Autonomous forklifts: A starting point, the current state of pragmatic data - The EE

Autonomous forklifts: A starting point, the current state of pragmatic data

As manufacturers seek to improve production processes, there are many considerations. Facing an array of technologies that promises to help reach future state Value Stream Mapping (VSM) goals, small and midsized manufacturers must carefully evaluate options, says Thomas R. Cutler.

Artificial intelligence (AI) and Deep Learning will be on factory floors worldwide by 2030, but for many small and midsized manufacturers working to cope with COVID consequences, replacing a manned forklift with an autonomous forklift allows for a “baby step” into the future state while adhering to the imminent demands of social distancing.

Getting decision-makers in SMEs to start with a single autonomous forklift is the first step in the process; the operations and facility managers understand that a single autonomous forklift is actually a good thing to improve quality, eliminate waste, and reduce costs.

SME manufacturers replacing 1 single manned forklift with 1 autonomous forklift

Here, manufacturing journalist, Thomas R. Cutler (TRC) interviews Gert Jensen (GJ) of Global AGV.

TRC: Are autonomous forklifts the logical way for small and mid-sized manufacturers to tiptoe into higher technologies? Is buy-in of this simple value proposition (moving product from A to B without a forklift driver) a good way to get started?

GJ: In general, the high technology trends will provide value in time to a variety of industries and products… but the top and immediate priority is dealing with employee safety, particularly during COVID.

TRC: Are autonomous forklifts the transition to a future state identified in value stream mapping?

GJ: Yes. It is a great first step. There are some real potential benefits that AGV technology can bring to support specific industries. The challenges in e-commerce fulfilment are different than in a packaging plant, yet both are good candidates for an autonomous forklift. Global AGV aims to target simple and intuitive interfaces to allow autonomous forklifts to be made accessible by the 49% of the market that has nine or fewer forklifts in a small fleet.

49% plan to acquire 9 or fewer forklifts this year, with 17% planning on < 3

Source: Peerless Research Group (PRG)

TRC: What is the current state of Big Data and AI and 5G limitations for SMEs adopting automation solutions, such as autonomous forklifts?

GJ: To create more intuitive and useful software, many companies are harvesting Big Data and applying AI and Machine Learning techniques for incremental improvements in efficiency and uptime of automation solutions. Many of these techniques require processing power and storage availability, so cloud solutions enable the raw infrastructure required to make these adjustments in real-time. There are bandwidth limitations and intermittent latencies that 5G promises to overcome to ensure that the cloud-based solutions can impact a process or machine in real-time for the biggest benefit.

While such optimisation will occur, many smaller manufacturers must crawl before they walk and walk before they run.

TRC: Why are there objections to Deep Learning among small to medium-sized enterprises (SMEs)?

GJ: To set up machine learning algorithms requires some sophisticated software and generally a cloud-based solution. Many manufacturers are against sharing their data in today’s world. Until IT departments get past this reluctance to share data and breaches are less likely to occur, small manufacturers remain with the pragmatism of effective product movement on the plant floor. With an AGV in a collaborative environment, human safety must be guaranteed. Removing a driver-operated forklift reduces risk and enhances safety.

TRC: Since nearly half of all manufacturers are purchasing a handful of autonomous forklifts, how do companies cost-justify the migration away from manned forklifts?

GJ: With nearly half of manufacturers testing single autonomous forklifts during COVID to adhere to strict social distancing, the benefits become obvious; equipment operates 24/7 and the A to B pragmatic solution is creating SME believers. The Big Data, Machine Learning, and other advanced business intelligence are almost certainly out of reach in small scale deployments due to the time and expertise required to apply them.

For large manufacturers, about 20% of whom are looking to invest in large fleets of 50-100+ units, deployment of mobile technologies for intralogistics such as 3PLs (third party logistics) makes sense. For everyone else, a single autonomous forklift is where the journey begins.

Thomas R. Cutler

The author is Thomas R. Cutler, the president and CEO of Fort Lauderdale, Florida-based, TR Cutler, Inc.

About the author

The author is Thomas R. Cutler, the president and CEO of Fort Lauderdale, Florida-based, TR Cutler, Inc., now celebrating its 21st year. Cutler is the founder of the Manufacturing Media Consortium including more than 8000 journalists, editors, and economists writing about trends in manufacturing, industry, material handling, and process improvement. Cutler authors more than 1000 feature articles annually regarding the manufacturing sector. More than 4600 industry leaders follow Cutler on Twitter daily at @ThomasRCutler. Contact Cutler at

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