general storage types) and an associated picking surface 314; 2) a cell sorting system 318; 3) a multi-purpose workstation 352 capable of adapting to different processes (e.g., sorting / importing operations, order fulfillment operations, and packing operations; and configurations for human or robotic workers); and 4) an AMR 354 for transporting and buffering between the storage type 312 / picking surface 314 and the multi-purpose workstation 352.

[0054] The multi-channel order fulfillment system 300 can be configured to accommodate and “activate” varying numbers of reconfigurable workstations 352 as needed to meet the throughput requirements of a warehouse facility. For example, multiple reconfigurable workstations 352 can be configured for any type of operation or service; for instance, a variable number of available workstations 352a-c can be configured for import / packaging operations, while another variable number of available reconfigurable workstations 352 can be configured for packing operations. It will be understood that because the reconfigurable nature of the workstations 352 allows them to operate in any available configuration, various parts of the order fulfillment system 300 (e.g., containing reconfigurable workstations 352) can operate differently at different times of the day as needed. Workstations 352 can be reconfigured immediately after all previous functions have been completed. For added flexibility, reconfigurable workstations 352 are configured for both human and / or robotic activities. The control system 301 of the multi-channel fulfillment facility synchronizes various order fulfillment functions and processes, including sorting various sizes of transport containers or picking totes (in picking or packing functions) or various sizes of supplier boxes or item containers (in dispensing / import functions) with inventory / donation containers (e.g., from an automated storage and retrieval system from storage system 312) at goods-to-person (GTP) or goods-to-robot (GTR) workstations to maximize operational productivity and facility throughput (see [link to relevant documentation]). Figure 5 ).

[0055] The multi-channel order fulfillment system 300 incorporates multiple different inventory storage technologies and operations as multiple parts of an overall storage system 312 (e.g., storage subsystem A 404, storage subsystem B 406, and storage subsystem C 408, each employing a different inventory storage technology). A generic or modular architecture allows storage systems 312 with different units of measurement (between different storage subsystems) to be interchangeable and reconfigurable. In one embodiment, an exemplary storage system 312 is configured as a modular storage system, for example, including a pair of storage systems 402a and 402b, each containing a set of storage subsystems 404a, 406a, and 408a; and 404b, 406b, and 408b. Storage system 312 includes automated and manual storage options that can be added or removed, either in individual storage units or as additional shelving within storage units (e.g., non-sortable inventory warehouses 418a and 418b). Storage components can be added to / removed from storage system 312, or storage modules can be added to / removed from storage system 312. For example, the storage type and picking surface 314 (of storage system 312) can be a dense storage automated storage and retrieval system (AS / RS), a high-speed storage type (AMR S2P (“shelf-to-person”) / B2P (“box-to-person”)), or static shelving / manual picking (considered “low-speed”, reserved, and “non-movable”). Storage picking station 314 can be goods-to-person or goods-to-robot and can handle the introduction of bulk picking and sorting systems. In one embodiment, storage system 312 includes an AS / RS storage system in which a portion of the storage capacity can be “disabled” or shut down when the storage capacity exceeds the required space. Alternatively, the AS / RS storage system may include storage modules that can be coupled to the entire AS / RS storage system as needed (and decoupled when not needed (and optionally removed)). Note that unused portions of the AS / RS storage system or unused storage modules will be idle, set to have minimal or no power requirements and minimal to no maintenance requirements to reduce operating overhead and costs. Note that the multichannel order fulfillment facility 300 includes a storage system 312, whose picking surface 314 is a portion of the storage system 312 that is readily accessible to order pickers (e.g., human pickers 202 and / or robotic pickers 204). Therefore, when items are moved from the picking surface, the storage system 312 will need to replenish the storage space of the picking surface 314 from other storage locations within the system 312. The transfer of items can be achieved via AMR. This can be accomplished using 354 or other automated methods. It's important to note that additional inventory storage modules can be added as needed and then removed, or activated when needed and then deactivated. The physical placement and removal of storage modules can be used for anticipated large-scale additional inventory storage needs (e.g., during anticipated holiday shopping peaks), while the activation / deactivation of storage modules can be used for short-term increases and decreases in demand.

[0056] Figure 2A , Figure 2B , Figure 3 and Figure 4 The unit sorting system 318 shown allows any unit picked from any picking medium to be transported to any packing station for consolidation and / or packing. The unit sorting system 318 can be implemented as a centralized, decentralized, or distributed system. The unit sorting system 318 can be automated using an AMR solution and can sort to discrete multi-line orders or multiple single-line order consolidation points. Circulating, cross-belt, linear, or Bombay sorters are commonly used for unit sorting. While the exemplary AMR-based unit sorting system is an exemplary embodiment, alternative embodiments may include cross-belt or Bombay sorting (supplementary or alternative to AMR). Figure 3 and Figure 4 An overview of sorting, for example, using AS / RS storage, is shown. In one such arrangement, the optimal layout may employ the Dematic Multi-Shuttle System (“DMS”) and the unique capabilities of the DMS to “pre-sort” donation boxes onto the DMS elevator. This system can be configured according to U.S. Patent No. 9,555,967, which is incorporated herein by reference in its entirety.

