Automated Material Handling Market by Equipment Type (Automated Guided Vehicles, Automated Storage And Retrieval Systems, Conveyors), End Use Industry (Automotive, ECommerce And Retail, Food And Beverage), Component, Installation Type - Global Forecast 20
Description
The Automated Material Handling Market was valued at USD 35.64 billion in 2024 and is projected to grow to USD 40.14 billion in 2025, with a CAGR of 12.72%, reaching USD 92.89 billion by 2032.
An authoritative orientation to the forces reshaping automated material handling, emphasizing technological integration, workforce transition, and operational resilience
The automated material handling landscape is undergoing accelerated transformation driven by converging forces in technology, labor dynamics, and supply chain strategy. This introduction frames the current environment, highlighting how advances in robotics, control software, and sensing systems are enabling a new class of flexible, scalable solutions that close the gap between warehouse intent and operational reality. Organizations are balancing immediate throughput needs with long-term resilience, and the decision calculus increasingly weighs total cost of ownership, retrofit feasibility, and software-driven orchestration rather than purely hardware-centric metrics.
As facility managers and supply chain leaders re-evaluate capital allocations, the interplay between installation choices and operational agility becomes central. New installations are often designed to embed modular automation platforms that support phased expansion, while retrofit opportunities emphasize interoperability and minimal disruption to ongoing operations. Moreover, workforce considerations now extend beyond headcount to include skills, change management, and safety protocols that accompany higher degrees of automation. Together, these dynamics set the stage for strategic investments that prioritize adaptability, integration readiness, and measurable productivity gains.
Fundamental shifts toward software-led integration, modular architectures, and workforce augmentation that are redefining value in material handling deployments
The landscape for automated material handling has shifted from point solutions toward architecture-level thinking, where digital orchestration binds discrete subsystems into coherent, responsive operations. This shift is evident as facilities migrate from fixed conveyor networks and isolated robots to software-led ecosystems that unify AGVs, ASRS, conveyors, palletizers, and sortation systems under centralized control frameworks. Interoperability and modularity have become decisive differentiators, as decision-makers favor technologies that allow incremental expansion without vendor lock-in or substantial rework.
Concurrently, the emphasis on data-driven performance has elevated software and analytics from supporting roles to strategic assets. Control software and warehouse management systems now serve as the command layer for real-time decisioning and predictive maintenance, enabling facilities to optimize throughput while reducing downtime. Edge computing and improved sensor fidelity have brought more deterministic control to previously stochastic processes, enabling tighter cycle times and higher reliability. Workforce dynamics have also evolved: organizations increasingly aim to augment human operators with collaborative robots and autonomous vehicles, reallocating labor to value-added tasks while addressing safety and training imperatives. As a result, procurement strategies are transitioning from a price-first mindset to a lifecycle-value orientation that prioritizes upgradeability, cybersecurity posture, and supplier ecosystems that offer professional services and long-term support.
How layered tariff measures influenced sourcing strategies, retrofit priorities, and the shift toward software and services as mitigants to hardware cost pressures
Cumulative tariff developments in the United States through 2025 have introduced layered effects across supplier selection, sourcing strategies, and total landed cost calculations for automated material handling equipment. Tariff-driven cost pressures have accelerated conversations around supply chain diversification and localization of critical hardware components, prompting both OEMs and systems integrators to reassess manufacturing footprints and distribution models. In many cases, procurement teams responded by seeking nearer-term alternatives, validating secondary suppliers, or negotiating longer-term agreements that provide pricing stability and assured lead times.
The tariff environment also shaped technology adoption patterns. Faced with higher import costs for certain hardware, some end users prioritized investments in software and services that increase throughput without proportional increases in hardware spend. Others restructured project scopes to favor retrofit installations that extend the life of existing assets rather than full-scale greenfield replacements. At the same time, tariffs spurred strategic supplier consolidation in some segments as buyers sought integrated vendors capable of absorbing cost volatility and delivering end-to-end project execution. These responses underscore a broader theme: trade policy changes acted as a catalyst for risk-management strategies that emphasize supply chain transparency, multi-sourcing, and the development of resilient procurement playbooks rather than solely dictating technology choices.
