AI for Pallet Manufacturers: Plain English

We have previously discussed pallet production robotics and its implications for small to mid-sized manufacturers. At the time, you learned about technologies such as end-of-arm tooling (EOAT) and collaborative robots (cobots). However, we left an elephant in the room without mentioning it: artificial intelligence (AI). Let's talk about what artificial intelligence means for pallet manufacturers. Most importantly, we will look past the hype and the inevitable sales pitches.

AI Does Not Replace Workers; It Needs Them

While some technologies may replace employees, artificial intelligence does not. In this context, AI relies on workers to incorporate its suggestions, findings, and alerts to reduce waste, increase output, and minimize unpredictable downtimes. While integrating new technology may have altered your employees' job descriptions, the goal here must be to have AI and workers collaborate effectively. What does this look like?

Predictive Maintenance Reports Lead to Fewer Breakdowns and Less Downtime

For pallet manufacturers, artificial intelligence means a proactive approach to equipment maintenance. In the past, you might run machines until they fail. Long-time employees attuned to machine noises may have noticed changes, but only after the problems had already become significant. Now, AI monitors minute changes in machine vibrations, operating temperatures, and other conditions that could signal a future breakdown. Your employees receive these readings, interpret them correctly, and predict when saws, compressors, nailers, or conveyors at your facility need service before they break down. It allows you to schedule technology maintenance during typically low-production periods.

Increased Production Efficiency

What will it take to squeeze out more productivity from your saws, nailers, and assembly lines? Something as simple as smart nailing line optimization with AI can increase the number of pallets your factory produces per hour while markedly reducing defects. Increasing efficiency no longer means starting the workday earlier or paying for overtime. Instead, it now relies on AI to:

• Adjust the nailing line speed to accommodate constantly changing data being analyzed.
• Monitor nail firing rates, board placement timing, and conveyor speed to adjust feed timing and workflow.
• Adjust nail counts and placement based on lumber differences, such as variable board densities and changing board measurements.

Here, AI helps employees move away from fixed parameters that can bring your production line to a halt when anything changes. It frees up your employees to work with the technology you are bringing into the factory, increasing your return on investment.

Reduced Lumber Waste

Waste is one of the most significant problems that pallet manufacturers face. It dramatically affects your bottom line. In many cases, waste is a direct result of human error. AI has your back. Lumber board inspection sensors scan the boards for defects and automatically grade them. Moreover, it determines the optimal cut patterns based on the analysis of each board. While it is impossible to remove all defective pieces of lumber before they enter your factory, it is now possible to work with the boards you have and still reduce scrap.

AI-Driven Quality Control (QC) is Impartial and Consistent

Human QC is inconsistent. What one employee considers faulty, another might consider acceptable. AI checks quality against pre-defined patterns and provides objective, continuous verification. It can do so without slowing down or stopping production. Machine learning and computer vision combine to identify commonalities. And, if you find that AI is getting a little too meticulous, you can allow for variances that the machine will learn and incorporate in its workings.

• Nails. Missing nails, nails that are incorrectly angled, and over- or under-driven nails are common complaints customers cite when rejecting pallets. AI catches these issues before the pallets leave your factory.
• Boards. Lumber that appears great upon arrival may have internal defects, resulting in split ends, edge cracks, and knots, which compromise the overall load-bearing capabilities of individual pallets. Besides that, AI notices variances in deck board spacing and overhangs. Unsafe pallets are removed from orders before they are shipped out.
• Customer specs. Making changes during pallet runs can result in human error. Nail counts and pattern requirements may not be met for some of the early pallets. High-speed cameras and machine learning AI rely on effectively reducing chargebacks and missed audit opportunities.

From the Factory Floor to the Office

It is essential to note that machine learning, computer vision, and smart factory output are just a few of the capabilities AI offers. While reducing pallet manufacturing waste with AI is one of the most popular uses of this technology, it is also highly effective in the office setting. Once again, you choose which processes you want to automate.

Automated Production Forecasting

Using AI for forecasting helps predict how much lumber to buy and store, as well as how many pallets to pre-build. The technology analyzes and incorporates data from historical orders, established customer behavior, and predictable production constraints. Depending on the data to which AI has access, it can forecast volume needed by pallet type, pallet repairs, and customer-specific buying patterns.

Automated Inventory Forecasting

On the other hand, AI can translate forecasted demand into the necessary inventory. Examples include board cuts, grade, block requirements, and nail quantities. Your business can purchase supplies that will be used rather than storing them and risking them becoming unusable. Also, you will never run out of fasteners because one of the office clerks neglected to place an order when the inventory got low.

Industrial Automation is Advantageous for Small and Mid-Sized Pallet Makers

Here is what artificial intelligence means for pallet manufacturers who invest in at least some new technology.

• Data collection. AI evaluates everything from production system information and actual sales. It can use real-time data and typically allows the addition of historical data.
• Pattern learning. Machine learning is essentially about acting on the data that has been collected and evaluated. These patterns can be utilized for manufacturing, ordering, and customer service purposes. Your office staff will be pleasantly surprised by how easy their tasks become.
• Ongoing learning. Things change. New customers come to your business. Established customers change their orders. Returns underscore-specific QC failures. AI continues to learn, update its data collection, and act on the information it receives. Its ability to analyze and act on data within seconds makes your company more competitive than a factory still operating manually.

For the office staff, this means actionable outputs, such as stock inventory, that provide a cushion without clogging your warehouse. Additionally, you will receive purchase recommendations and suggested build schedules.

In Plain English: AI Forecasting Versus Traditional Forecasting Methods

We promised you plain English, and here it is. The traditional way of doing business relied on static spreadsheets, overstock that exceeded a needed cushion, and reactive buying that routinely creates budget problems. The AI approach to business incorporates self-learning technology that enables predictive purchasing and optimized (lean) inventory management.

What makes it overwhelming to consider AI is the sheer magnitude of the technology. There is also the misunderstanding that you have to jump in with both feet. It is not true! AI enables the gradual and scalable integration into your manufacturing and office processes. Start small; vision-based inspection analytics are a great way to get started. Once you feel comfortable and see the benefits, consider integrating AI with other existing automation. Eventually, you will look forward to expanding AI for forecasting and ongoing operational optimization.

You Know Pallet Manufacturing, We Know Marketing for the Industry

Whenever you introduce new technology or upgrade existing technology in your factory, it is a good idea to inform both current and prospective customers. Doing so demonstrates that you are at the forefront of pallet manufacturing, which signals that your business is trustworthy and suitable for customers who are also integrating new technology into their operations.

Our team brings an expert pallet industry marketing strategy to the table. While you focus on integrating new technology or AI into your factory, we handle your digital marketing to expand your online presence and increase sales. Most importantly, targeted search engine optimization (SEO) strategies ensure you are identified as the local pallet manufacturer that caters to customers who rely on their own versions of scalable AI technology.

Let's talk about it. Schedule a call today!

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