[0057] refer to Figure 5 An exemplary AS / RS storage module 502 is associated with a material conveying device 504 to move donation boxes into and out of the AS / RS storage module 502. It should be noted that, although... Figure 5 The conveying device 504 shown utilizes conveyors and other similar devices for inventory movement, but AMR sorting modules (e.g., unit sorting (AMR) system 318) may also be used.

[0058] Transport and buffering are performed using an exemplary AMR through a flexible, modular order fulfillment system 300 (see [link]). Figure 3 (AMR 354 in the example). AMR 354 is used for automated and flexible transport throughout the order fulfillment system 300. This allows for a more even distribution of workflows among packing stations (and reconfigurable workstations 352) and helps maximize throughput. AMR allows physical workflows to be changed quickly without requiring infrastructure alterations. This enables the exemplary modular order fulfillment system 300 to be rapidly scaled up or down (in terms of physical infrastructure). Compared to traditional transport or sorting methods, this arrangement achieves greater sustainability by reducing energy consumption.

[0059] Example packing buffer 416 (see Figure 4This approach decouples the packing station and supports consolidated order sorting. When the import station is configured as a workstation to place products onto the sorting station, the packing station configuration is very simple (e.g., a simple sorting workstation). Packing destinations are not limited by conveyors and predetermined paths, allowing for the redirection of "pending packing" orders to balance workflows. Furthermore, compared to solutions based on fixed conveyors, high-priority orders can bypass low-priority orders, prioritizing packing capacity and improving on-time delivery rates.

[0060] Example workstation procedure:

[0061] refer to Figure 6A and Figure 6B This illustrates an exemplary process of a Goods-to-Person (GTP) / Import workstation 352. The exemplary multi-purpose workstation 352 is configured to adapt the process based on workflow changes (e.g., import, picking, packing, etc.). Manual and robotic / automated packing stations can be interchanged between fixed automation / mobile / manual. As described herein, the exemplary packing station allows both workers and robots to operate. The automated packing module allows operations to be fully automated over time without significant infrastructure changes. In one embodiment, the exemplary packing module is not physically connected to sorting or consolidation, allowing for the addition of other modules to increase order processing capacity. Furthermore, since any unit can reach any packing station from any picking location, higher batch rates can be achieved during the picking process, thereby improving operational efficiency.

[0062] The operation of the exemplary Goods-to-Person (GTP) / Import workstation 352 begins at step 602. In step 604, inventory arrives at the Import / (GTP) workstation 352. In step 606, it is determined whether the AMR configured for picking is ready for import (part of the cell sorting system 318). If the picking AMR is not yet ready for import, the process continues to step 608, where the user (or robotic arm) waits until the AMR is available. When the picking AMR is ready for import, the process continues to step 610, where the user (or robotic arm) picks the inventory items from the retrieved bins. Optionally, the process includes step 612, where the inventory items are scanned and picking verification controls are performed. The process proceeds to step 614, where the user or robotic arm places the inventory items onto the picking AMR. If step 612 has been performed, the process proceeds to step 626 after step 614. If step 612 has not been performed, the inventory is scanned in step 616. In step 618, an interface is sent from the fulfillment activity controller (e.g., warehouse control system 301) to the sorting control layer (of the unit sorting system 318). In step 620, picking verification is performed. In step 622, it is determined whether picking is complete. If picking is not complete, the process flow returns to step 620 and picking verification is performed again. If picking is complete, the process proceeds to step 624, where it is determined whether a redirection opportunity is available. If not, the process proceeds to step 628. If a redirection opportunity exists, the process proceeds to step 626, where target order tote bag allocation is performed. In step 630, it is determined whether bin allocation is complete. If bin allocation is not complete, the process returns to step 626, where target order tote bag allocation continues, and then returns to step 630 for further processing. If bin allocation is completed in step 630, the process proceeds to step 628, where the AMR executes the route to the target order tote bag. After step 628, the process proceeds to... Figure 6B Step 632. In step 632, the AMR arrives at the target order tote. In step 634, the AMR stores the inventory items into the target order tote. In step 636, the database is updated for inventory location and order status. In step 638, it is determined whether the order tote is full. If the order tote is full, the process continues to step 640, where an interface is sent from the sorting control layer (of the unit sorting system 318) for tote picking. If the order tote is incomplete (in step 638), the process ends in step 642.