Actionable segmentation insights that connect equipment taxonomies, industry-specific requirements, component-level priorities, and installation strategies to deployment success
Understanding segmentation is essential to align solution design with operational objectives across diverse equipment types, end-use industries, component classes, and installation approaches. When viewed through the lens of equipment type, Automated Guided Vehicles coexist with Automated Storage and Retrieval Systems, conveyors, industrial robots, palletizing systems, and sortation systems, each with distinct operational profiles and integration requirements; within AGVs, examples such as forklift AGVs, towing AGVs, and unit load vehicles demand different navigation systems and safety schemas, while ASRS options like mini load, shuttle, and unit load variants impose varied footprint and throughput trade-offs. End-use industry segmentation further clarifies requirements: sectors such as automotive, eCommerce and retail, food and beverage, manufacturing, pharmaceuticals and healthcare, and warehousing and logistics manifest unique process constraints and regulatory considerations; automotive assembly plants and parts manufacturing prioritize high-precision sequencing, online retailers and brick-and-mortar channels emphasize order velocity and SKU diversity, and pharmaceutical operations necessitate stringent traceability and validation.
Component-level segmentation highlights where value accrues and where investment focus is likely to yield operational leverage. Hardware categories including control devices, conveying equipment, and robotic equipment require robust integration testing and lifecycle servicing plans, while services such as installation and maintenance and support are increasingly central to uptime guarantees and performance contracts. Software segmentation distinguishes control software and warehouse management systems as pivotal for orchestration, optimization, and unlocking new use cases such as goods-to-person workflows or dynamic slotting. Finally, installation type-new installations versus retrofit installations-frames deployment cadence and cost structures; new builds afford architectural freedom and higher initial automation ratios, whereas retrofits demand creative phasing, interoperability with legacy systems, and minimal operational disruption. Together, these segmentation lenses drive differentiated procurement criteria and implementation roadmaps that must be reconciled with organizational goals and operational realities.
Regional drivers and deployment dynamics that determine automation adoption pathways across the Americas, Europe Middle East & Africa, and Asia-Pacific markets
Regional dynamics materially influence strategic choices and deployment timelines for automated material handling solutions. In the Americas, demand patterns are shaped by a combination of distribution network expansion, labor market tightness in key logistics corridors, and a growing emphasis on nearshoring that affects supplier selection and logistics planning. These factors drive a preference for scalable solutions that can be deployed rapidly to meet peak season surges while maintaining configurability for diverse product assortments. Across Europe, the Middle East & Africa, stakeholders contend with regulatory variability, labor cost differentials, and urban density constraints that favor compact systems, energy-efficient designs, and solutions that integrate seamlessly into constrained footprints. Investments in automation here also reflect a heightened focus on sustainability metrics and compliance with evolving environmental standards.
In the Asia-Pacific region, high-volume manufacturing hubs, dense eCommerce fulfillment networks, and a broad spectrum of maturity levels among adopters create a dynamic market where both high-end automation and cost-optimized solutions coexist. Rapid urbanization and the prevalence of multi-channel retailing have accelerated the adoption of ASRS and sortation technologies that support high throughput and dense storage. Across all regions, supplier ecosystems and the availability of local service capabilities significantly influence procurement decisions, with buyers prioritizing partners that can provide regional engineering support, spare parts availability, and response SLAs that align with operational risk tolerances.
Competitive and capability insights that reveal how vendor combinations, integration know-how, and service innovation drive project win rates and long-term client value
Competitive dynamics in the automated material handling space are defined by a diverse set of participants that include equipment OEMs, systems integrators, software platform providers, and service specialists. Companies that combine deep domain engineering with modular product architectures tend to win larger, more complex projects because they can demonstrate predictable integration outcomes and reduced commissioning timelines. Strategic partnerships between hardware vendors and software firms increasingly underpin compelling value propositions, enabling tighter coupling between physical assets and higher-level orchestration layers that deliver measurable throughput improvements and maintenance efficiencies.
