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Automated Material Handling Market - Forecasts from 2022 to 2027

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    Report

  • 133 Pages
  • August 2022
  • Region: Global
  • Knowledge Sourcing Intelligence LLP
  • ID: 5649021
The automated material handling market was evaluated at US$26.485 billion for the year 2020, growing at a CAGR of 7.36%, reaching a market size of US$43.528 billion by the year 2027. Automated material handling is a term derived from handling practices that refers to various forms of automation to assist people in a manufacturing facility in transporting products under production between assembly stations or finished goods to storage facilities. These jobs were taken over by machines with the development of technology, resulting in the industry for automated material handling. In today’s marketplace, businesses are increasingly focusing on integrating various technologies into their operations to cut overall costs and obtain a strong position in the market.

The e-commerce industry is booming all over the world, providing a huge need for process automation. Amazon, Walmart, and other major retailers are progressively incorporating automated technologies to carry out operations in a more consistent, precise, cost-effective, and secure manner. For example, Amazon secured a deal with Baylo, a French robotic software business, in January 2020. The value of this commercial arrangement was added to the design and development of revolutionary robotic systems for material handling trucks. This strategic initiative improved Amazon's warehouse material management, making the e-commerce business smoother. Apart from that, the growth of the manufacturing sector is a notable contributor to market expansion. Owners of facilities are concentrating on supplying and distributing products to their clients at a faster, cheaper, and higher quality rate. As a result, integrating automated equipment allows for more efficient production cycles, minimizing operational costs and waste.

Furthermore, the automated material handling industry is anticipated to benefit from the growing trend toward smart factories. To evaluate operating efficiency and decrease waste, the entire manufacturing process, including selecting, sorting, and conveying systems, needs monitoring at every step of the process. In such cases, smart factories with automated systems continuously monitor all processes. The rise of industry 4.0 and innovative factory development, as a result of the aforementioned factors, provides a potential area for the automated material handling market.

However, large implementation and switching expenses of automated material handling solutions are limiting market expansion. Deployment, incorporation of intelligent sensors, software solutions, after-sales services, and regular maintenance all add to the total cost of ownership, making it difficult for businesses to invest in AMH equipment. Due to poor operational output and market returns, as well as the reorganization of pre-existing facilities, plant designs, and other factors, smaller businesses find it challenging to transition from traditional handling of materials to automated products.

Because of the expansion of numerous technologies deployed in AGV, like SLAM which signifies simultaneous localization and mapping, machine learning, and the Internet of Things, the automated guided vehicle segment is anticipated to grow at the fastest rate. Furthermore, prominent businesses are constantly working to improve established automated guided vehicles to provide more efficient products in logistical environments.

The Airport segment is expected to significantly drive market growth by industrial vertical. The demand for automated handling services such as tugs, ASRS, and sorting systems increases as the volume of cross-border freight dedicated to speedy deliveries rises, as hefty air freight carriers pay close attention to AMH solutions. The growth of the airport segment in the country is being driven by investments from pioneering airport logistics solution providers, such as Siemens Logistics and Airport Solutions, as well as the deployment of new baggage-handling facilities & IT frameworks, along with operational, service, and technical support. For example, Stansted Airport has been investing € 59 million in a new luggage delivery system since December 2019, modernizing the vast network of conveyor belts and other equipment. John Bean Technologies Corp. also launched JBT Cargo Chute, a method for unloading products from passenger cabins, in August 2020. The chute can be added to existing or new passenger steps, allowing parcels to slide down safely and in a controlled way, removing the need to either hold the products while walking down the steps or have additional operators on the steps passing the packages between each other.

In the projected period, Asia-Pacific is expected to grow the fastest. Expanding industrialization, increasing e-commerce revenues, and the considerable presence of technology providers are the key driving drivers for the Asia-Pacific regional segment's growth. As a result, many companies spend on R&D to provide innovative solutions to stay competitive. In June 2020, for example, VisionNav Robotics completed a B1 round of funding for approximately CNY 100.00 million, headed by Lenovo Capital & Flyfot Ventures, with the old stakeholder, Eastern Bell Capital. The funds were used to expand R&D to improve existing visual control & perception technology. These examples will help the AMH market grow even faster.

Recent Development

In September 2020, Bohus, a large furniture manufacturer in Norway, tasked Jungheinrich with developing a new warehouse facility in Lillestrom, near Oslo. The project includes a high-pallet-racking facility, mini-load conveyors, and software, among other automation technologies.

TJ Morris Ltd, one of the UK's fastest-growing and best-rated retailers in Europe, has chosen WITRON to help its expansion plans. In Warrington, the business signed a contract for the design and construction of a 79,000 square meter rapidly evolving distribution centre with a capacity to hold 12,000 different dry goods items.