[0063] refer to Figure 7The diagram illustrates the steps of an exemplary picking verification process. In step 702, the picking verification process begins. In step 704, exemplary picking verification is performed. In step 706, inventory barcodes are verified against the database. In step 708, it is determined whether the scan was successful. If the scan fails, the process continues to step 708, and the scan error and its cause are displayed to the user at the import station. In step 710, the AMR remains stationary until the scan problem is resolved. In step 712, it is determined whether the problem has been resolved. If the problem has not been resolved, the process returns to step 710, and the AMR remains stationary until the scan problem is resolved. In step 712, once the problem is resolved, the process continues to step 708, and the process again determines whether the scan was successful. If the scan is successful, the process continues to step 714, where the picking is completed by the fulfillment system 300. In step 716, the database is updated for the order status, and in step 718, the process ends.

[0064] refer to Figure 9 An exemplary method for reallocating picked inventory (“pick stealing”) includes the following steps: In step 902, a new order is issued. In step 904, the priority of the newly issued order is compared with any previously issued orders. In step 906, it is determined whether there is inventory / items at a pickable location for the newly issued order. If the inventory / items for the newly issued order are at a pickable location, the method proceeds to step 908. If there is unavailable inventory / items (i.e., not at a pickable location for the newly issued order), the method continues to step 910. In step 908, it is determined whether the allocated inventory / items can be picked and satisfy the customer's Service Level Agreement (“SLA”) for the newly issued order. If the allocated inventory / items can be picked and satisfy the customer's SLA for the newly issued order, the method continues to step 912 and ends. If one or more allocated inventory / items cannot be picked and cannot satisfy the customer's SLA for the newly issued order, the method proceeds to step 910. In step 910, it is determined whether reallocating inventory / items from any previously lower priority orders will satisfy the customer's SLA for the newly released order. If reallocating inventory / items from previously lower priority orders cannot satisfy the customer's SLA for the newly released order, the method ends at step 912. If reallocating inventory / items from previously lower priority orders can satisfy the customer's SLA for the newly released order, the method proceeds to step 914.

[0065] In step 914, one or more inventory / items allocated to a previously lower-priority order are reassigned to the newly issued order. In one embodiment, if other inventory / items are available to fulfill the lower-priority order, only the inventory / items are reassigned. In step 916, additional inventory / items are allocated to replace one or more reassigned inventory / items to satisfy the customer SLA for the previously lower-priority order. The method ends at step 912.

[0066] Intelligent coordination:

[0067] An exemplary control system 301 for a multi-channel order fulfillment system 300 includes end-to-end inventory fulfillment logic (implemented in software) based on the intelligent coordination of inventory and resources to fulfill customer orders. This exemplary fulfillment control logic can be configured as a “facility coordinator” (i.e., warehouse control system 301) responsible for managing the overall flow of product and task execution throughout the order fulfillment system 300. The coordinator’s primary function is to ensure workflow consistency throughout the order fulfillment system 300, avoiding bottlenecks (excessive inventory for available processing / handling resources) and resource scarcity (insufficient inventory leading to idle processing / handling resources). Coordinator 301 determines which tasks need to be completed, when they need to be performed, and who (person) or what (machine) will perform those tasks. The warehouse (task) coordinator 301 is responsible for prioritizing, optimizing, and coordinating work between workers and automated systems to ensure consistent workflow throughout the warehouse and to ensure the right work is done at the right time, thereby fulfilling customer commitments. Coordinator 301 automatically adjusts the task execution flow based on various factors, including order commitment time, inventory constraints, labor constraints and performance, and equipment performance. Coordinator 301 continuously assesses which tasks need to be performed—when, by whom (workers), or by what (machines)—to avoid bottlenecks and resource shortages, and to ensure that customer-committed timelines are met. The system maintains control over all fulfillable inventory from receipt to shipment. The system is capable of real-time routing of inventory for replenishment and fulfillment.

[0068] The functions performed by the coordinator 301 include resource management and order management. In performing resource management, the coordinator 301 monitors the performance and utilization of resources (operators, mobile devices, and robots) and redirects resources as needed to avoid task bottlenecks or resource shortages. Order management involves prioritizing order releases based on factors such as order fulfillment time, inventory constraints, and labor / machine capacity limitations to meet customer service level agreements (“SLAs”). The coordinator 301 can partition orders into different order fulfillment subsystems as needed, based on inventory location and performance factors. The coordinator 301 then ensures that these partial orders are correctly consolidated before shipment.

[0069] When performing order management, coordinator 301 is also capable of performing intelligent release sorting (units fulfilled from different storage subsystems (e.g., subsystems 404, 406, and 408) arrive at the consolidation point simultaneously to avoid prolonged dwell time). The release of individual units is based on factors such as distance and picking rate. The unit destination is initially determined at the time of unit release and, for multi-line orders, can be reassigned upon import into the sorting system (sorting system 318). Single-line orders can be reassigned to downstream packing stations. Coordinator 301 also performs intelligent flow adjustment, such as configurable order release and dynamic rerouting after picking. This flow adjustment is designed to enable waveless operations with multiple deadlines, and the fulfillment system can reassign order unit destinations between the picking and packing processes. For example, if 5:00 PM (17:00) is the deadline for priority orders, and it is currently 9:00 PM (21:00), coordinator 301 can flexibly and immediately release all 17:00 orders to serve more priority orders.