At the same time, systems integrators that offer comprehensive professional services-from needs assessment and solution design to installation, training, and post-deployment support-are capturing a growing share of project value. Their ability to manage multi-vendor environments and to translate operational KPIs into technical specifications positions them as essential intermediaries, especially for retrofit projects where legacy constraints complicate rollout. Service innovation is another differentiator: providers that offer outcome-based contracts, predictive maintenance programs, and flexible financing arrangements are more likely to build long-term client relationships and to secure recurring revenue streams. Finally, software providers that prioritize open APIs, cyber-secure architectures, and intuitive operator interfaces are accelerating adoption by lowering integration risk and enabling faster user acceptance.
Practical, phased recommendations for leaders to maximize automation returns through modular investments, supplier diversification, workforce reskilling, and service-driven models
Industry leaders should adopt a pragmatic, phased approach to automation investments that balances strategic objectives with operational realities. Begin by prioritizing deployments that deliver the fastest, verifiable improvements in labor productivity and throughput while preserving architectural flexibility for future expansion. Where possible, structure procurements to include modular hardware that supports incremental capacity additions and software licenses that enable staged activation of advanced features. Leaders should also embed rigorous acceptance criteria and data-driven KPIs into contracts to ensure accountability and to facilitate continuous improvement after go-live.
In parallel, invest in supplier diversification and supply chain transparency to mitigate sourcing risks exposed by trade policy shifts or component shortages. Developing deeper relationships with regional engineering and service partners can shorten response times and reduce the total cost of ownership. From a workforce perspective, allocate budget to structured training and reskilling programs that prepare operators and technicians for higher-skill roles associated with automated environments. Finally, embrace a product-plus-services mindset: pairing hardware deployments with professional services, predictive maintenance, and software-driven optimization will maximize uptime and accelerate return on operational objectives while creating enduring competitive advantage.
A transparent, multi-method research approach combining practitioner interviews, technical synthesis, scenario analysis, and stakeholder validation to ensure operational relevance and accuracy
This research synthesizes insights from a multi-method approach designed to reflect both technological nuance and operational realities. Primary data was collected through structured interviews with practitioners across distribution, manufacturing, and eCommerce operations, alongside conversations with engineering leads at integrator organizations and control software providers. These qualitative inputs were triangulated with secondary sources including technical white papers, trade association publications, standards documents, and product literature to ensure accuracy in technology descriptions and deployment considerations.
Analytical techniques included comparative capability mapping across equipment types, scenario analysis to evaluate responses to supply chain disruptions and tariff changes, and systems integration assessment to determine common interoperability challenges. Validation workshops with industry stakeholders were held to test assumptions about retrofit feasibility, commissioning timelines, and service models. Throughout the process, emphasis was placed on operational applicability: recommendations and insights were vetted against real-world constraints such as facility layouts, workforce skill sets, and regulatory requirements to ensure they translate into executable plans for decision-makers.
Synthesis of strategic imperatives and operational priorities that executives must align to convert automation investments into durable competitive advantages
In summary, the automated material handling domain is transitioning from fragmented implementations to coherent, software-enabled ecosystems that deliver higher throughput, greater resiliency, and more predictable operational outcomes. Decision-makers must navigate a complex interplay of equipment choices, industry-specific requirements, component-level priorities, and installation constraints while also responding to external pressures such as tariff shifts and regional supply chain dynamics. Success will depend on adopting modular architectures, strengthening supplier and service partnerships, and investing in the human capital required to operate and sustain advanced automated systems.
The insights presented here are designed to empower executives and operations leaders to make informed choices about where to invest, when to retrofit, and how to structure partnerships that deliver sustained value. By prioritizing flexibility, interoperability, and lifecycle serviceability, organizations can convert automation investments into durable advantages that support both near-term performance and long-term strategic objectives.
Note: PDF & Excel + Online Access - 1 Year
An authoritative orientation to the forces reshaping automated material handling, emphasizing technological integration, workforce transition, and operational resilience
The automated material handling landscape is undergoing accelerated transformation driven by converging forces in technology, labor dynamics, and supply chain strategy. This introduction frames the current environment, highlighting how advances in robotics, control software, and sensing systems are enabling a new class of flexible, scalable solutions that close the gap between warehouse intent and operational reality. Organizations are balancing immediate throughput needs with long-term resilience, and the decision calculus increasingly weighs total cost of ownership, retrofit feasibility, and software-driven orchestration rather than purely hardware-centric metrics.