COVID-19 Impact

The COVID-19 pandemic had a relatively negative effect on the market, owing to the production hub closures and supply chain disruption. However, the market is anticipated to stabilize in the long run as large businesses move their focus to automated material handling solutions to save labour on factory floors and get a faster return on investment.

Segmentation

By Type

  • Automated Conveyor & Sorting System
  • Automated Storage and Retrieval System
  • Automated Guided Vehicle

By Industry Vertical

  • Airport
  • Manufacturing
  • Healthcare
  • Chemical
  • Paper
  • Food and Beverage
  • Warehousing

By Geography

  • North America
  • USA
  • Canada
  • Mexico
  • South America
  • Brazil
  • Argentina
  • Europe
  • United Kingdom
  • Germany
  • France
  • Italy
  • Middle East and Africa
  • Saudi Arabia
  • Israel
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Indonesia
  • Thailand
  • Taiwan
Frequently Asked Questions about the Automated Material Handling Market

What is the estimated value of the Automated Material Handling Market?

The Automated Material Handling Market was estimated to be valued at $26.49 billion in 2020.

What is the growth rate of the Automated Material Handling Market?

The growth rate of the Automated Material Handling Market is 7.3%, with an estimated value of $43.53 billion by 2027.

What is the forecasted size of the Automated Material Handling Market?

The Automated Material Handling Market is estimated to be worth $43.53 billion by 2027.

Who are the key companies in the Automated Material Handling Market?

Key companies in the Automated Material Handling Market include BEUMER Group, Daifuku Co., Ltd., Honeywell Intelligrated, Dematic GMBH & Co. KG, Amazon Robotics, The Schaefer Group, Bosch Rexroth, Siemens AG, Toyota Industries Corporation and Konecranes Plc.

Table of Contents

1. Introduction
1.1. Market Overview
1.2. Covid-19 Scenario
1.3. Market Definition
1.4. Market Segmentation
2. Research Methodology
2.1. Research Data
2.2. Assumptions
3. Executive Summary
3.1. Research Highlights
4. Market Dynamics
4.1. Market Drivers
4.2. Market Restraints
4.3. Market Opportunities
4.4. Porter’s Five Forces Analysis
4.4.1. Bargaining Power of Suppliers
4.4.2. Bargaining Power of Buyers
4.4.3. Threat of New Entrants
4.4.4. Threat of Substitutes
4.4.5. Competitive Rivalry in the Industry
4.5. Industry Value Chain Analysis
5. Automated Material Handling Market Analysis, by Type
5.1. Introduction
5.2. Automated Conveyor & Sorting System
5.3. Automated Storage and Retrieval System
5.4. Automated Guided Vehicle
6. Automated Material Handling Market Analysis, by Industry Vertical
6.1. Introduction
6.2. Airport
6.3. Manufacturing
6.4. Healthcare
6.5. Chemical
6.6. Paper
6.7. Food and Beverage
6.8. Warehousing
6.9. Others
7. Automated Material Handling Market Analysis, by Geography
7.1. Introduction
7.2. North America
7.2.1. USA
7.2.2. Canada
7.2.3. Mexico
7.3. South America
7.3.1. Brazil
7.3.2. Argentina
7.3.3. Others
7.4. Europe
7.4.1. United Kingdom
7.4.2. Germany
7.4.3. France
7.4.4. Italy
7.4.5. Others
7.5. The Middle East and Africa
7.5.1. Saudi Arabia
7.5.2. Israel
7.5.3. Others
7.6. Asia Pacific
7.6.1. China
7.6.2. Japan
7.6.3. India
7.6.4. South Korea
7.6.5. Indonesia
7.6.6. Thailand
7.6.7. Taiwan
7.6.8. Others
8. Competitive Environment and Analysis
8.1. Major Players and Strategy Analysis
8.2. Emerging Players and Market Lucrativeness
8.3. Mergers, Acquisitions, Agreements, and Collaborations
8.4. Vendor Competitiveness Matrix
9. Company Profiles
9.1. BEUMER Group
9.2. Daifuku Co., Ltd.
9.3. Honeywell Intelligrated
9.4. Dematic GMBH & Co. KG
9.5. Amazon Robotics
9.6. The Schaefer Group
9.7. Bosch Rexroth
9.8. Siemens AG
9.9. Toyota Industries Corporation
9.10. Konecranes Plc

Companies Mentioned

  • BEUMER Group
  • Daifuku Co., Ltd.
  • Honeywell Intelligrated
  • Dematic GMBH & Co. KG
  • Amazon Robotics
  • The Schaefer Group
  • Bosch Rexroth
  • Siemens AG
  • Toyota Industries Corporation
  • Konecranes Plc

Methodology

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