[0070] Coordinator 301 includes an integration process capable of integrating items into discrete orders (i.e., discrete order chutes), batch orders (i.e., multi-order chutes), single-item orders (i.e., multiple single-line orders in one chute), plastic bags, and single-item orders. Each integration point (i.e., chute) can be configured to any integration state and can be changed during operation.

[0071] Coordinator 301 also includes picking transfer (redistribution) functionality (see [link]). Figure 9 When a high-priority order is issued, the order fulfillment system 300 may be able to "transfer" products / items already picked for other orders and reassign them to the highest priority order. This may occur if a "transfer" of picking is required to meet a customer's SLA for a high-priority order, or if there is no stock available at a picking location for the high-priority order. After a picking transfer occurs, the system allocates additional stock to meet the low-priority order. This behavior should be configured by the customer. The customer should be able to configure whether picking transfers are allowed, at what stage of the fulfillment process order transfers are allowed, and whether picking transfers are allowed when no additional stock is available to fulfill a low-priority order.

[0072] Coordinator 301 manages inventory movement. Coordinator 301 manages inventory flow within order fulfillment system 300 and manages the movement of inventory to different areas of the warehouse / fulfillment facility as needed. For example, coordinator 301 determines and initiates replenishment to the order fulfillment subsystem as needed to ensure proper inventory balance. This type of inventory management is based on predicting customer behavior and handling SKU surges. It uses historical and current information to guide inventory receipt and replenishment. This type of inventory movement also includes transportation management, where coordinator 301 issues instructions to fixed and flexible automated systems to move goods.

[0073] Finally, the warehouse task / control coordinator 301 utilizes control and monitoring functions (via the order fulfillment control and monitoring system 302) to monitor operations from the warehouse to the entire enterprise, providing operational performance insights, alerting to process anomalies, and identifying performance degradation due to changes in labor, equipment, order profiles, etc. Advanced data integration and guided workflow resolution capabilities enable the system to identify the root causes of problems and provide suggestions on how to resolve issues and anomalies. The system can be configured to autonomously adjust its configuration or allow for manual configuration changes. Furthermore, the AI / ML capabilities of the control / monitoring system (regarding control system visibility / monitoring) are used to provide predictive analytics to anticipate future changes in the customer's distribution network and environment (e.g., increased demand for specific SKUs due to weather, supply chain issues, shipping delays, etc.).

[0074] Dynamic and configurable workflows and microservices:

[0075] Controlling order fulfillment within an exemplary multi-channel order fulfillment system 300 and its associated supply chain includes a control system 301 (a software solution for controlling execution within a flexible fulfillment center and throughout the supply chain), built on a modular architecture based on microservices. The control system 301, using microservices, is configured to control the order fulfillment system 300 and guide workers within the warehouse facility. The exemplary control system 301 intelligently coordinates inventory and order flow within the warehouse / fulfillment facility by using real-time or near real-time data and providing advice (decision support) to warehouse managers and operators on current performance and how to configure workflows to maximize productivity, throughput, and capacity by controlling the automated portions of the warehouse / fulfillment facility. The control system 301 allows order demands to be met in a timely manner based on the inventory received at the facility. This cross-terminal capability enables the most efficient order fulfillment, completely bypassing storage.

[0076] The exemplary modular order fulfillment system 300 supports non-linear processes and decisions; that is, for each location where an inventory unit is scanned or identified, the system should select the next optimal location (sending the unit to the warehouse or fulfillment center) in a timely manner. Continuous optimization calculations using real-time data optimize the entire solution's processes. This flexibility improves upstream picking efficiency by combining single-item and multi-item picking tasks; makes packing station workflows more flexible to reduce capacity losses due to insufficient inventory; eliminates reliance on single-item picking; and allows operations to adapt to rapid changes in order status (i.e., the percentage of backlog orders represented by single items) without requiring labor relocation.

[0077] A microservice consists of one or more code functions or services that can run as independent services and can be easily coupled with other microservices to build specific solutions (via APIs coupled with the microservices). Microservices contain code that performs specific functions and / or services (e.g., picking, receiving, etc.), controls user interface screens, handles integration with other systems and solutions, and handles background functions (e.g., message processing, alerts, etc.).