As facility managers and supply chain leaders re-evaluate capital allocations, the interplay between installation choices and operational agility becomes central. New installations are often designed to embed modular automation platforms that support phased expansion, while retrofit opportunities emphasize interoperability and minimal disruption to ongoing operations. Moreover, workforce considerations now extend beyond headcount to include skills, change management, and safety protocols that accompany higher degrees of automation. Together, these dynamics set the stage for strategic investments that prioritize adaptability, integration readiness, and measurable productivity gains.
Fundamental shifts toward software-led integration, modular architectures, and workforce augmentation that are redefining value in material handling deployments
The landscape for automated material handling has shifted from point solutions toward architecture-level thinking, where digital orchestration binds discrete subsystems into coherent, responsive operations. This shift is evident as facilities migrate from fixed conveyor networks and isolated robots to software-led ecosystems that unify AGVs, ASRS, conveyors, palletizers, and sortation systems under centralized control frameworks. Interoperability and modularity have become decisive differentiators, as decision-makers favor technologies that allow incremental expansion without vendor lock-in or substantial rework.
Concurrently, the emphasis on data-driven performance has elevated software and analytics from supporting roles to strategic assets. Control software and warehouse management systems now serve as the command layer for real-time decisioning and predictive maintenance, enabling facilities to optimize throughput while reducing downtime. Edge computing and improved sensor fidelity have brought more deterministic control to previously stochastic processes, enabling tighter cycle times and higher reliability. Workforce dynamics have also evolved: organizations increasingly aim to augment human operators with collaborative robots and autonomous vehicles, reallocating labor to value-added tasks while addressing safety and training imperatives. As a result, procurement strategies are transitioning from a price-first mindset to a lifecycle-value orientation that prioritizes upgradeability, cybersecurity posture, and supplier ecosystems that offer professional services and long-term support.
How layered tariff measures influenced sourcing strategies, retrofit priorities, and the shift toward software and services as mitigants to hardware cost pressures
Cumulative tariff developments in the United States through 2025 have introduced layered effects across supplier selection, sourcing strategies, and total landed cost calculations for automated material handling equipment. Tariff-driven cost pressures have accelerated conversations around supply chain diversification and localization of critical hardware components, prompting both OEMs and systems integrators to reassess manufacturing footprints and distribution models. In many cases, procurement teams responded by seeking nearer-term alternatives, validating secondary suppliers, or negotiating longer-term agreements that provide pricing stability and assured lead times.
The tariff environment also shaped technology adoption patterns. Faced with higher import costs for certain hardware, some end users prioritized investments in software and services that increase throughput without proportional increases in hardware spend. Others restructured project scopes to favor retrofit installations that extend the life of existing assets rather than full-scale greenfield replacements. At the same time, tariffs spurred strategic supplier consolidation in some segments as buyers sought integrated vendors capable of absorbing cost volatility and delivering end-to-end project execution. These responses underscore a broader theme: trade policy changes acted as a catalyst for risk-management strategies that emphasize supply chain transparency, multi-sourcing, and the development of resilient procurement playbooks rather than solely dictating technology choices.
Actionable segmentation insights that connect equipment taxonomies, industry-specific requirements, component-level priorities, and installation strategies to deployment success
Understanding segmentation is essential to align solution design with operational objectives across diverse equipment types, end-use industries, component classes, and installation approaches. When viewed through the lens of equipment type, Automated Guided Vehicles coexist with Automated Storage and Retrieval Systems, conveyors, industrial robots, palletizing systems, and sortation systems, each with distinct operational profiles and integration requirements; within AGVs, examples such as forklift AGVs, towing AGVs, and unit load vehicles demand different navigation systems and safety schemas, while ASRS options like mini load, shuttle, and unit load variants impose varied footprint and throughput trade-offs. End-use industry segmentation further clarifies requirements: sectors such as automotive, eCommerce and retail, food and beverage, manufacturing, pharmaceuticals and healthcare, and warehousing and logistics manifest unique process constraints and regulatory considerations; automotive assembly plants and parts manufacturing prioritize high-precision sequencing, online retailers and brick-and-mortar channels emphasize order velocity and SKU diversity, and pharmaceutical operations necessitate stringent traceability and validation.
