Taking advantage of automation in manufacturing
by George Konidaris, CTO and Co-Founder of Realtime Robotics
The current economic and business conditions in the manufacturing, supply chain and logistics industries necessitate that companies take a long, hard look at automation and see how it can be used to their advantage.
Automation has continued to gain steam worldwide, with much of the renewed interest and growth spurred on by the pandemic. Lockdowns, delays and the need to rethink how work is done and industries operate, combined with an ongoing labor shortage in the industry, have shone a new spotlight on the advantages of automation.
But very few companies can just wake up one morning and decide to automate. There are several mitigating factors to the automation decision that must be considered in order to understand where to start, what to invest in – and what to perhaps stay away from, at least in the early stages.
The first step – as with any large investment – is to plan things out. What this means when considering automation is to take a look at your entire operation and see where automation can help the most. Look for areas where there are repeated or mundane tasks that employees have to deal with. For example, are there actions on the assembly line that could be done by robots, freeing up time for employees to handle more complex tasks? Any task that can best be described by the words repetition, consistency, and simplicity is a good candidate.
Once you have a solid idea of which processes could benefit from automation, and a clear success criterion for each process, then you have a starting point.
Creating a comprehensive ROI model is an important step in the planning process. Above all, you must ensure in this stage that the automation plans make sense from a company ROI standpoint. Is there a return on your investment – and how long will it take to get there? What are the costs to other related parts of your organization? Is it a seamless swap in of an automated tool, or is there a long ramp up period? Do you need to add to or upgrade your infrastructure in order to handle the addition of automation technologies?
Test your model. Does it stand up? Don’t just assume it’s correct (or will always stay that way). Understanding all of these factors and laying out expectations across the company will set the stage for long-term automation success.
Use Your Network
No one likes to be the first to try something new – and there are often questions that pundits, sales brochures and articles like this one don’t have the answers to. This is the time to utilize your network. Investigate what has been done at other, similar sized companies in the industry. Talk to your peers. Ask them about their automation experiences, where they started, how they gained internal champions to the cause, etc. These discussions should help you understand if your models are correct and if you’re on the correct track.
Build vs. Buy
The old adage is that large companies can afford to create their own solutions, while small companies need to buy them. But that really isn’t the measuring stick that decisions should be made by – especially when it’s something as important as investing in automation.
Size and complexity matter and are far more important to consider than the size of your company. There can be complex projects in a small company, and simple ones in a large organization. The question really is: how complex is the automation you have planned, and is it too complex for what’s available off-the-shelf? More likely than not, your organization will need some mix of building and buying.
It is best to start with a pilot program or a small implementation. Build the results that show all of your hard work planning and developing a process was worth it. Show success and ROI – and then be able to lay out how exactly that success can be expanded upon throughout the organization. Nothing beats a skeptic like hard numbers.
One thing to watch out for – even before you get started – is that automation programs can quickly expose data problems within an organization. Bad data in means bad results out; it’s that simple. If your data is low quality (meaning, doesn’t line up with what the actual day-to-day operations of your facility are), then the automation platform won’t be able to keep up with the actual reality you’re placing it in. Expectations will be off, and the initiative will be a failure. Before getting started make sure you review the data you’d be feeding the automation technology – and whether it needs to be updated, or if the way you’d deliver that data to the automation needs to be improved.
The current economic and business conditions in the manufacturing, supply chain and logistics industries necessitate that companies take a long, hard look at automation and see how it can be used to their advantage – both to offset the labor shortage, and to make their organization more resilient to disruptive issues such as the pandemic. But what the conditions do not call for is a rush into the situation. Planning, modeling and understanding your organization’s specific and unique workflow – and where best to automate – will make the difference between success and failure.