[0078] Multiple microservice instances can be created and run simultaneously to ensure optimal system performance. For example, a single microservice instance can be used to handle activities at Goods-to-Person (GTP) workstation 352. During peak periods, an additional GTP workstation 352 might come online, increasing the workload. In response to the additional GTP workstation 352, the system can create additional instances of the GTP workstation microservice. When workload decreases, the additional microservice is removed. Furthermore, when no GTP processing is occurring, all instances of the GTP workstation microservice can be removed to ensure the system operates as leanly as possible, thereby maximizing system performance. When creating multiple microservice instances, task prioritization is also important. For example, using multiple microservice instances to handle messages from a conveyor belt could lead to disordered message processing.

[0079] Using microservices to develop a control architecture allows complex control systems (such as warehouse control system 301) to be broken down into smaller, simpler, and more manageable parts. Building control system 301 in this way offers the following advantages:

[0080] • Decouple functionality into appropriate subsystems / control modules to avoid a single approach.

[0081] • Improve patching and upgrade capabilities by decoupling functionality and using defined APIs between subsystems / modules, allowing for independent deployment without affecting overall system functionality.

[0082] • Supports improved functional testing.

[0083] • It accelerated the development speed.

[0084] • Microservices help improve the resilience and survivability of a system by increasing the number of instances when demand increases and decreasing the number of instances when no longer needed.

[0085] An exemplary control system 301 for a multi-channel order fulfillment system 300 includes a front-end interface for workflow configuration. The control system 301 receives real-time and historical data (from the order fulfillment control and monitoring system 302) and provides recommendations for continuous optimization. The interface is configured to inform warehouse managers and operators of situations and provide action suggestions, and to flexibly reconfigure warehouse workflows. Embodiments of the multi-channel order fulfillment system 300 allow for fully configurable system workflows. For example, a particular order fulfillment system 300 can customize all system workflows by connecting different tasks to meet the operational needs of a warehouse facility. The exemplary control system 301 provides default configurations for different workflows and workflow activities.

[0086] Control system 301 uses workflows to define how human operators and machines complete warehouse tasks, and also to determine how products / inventory items should flow through the warehouse / fulfillment facility. Workflow configuration can be done using a no-code / low-code workflow editor (see this document). This workflow configuration approach allows a specific multi-channel order fulfillment system 300 to have custom workflows that meet its needs but are built using standard functionalities. Because configuration can be completed without writing code, this approach also reduces the time, effort, and cost required to implement and adapt the multi-channel order fulfillment system 300.

[0087] In addition to configuring different workflows, the tasks that make up the workflows also contain configurations that allow individual customers to precisely customize how tasks behave (within their warehouses / fulfillment centers). These configurations can be executed without writing code. Examples of task configurations include, for example: item storage rules, inventory selection rules when allocating orders, information required by users during picking, whether products can be over-accepted (based on POs), and the movement path of products within the warehouse during order fulfillment. All configuration changes are logged by the order fulfillment system 300, indicating when parameters were changed to trace changes that may affect system performance. Users who execute changes are also logged, where permitted by customer and local / regional laws. In one embodiment, the control system 301 is "cloud-based" and provides instructions and information. For example, it can determine where to send workers, predict capacity based on current information (in the warehouse / fulfillment center), issue operational risk alerts, and propose action recommendations.

[0088] A workflow consists of a series of tasks (or steps) required to complete the workflow, in which data is updated and transferred. Tasks can be designed to be performed by a specific type of machine or by a human. Tasks contain code that executes when the task is performed. This code consists of a single microservice or a set of microservices designed to work together. For example, in an order identification task, an Order_ID is input to allocate inventory. In response, the corresponding output includes, for example: a list of inventory reservations for that order (location, SKU, reservation quantity); the original order is modified, where the order line is expanded to include the location to be picked; and the return status (i.e., success or failure). The task / step logic includes the steps to be performed based on the microservice task (e.g., for the Order_ID task, for each order line, look up available inventory for that order line; update the order line with the location where the inventory was found; and create an inventory reservation for that specific order). Figure 8A An example of task 802, which allocates inventory for an order, is shown. Task 802 contains two microservices, 804 and 806. Both microservices 804 and 806 call two code functions. For example, inventory microservice 804 calls the example operations [Inv_Info Get_Available_Inventory_for_SKU(SKU)] and [Inv_Res Create_Inventory_Reservation(Loc,sku,qty,order)], while inventory microservice 806 calls the example operations [Order_Get_Order_by_ID(Order_ID)] and [Void Update_Order_Line(OrderLineline)]. Each time this task is executed, these two microservices 804 and 806 (and their operations) will be executed. Figure 8A As shown, when control system 301 receives an order ID, the first task or step logic of the example workflow outputs a list of inventory reservations (location, SKU, and reservation quantity) for that order, modifies the original order to expand the row containing the pick locations from which, and returns a status (success / failure). The second task or step of the workflow involves finding the available inventory for each SKU in each order row, updating the order row with the found inventory locations, and creating an inventory reservation for that specific order. Figure 8AAs shown, when inventory allocation task 802 is invoked via order ID input, a pair of microservices 804 and 806 (i.e., inventory microservice 804 and order microservice 806) are invoked to execute the workflow. As described above, each microservice 804 and 806 contains a pair of code functions. The operations of inventory microservice 804 include calling functions to retrieve information about the order's location, SKU, quantity, etc., and to reserve inventory items for the order. Furthermore, the operations of order microservice 806 include calling functions to invoke a specific order based on its order ID and update the order line of the invoked order (including finding the location of the inventory). As described herein (and as...). Figure 2A As shown, the microservices 804 and 806 used to execute the workflow are selected from the available microservice library 304 (e.g., an available API library that can be used to build the required functions).