Component-level segmentation highlights where value accrues and where investment focus is likely to yield operational leverage. Hardware categories including control devices, conveying equipment, and robotic equipment require robust integration testing and lifecycle servicing plans, while services such as installation and maintenance and support are increasingly central to uptime guarantees and performance contracts. Software segmentation distinguishes control software and warehouse management systems as pivotal for orchestration, optimization, and unlocking new use cases such as goods-to-person workflows or dynamic slotting. Finally, installation type-new installations versus retrofit installations-frames deployment cadence and cost structures; new builds afford architectural freedom and higher initial automation ratios, whereas retrofits demand creative phasing, interoperability with legacy systems, and minimal operational disruption. Together, these segmentation lenses drive differentiated procurement criteria and implementation roadmaps that must be reconciled with organizational goals and operational realities.
Regional drivers and deployment dynamics that determine automation adoption pathways across the Americas, Europe Middle East & Africa, and Asia-Pacific markets
Regional dynamics materially influence strategic choices and deployment timelines for automated material handling solutions. In the Americas, demand patterns are shaped by a combination of distribution network expansion, labor market tightness in key logistics corridors, and a growing emphasis on nearshoring that affects supplier selection and logistics planning. These factors drive a preference for scalable solutions that can be deployed rapidly to meet peak season surges while maintaining configurability for diverse product assortments. Across Europe, the Middle East & Africa, stakeholders contend with regulatory variability, labor cost differentials, and urban density constraints that favor compact systems, energy-efficient designs, and solutions that integrate seamlessly into constrained footprints. Investments in automation here also reflect a heightened focus on sustainability metrics and compliance with evolving environmental standards.
In the Asia-Pacific region, high-volume manufacturing hubs, dense eCommerce fulfillment networks, and a broad spectrum of maturity levels among adopters create a dynamic market where both high-end automation and cost-optimized solutions coexist. Rapid urbanization and the prevalence of multi-channel retailing have accelerated the adoption of ASRS and sortation technologies that support high throughput and dense storage. Across all regions, supplier ecosystems and the availability of local service capabilities significantly influence procurement decisions, with buyers prioritizing partners that can provide regional engineering support, spare parts availability, and response SLAs that align with operational risk tolerances.
Competitive and capability insights that reveal how vendor combinations, integration know-how, and service innovation drive project win rates and long-term client value
Competitive dynamics in the automated material handling space are defined by a diverse set of participants that include equipment OEMs, systems integrators, software platform providers, and service specialists. Companies that combine deep domain engineering with modular product architectures tend to win larger, more complex projects because they can demonstrate predictable integration outcomes and reduced commissioning timelines. Strategic partnerships between hardware vendors and software firms increasingly underpin compelling value propositions, enabling tighter coupling between physical assets and higher-level orchestration layers that deliver measurable throughput improvements and maintenance efficiencies.
At the same time, systems integrators that offer comprehensive professional services-from needs assessment and solution design to installation, training, and post-deployment support-are capturing a growing share of project value. Their ability to manage multi-vendor environments and to translate operational KPIs into technical specifications positions them as essential intermediaries, especially for retrofit projects where legacy constraints complicate rollout. Service innovation is another differentiator: providers that offer outcome-based contracts, predictive maintenance programs, and flexible financing arrangements are more likely to build long-term client relationships and to secure recurring revenue streams. Finally, software providers that prioritize open APIs, cyber-secure architectures, and intuitive operator interfaces are accelerating adoption by lowering integration risk and enabling faster user acceptance.
Practical, phased recommendations for leaders to maximize automation returns through modular investments, supplier diversification, workforce reskilling, and service-driven models
Industry leaders should adopt a pragmatic, phased approach to automation investments that balances strategic objectives with operational realities. Begin by prioritizing deployments that deliver the fastest, verifiable improvements in labor productivity and throughput while preserving architectural flexibility for future expansion. Where possible, structure procurements to include modular hardware that supports incremental capacity additions and software licenses that enable staged activation of advanced features. Leaders should also embed rigorous acceptance criteria and data-driven KPIs into contracts to ensure accountability and to facilitate continuous improvement after go-live.
In parallel, invest in supplier diversification and supply chain transparency to mitigate sourcing risks exposed by trade policy shifts or component shortages. Developing deeper relationships with regional engineering and service partners can shorten response times and reduce the total cost of ownership. From a workforce perspective, allocate budget to structured training and reskilling programs that prepare operators and technicians for higher-skill roles associated with automated environments. Finally, embrace a product-plus-services mindset: pairing hardware deployments with professional services, predictive maintenance, and software-driven optimization will maximize uptime and accelerate return on operational objectives while creating enduring competitive advantage.
A transparent, multi-method research approach combining practitioner interviews, technical synthesis, scenario analysis, and stakeholder validation to ensure operational relevance and accuracy
This research synthesizes insights from a multi-method approach designed to reflect both technological nuance and operational realities. Primary data was collected through structured interviews with practitioners across distribution, manufacturing, and eCommerce operations, alongside conversations with engineering leads at integrator organizations and control software providers. These qualitative inputs were triangulated with secondary sources including technical white papers, trade association publications, standards documents, and product literature to ensure accuracy in technology descriptions and deployment considerations.
Analytical techniques included comparative capability mapping across equipment types, scenario analysis to evaluate responses to supply chain disruptions and tariff changes, and systems integration assessment to determine common interoperability challenges. Validation workshops with industry stakeholders were held to test assumptions about retrofit feasibility, commissioning timelines, and service models. Throughout the process, emphasis was placed on operational applicability: recommendations and insights were vetted against real-world constraints such as facility layouts, workforce skill sets, and regulatory requirements to ensure they translate into executable plans for decision-makers.
Synthesis of strategic imperatives and operational priorities that executives must align to convert automation investments into durable competitive advantages
In summary, the automated material handling domain is transitioning from fragmented implementations to coherent, software-enabled ecosystems that deliver higher throughput, greater resiliency, and more predictable operational outcomes. Decision-makers must navigate a complex interplay of equipment choices, industry-specific requirements, component-level priorities, and installation constraints while also responding to external pressures such as tariff shifts and regional supply chain dynamics. Success will depend on adopting modular architectures, strengthening supplier and service partnerships, and investing in the human capital required to operate and sustain advanced automated systems.
The insights presented here are designed to empower executives and operations leaders to make informed choices about where to invest, when to retrofit, and how to structure partnerships that deliver sustained value. By prioritizing flexibility, interoperability, and lifecycle serviceability, organizations can convert automation investments into durable advantages that support both near-term performance and long-term strategic objectives.
Note: PDF & Excel + Online Access - 1 Year
Table of Contents
185 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Integration of autonomous mobile robots with AI-driven dynamic routing for real-time order fulfillment optimization
- 5.2. Deployment of collaborative robotic arms with advanced vision for precise high-mix low-volume assembly tasks