[0089] like Figure 8B As shown, microservices can be grouped together in a "wrapper microservice" 858. Task 802 can execute these wrapper microservices 858, and during execution, the wrapper microservice 858 will execute its sub-microservices 854, 856. This approach (wrapper microservices) allows common functionalities composed of multiple microservices to be easily inserted into tasks without recreating the functionality each time, and allows for simplified updates to microservices, as sub-microservices (in the microservice library 304) can be updated, thereby updating all related wrapper microservices.

[0090] Figure 8B The packaging microservice 858 and Figure 8A Similar to task 802, this example contains task 802, which allocates inventory to an order by calling wrapper microservice 858. (See above regarding...) Figure 8A In the discussion of the example order identification task, an Order_ID is input to allocate inventory. In response, the corresponding output includes, for example: a list of inventory reservations for the order (location, SKU, reservation quantity); the original order being modified, where the order line is expanded with the location to be picked; and the return status (i.e., success or failure). The task / step logic includes those steps performed according to the microservice task (e.g., for the Order_ID task, for each order line, look up available inventory for that order line; update the order line with the location where the inventory was found; and create an inventory reservation for that specific order). Similarly, the task / step logic contains function calls for the steps to be completed (calling inventory; allocating microservice functions to perform the task / step). This task 802 consists of a wrapper microservice 858 (inventory allocation microservice) that calls a pair of sub-microservices (inventory sub-microservice 854 and order sub-microservice 856). Figure 8ASimilar to the illustration, each of the two sub-microservices 854 and 856 calls a pair of code functions. For example, the inventory microservice 854 calls the example operations [Inv_Info Get_Available_Inventory_for_SKU(SKU)] and [Inv_Res Create_Inventory_Reservation(Loc,sku,qty,order)], while the inventory microservice 856 calls the example operations [Order_Get_Order_by_ID(Order_ID)] and [Void Update_Order_Line(OrderLineline)]. The inventory sub-microservice 854 includes call functions for retrieving the inventory (by SKU) for an order and creating an inventory reservation (location, SKU, and quantity reserved for the order). Furthermore, the order sub-microservice 856 includes call functions for calling a specific order based on its order ID and updating the order line of the called order (using the location where the inventory was found). As described above, sub-microservices 854 and 856 can be selected from the available sub-microservice library 304.

[0091] Flexible modular expansion / reduction (via the self-market):

[0092] The exemplary multi-channel order fulfillment system 300 flexibly expands and shrinks using "plug-and-play" modules that provide additional storage, configurable workstations, AMRs, and single-point solutions for additional workflows. Therefore, additional capacity can be added with minimal or even no infrastructure changes. To meet the needs of customers who may wish to integrate a wide range of potential automation solutions into their fulfillment operations, an exemplary embodiment provides an "autonomous marketplace" containing integrations of numerous pre-built autonomous solutions, including hardware and software solutions, that can be enabled and added to configurable workflows. Such pre-built integrations can be implemented as "plug-and-play" modules.

[0093] These pre-built integrations (plug-and-play modules) can exist in many types of automation and software systems (see...). Figure 3 and Figure 4 ), including but not limited to:

[0094] • Modular storage – Automatic or manual storage options that can be added or removed over time (complete system or additional shelves).

[0095] • AMR / AGVs used for transportation and buffering.

[0096] • Picking workstations (robotic and manual), which can be used alone or in combination with sorting inbound stations.

[0097] • Packaging workstations (robotic and manual), including automated packaging equipment.

[0098] • Parcel shipping solutions.

[0099] • Automation islands, including interchangeability between stationary automation / mobile / human automation.

[0100] Flexibility is achieved through standardized subsystem microservices, enabling scalability and interchangeability—any subsystem can be easily and repeatedly integrated into the solution without custom integration (avoiding dependencies and reprogramming). This flexibility is further enhanced by providing a marketplace of pre-built integrations for various automation and software solutions. Since any flexible fulfillment facility needs to add a new automation solution each time without writing code, the workload, time, and cost of implementation are significantly reduced. This approach also ensures standardized interfaces for all customers' fulfillment facilities, simplifying ongoing maintenance of integrations and reducing overall support workload.