- 5.3. Implementation of IoT-enabled conveyor systems with predictive maintenance through machine learning analytics
- 5.4. Adoption of digital twin technology for virtual simulation and continuous optimization of warehouse workflows
- 5.5. Utilization of blockchain-based asset tracking to ensure secure end-to-end visibility in supply chain networks
- 5.6. Development of automated guided vehicles with multi-sensor fusion for safe navigation in mixed human environments
- 5.7. Utilization of energy-efficient regenerative braking in automated material handling equipment to reduce operational costs
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. Automated Material Handling Market, by Equipment Type
- 8.1. Automated Guided Vehicles
- 8.1.1. Forklift AGVs
- 8.1.2. Towing AGVs
- 8.1.3. Unit Load Vehicles
- 8.2. Automated Storage And Retrieval Systems
- 8.2.1. Mini Load ASRS
- 8.2.2. Shuttle ASRS
- 8.2.3. Unit Load ASRS
- 8.3. Conveyors
- 8.3.1. Belt Conveyors
- 8.3.2. Chain Conveyors
- 8.3.3. Roller Conveyors
- 8.4. Industrial Robots
- 8.4.1. Articulated Robots
- 8.4.2. Delta Robots
- 8.4.3. SCARA Robots
- 8.5. Palletizing Systems
- 8.5.1. Conventional Palletizers
- 8.5.2. Robotic Palletizers
- 8.6. Sortation Systems
- 8.6.1. Cross-Belt Sorters
- 8.6.2. Parcel Sorters
- 8.6.3. Sliding Shoe Sorters
- 9. Automated Material Handling Market, by End Use Industry
- 9.1. Automotive
- 9.1.1. Assembly Plants
- 9.1.2. Parts Manufacturing
- 9.2. ECommerce And Retail
- 9.2.1. Brick And Mortar Retailers
- 9.2.2. Online Retailers
- 9.3. Food And Beverage
- 9.3.1. Beverage Processing
- 9.3.2. Packaged Food
- 9.4. Manufacturing
- 9.4.1. Discrete Manufacturing
- 9.4.2. Process Manufacturing
- 9.5. Pharmaceuticals And Healthcare
- 9.5.1. Hospital Pharmacies
- 9.5.2. Pharmaceutical Manufacturing
- 9.6. Warehousing And Logistics
- 9.6.1. Distribution Centers
- 9.6.2. Third Party Providers
- 10. Automated Material Handling Market, by Component
- 10.1. Hardware
- 10.1.1. Control Devices
- 10.1.2. Conveying Equipment
- 10.1.3. Robotic Equipment
- 10.2. Services
- 10.2.1. Installation
- 10.2.2. Maintenance And Support
- 10.3. Software
- 10.3.1. Control Software
- 10.3.2. Warehouse Management Systems
- 11. Automated Material Handling Market, by Installation Type
- 11.1. New Installations
- 11.2. Retrofit Installations
- 12. Automated Material Handling Market, by Region
- 12.1. Americas
- 12.1.1. North America
- 12.1.2. Latin America
- 12.2. Europe, Middle East & Africa
- 12.2.1. Europe
- 12.2.2. Middle East
- 12.2.3. Africa
- 12.3. Asia-Pacific
- 13. Automated Material Handling Market, by Group
- 13.1. ASEAN
- 13.2. GCC
- 13.3. European Union
- 13.4. BRICS
- 13.5. G7
- 13.6. NATO
- 14. Automated Material Handling Market, by Country
- 14.1. United States
- 14.2. Canada
- 14.3. Mexico
- 14.4. Brazil
- 14.5. United Kingdom
- 14.6. Germany
- 14.7. France
- 14.8. Russia
- 14.9. Italy
- 14.10. Spain
- 14.11. China
- 14.12. India
- 14.13. Japan
- 14.14. Australia
- 14.15. South Korea
- 15. Competitive Landscape
- 15.1. Market Share Analysis, 2024
- 15.2. FPNV Positioning Matrix, 2024
- 15.3. Competitive Analysis
- 15.3.1. Daifuku Co., Ltd.
- 15.3.2. Honeywell International Inc.
- 15.3.3. Murata Machinery, Ltd.
- 15.3.4. Toyota Industries Corporation
- 15.3.5. SSI Schaefer AG
- 15.3.6. Vanderlande Industries B.V.
- 15.3.7. BEUMER Group GmbH & Co. KG
- 15.3.8. Fives Group
- 15.3.9. Intelligrated, Inc.
- 15.3.10. Knapp AG
- 15.3.11. Mecalux, S.A.
- 15.3.12. Swisslog Holding AG (KUKA AG)
- 15.3.13. TGW Logistics Group GmbH
- 15.3.14. Witron Logistik + Informatik GmbH
- 15.3.15. Bastian Solutions, LLC
- 15.3.16. JBT Corporation
- 15.3.17. Kardex AG
- 15.3.18. System Logistics S.p.A.
- 15.3.19. Viastore Systems GmbH
- 15.3.20. Hanel GmbH & Co. KG
- 15.3.21. Eisenmann SE
- 15.3.22. Lödige Industries GmbH
- 15.3.23. Addverb Technologies Pvt. Ltd.
- 15.3.24. Grenzebach Maschinenbau GmbH
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