[0101] See Figure 10 An exemplary modular infrastructure selection and task panel 1070 is illustrated. In one embodiment, panel 1070 serves as a selection and task assignment panel, accessible to an operator or administrator to select infrastructure components and their functional task / service selections (as needed for order fulfillment). In another embodiment, panel 1070 serves as a selection and task monitoring / instruction panel, illustrating the control system's dynamic selection and reconfiguration of the infrastructure components required for order fulfillment based on current warehouse order fulfillment activity (provided by the order fulfillment control and monitoring system 302). That is, the selection of configuration (or reconfiguration) of individual workstations, storage modules of the modular storage system, and / or the selection of current or anticipated warehouse operations from a workflow library can be performed through user interaction with the selection and task assignment panel 1070, or can be dynamically executed by the control system 301 (panel 1070 serves as a selection and task monitoring / instruction panel).

[0102] Figure 10 The allocation, configuration, and status of the warehouse subsystem are shown, including storage modules of storage system 312, AMR 354, and workstation 352. Figure 10As shown, the status of a group of storage modules 312 is indicated by the graphical button arrays 1012a-g. Storage modules 312 indicated by graphical buttons 1012a-c are depicted as currently allocated and storing inventory. Storage modules 312 indicated by graphical button 1012d are depicted as currently selected for allocation, while storage modules 312 indicated by graphical buttons 1012e-g are depicted as deactivated. When graphical button 1012d is selected for allocation (corresponding to the allocation of storage module 312), graphical button 1076 is also selected to provide an indication of the type of storage module being allocated (e.g., components of an ASRS storage system).

[0103] Figure 10 Graphical buttons 1054a-g depict AMRs 354 assigned to transport and / or sorting tasks (and other assignments). Graphical buttons 1054h-i depict AMRs 354 selected for assignment and task allocation, while graphic buttons 1054j-l depict AMRs 354 currently deactivated and awaiting assignment. When graphic button 1054h-i is selected for assignment (assignment of the corresponding AMR 354), graphic button 1072 is also selected to provide an indication of the type of service and / or function configured to be performed by the assigned AMR 354. Graphical button 1072 can also be used to select or indicate the type of AMR in question.

[0104] Similarly, Figure 10 Graphical buttons 1052a-c depict configurable workstations 352 assigned to order fulfillment tasks. Graphical button 1072 indicates the type of functional task / service performed (or to be performed) by the assigned AMR 354, while graphical button 1074 indicates the type of functional task / service the assigned workstation is configured to perform (or to be configured to perform). Graphical buttons 1052d-e depict configurable workstations 352 selected for assignment and task allocation, while graphical buttons 1052f-g depict configurable workstations 352 currently deactivated and awaiting assignment. When graphical buttons 1052d-e are selected for allocation (the corresponding allocation of configurable workstation 352), graphical button 1074 is also selected to provide an indication of the type of service and / or function the assigned configurable workstation 352 is configured to perform. Graphical button 1074 can also be used to select or indicate the type of AMR discussed.

[0105] In addition to the AMR task selection panel 1072, the workstation function task / service selection panel 1074, and the storage module allocation panel 1076, an additional panel 1078 is used to indicate or select other order fulfillment services that the infrastructure components are performing.

[0106] In one embodiment, the infrastructure components (312, 354, 352) indicated as deactivated and awaiting allocation are currently located in the local warehouse facility, awaiting allocation and configuration. In another embodiment, additional graphical buttons may be used to indicate that storage module 312, AMR 354, and / or configurable workstation 352 have been ordered and are expected to be delivered to the warehouse environment and activated when appropriate. Panel 1078 may also be used to indicate the delivery timeframe for the requested infrastructure components.

[0107] Therefore, the exemplary multi-channel order fulfillment system 300 is scalable to meet fluctuating and seasonal demand and handle order volumes from average to peak. Its flexibility allows it to adapt over time and adjust quickly and efficiently as fulfillment business grows or business needs change. With modular components and an adaptive control system (facility coordinator) 301, the exemplary order fulfillment system 300 can be flexibly managed and monitored (e.g., providing real-time data to inform operators and administrators of current performance). Thus, the multi-channel order fulfillment system 300 can be quickly and easily adapted without customization or redesign. Easy integration of flexible automation allows for rapid scaling (up or down). Fully automated modules can be used to (gradually) replace human operators to reduce reliance on labor. The resulting multi-channel order fulfillment system 300 is not dependent on specific units of measurement or workflows and allows for non-linear workflows. The flexibility of the exemplary fulfillment facility meets evolving operational needs, thereby maximizing productivity, throughput, and capacity at low cost. Workflows can be adjusted to address dynamic operational needs and requirements as they occur. Dynamic reordering of units can also accommodate changing order backlog priorities. Customers (fulfillment facilities) can use microservices (such as APIs) selected by customers from an available library of microservices to build and modify operational workflows without involving technical resources or writing code to change (their workflows).

[0108] Changes and modifications may be made to the specific embodiments described without departing from the principles of the invention. The invention is limited only by the scope of the appended claims and is interpreted in accordance with the principles of patent law, including the doctrine of equivalents.

Claims

1. An order fulfillment system for a warehouse, the order fulfillment system comprising: A control system is configured to control the fulfillment activities in the warehouse and record operational data corresponding to the fulfillment activities in the warehouse; A memory configured to store the operational data and workflow library; Modular inventory storage system, configured to store inventory items, and The workstation can be reconfigured to operate in one of several operating configurations. The control system is operable to select an operating configuration for each of the reconfigurable workstations; The control system includes multiple workflows selected from the workflow library, each workflow defining how the control system controls the fulfillment activities in the warehouse; and The selected workflow, the selected operation configuration for the reconfigurable workstation, and the configuration of the modular inventory storage system correspond to the current state of the warehouse defined by the selected portion of the operation data.

2. The order fulfillment system of claim 1 further includes a sorting system comprising a plurality of autonomous mobile robots (AMRs), each AMR configured to move inventory items from one location to a desired next location.

3. The order fulfillment system according to claim 2, wherein, The sorting system is a unit sorting system.

4. The order fulfillment system according to any one of claims 1 to 3, wherein, The modular inventory storage system includes one or more different storage technologies.

5. The order fulfillment system according to claim 4, wherein, The configuration of the modular inventory storage system includes adding / removing additional storage modules to the modular inventory storage system according to current and / or anticipated needs.

6. The order fulfillment system according to claim 4, wherein, The configuration of the modular inventory storage system includes adding / removing additional storage capacity to the modules of the modular inventory storage system according to current and / or anticipated needs.

7. The order fulfillment system according to any one of claims 1 to 3, wherein, The workflow involves one or more function calls, each of which selects a microservice from the microservice library.

8. The order fulfillment system according to claim 7, wherein, The microservices include wrapper microservices, and each wrapper microservice includes sub-microservices selected from a library of sub-microservices.

9. The order fulfillment system according to claim 1, wherein, The reconfigurable workstation is configured for use by humans and / or robots.

10. The order fulfillment system according to any one of claims 1 to 3, wherein, The control system is operable to determine or identify the priority of newly received orders; and wherein if a newly received order has a higher priority than a previously received order, the control system is also operable to determine whether to reallocate inventory allocated to one or more previously received orders to the newly received order if a service level agreement (SLA) for the newly received order needs to be satisfied.

11. The order fulfillment system according to any one of claims 1, 2, 3 or 9, wherein, The operational configurations for the reconfigurable workstation include order fulfillment, inventory import, or order packaging.

12. A method for controlling order fulfillment activities in a warehouse, the method comprising: Control the fulfillment activities in the warehouse; Select a specific operating configuration for each of the multiple reconfigurable workstations from multiple configurations; Controlling and configuring modular inventory storage systems; Record operational data corresponding to the fulfillment activities in the warehouse, wherein the operational data is stored in a memory; The configuration of the control and storage system for fulfillment activities in the warehouse is defined by multiple selected workflows chosen from a workflow library stored in the memory; and The selection of workflow, the selection of operational configuration for each of the plurality of reconfigurable workstations, and the configuration of the modular inventory storage system correspond to the current state of the warehouse defined by the selected portion of the operational data and the expected demand.

13. The method of claim 12, further comprising controlling the sorting system by controlling a plurality of autonomous mobile robots (AMRs), each AMR configured to move inventory items from one location to the next desired location.

14. The method according to claim 13, wherein, The sorting system is a unit sorting system.

15. The method according to any one of claims 12 to 14, wherein, The modular inventory storage system includes one or more different storage technologies.

16. The method according to claim 15, wherein, Configuring the modular inventory storage system includes adding / removing additional storage modules to the modular inventory storage system based on current and / or anticipated needs.

17. The method according to claim 15, wherein, Configuring the modular inventory storage system includes adding / removing additional storage capacity to the modules of the modular inventory storage system based on current and / or anticipated needs.

18. The method according to any one of claims 12 to 14, wherein, The workflow involves one or more function calls, each function call being a microservice.

19. The method according to claim 18, wherein, The microservices include wrapper microservices, and each wrapper microservice includes sub-microservices selected from a library of sub-microservices.

20. The method according to claim 12, wherein, The reconfigurable workstation is configured for use by humans and / or robots.

21. The method according to any one of claims 12 to 14, further comprising: Determine or prioritize newly received orders; And if a newly received order has a higher priority than a previously received order, then if the service level agreement (SLA) of the newly received order needs to be satisfied, determine whether to reallocate the inventory allocated to one or more previously received orders to the newly received order.

22. The method according to any one of claims 12, 13, 14 or 20, wherein, The operational configurations for the reconfigurable workstations mentioned above include order fulfillment, inventory import, or order packaging.

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