Five Steps To Get Started With Robotic Automation

Kel Guerin Kel Guerin
July 17, 2020 AI & Machine Learning

This past summer, McKinsey reported that 88% of businesses want to implement more robotic automation. However, it’s hard to know where to start, because planning and implementing that automation project can seem daunting. What processes in my plants should I automate first? How do I calculate my ROI? How do I handle high-mix, low-volume processes? How will my workers react? 

If you are an enterprise or conglomerate, things are even more complex. Which parts of my business are most conducive to automation? How do I replicate successes across my entire organization?

These are the questions that many business owners and stakeholders have asked me, everyone from tier-one automotive suppliers to 10-person machine shops, from small businesses to Fortune 100 enterprises. Here are the five steps I share with them to make their automation rollout smooth, cost-effective and repeatable.

1. Find The Low-Hanging Fruit

When looking for opportunities to automate, companies often gravitate to the most difficult tasks. The rationale behind this is simple: Automation can be complex and time-consuming; therefore, companies look for the highest-reward applications that are “worth the effort.” What I tell my clients is that the processes they should look to automate:

• Are low in complexity.

• Underuse people.

• Cause bottlenecks in production.

• Involve dull, dirty or dangerous work.

Whenever I visit a factory, I say the same thing: Show me a relatively simple process where a worker is spending more than half their time waiting for another process to finish, or where production is being bottlenecked by the availability of labor, or where that worker is constantly in reach of heavy machinery, and we should talk about automation.

2. Automate Incrementally

There is value in the large-scale automation of processes, but usually, a production process is a mix of menial, relatively simple, repetitive tasks and complex tasks that require significant worker knowledge and expertise. It is a mistake to try to automate this entire process because automating the tasks that require significant expertise will inevitably require a huge investment in time and money.

Instead, a better approach is to find the easy-to-automate tasks of that larger process and start with those. If after you have succeeded in those initial tasks you expand the scope of automation, you can do so incrementally.

3. Focus On Your People

Whenever I visit a factory, I ask the same questions about each process I see: How long does the process take, and how much time does a worker spend doing that process?

Take machine tending as an example, where a worker takes a few seconds to place raw material in a machine that then takes time to process that material (through material removal, heat, pressure, etc.). When the machine is done, the worker removes the finished part. Now, if that process takes 10 minutes, then chances are that worker is tending many of those machines or has a different task to do during the intervening time.

However, if the process takes less time, then the worker may not be able to leave that work station. This means that with automation, there may be an opportunity for that worker to do more value-add tasks that leverages other skills of that worker.

4. Aim For 80%, And Iterate

Being agile is not an excuse for delivering something that doesn’t work. The 80% solution has to provide value and an acceptable ROI, but it also doesn’t have to be perfect. The mantra here needs to be “My automation solution must provide an acceptable amount of value over the nonautomated process, and then I can improve that over time.” This allows you to extract value out of your automation system immediately before it is perfect, and then reap greater rewards as that project goes through continuous improvement.

5. Advertise Your Success

Once you’ve been successful at automating your first process, it becomes easier to automate your next task. In my experience, most low-hanging-fruit tasks are not unique, and by automating one instance of that task, you’ve likely created a template for automating more tasks throughout your factory or even your company.

The key, though, is to advertise your success to the rest of your organization so the automation benefits can be replicated. Once you create buy-in around a solution, with concrete evidence about its positive effects in the business, the rest of your organization will be chomping at the bit to copy it.

Don’t Wait; Dive In

The hardest part of most projects is taking that first step. I have used these five steps to help many manufacturers begin their automation journey, starting from their first cell and building up to entire automated lines. Don’t wait until you have a master plan — be agile. Kick things off today by looking for that first low-hanging project, and use it as a quick win to act as the foundation for your widespread automation success.

  • Experfy Insights

    Top articles, research, podcasts, webinars and more delivered to you monthly.

  • Kel Guerin

    Tags
    BusinessesImplementRobotic Automation
    Leave a Comment
    Next Post
    Remote Work is Surprisingly Productive, But For Many… Something Is Missing

    Remote Work is Surprisingly Productive, But For Many… Something Is Missing

    Leave a Reply Cancel reply

    Your email address will not be published. Required fields are marked *

    More in AI & Machine Learning
    AI & Machine Learning,Future of Work
    AI’s Role in the Future of Work

    Artificial intelligence is shaping the future of work around the world in virtually every field. The role AI will play in employment in the years ahead is dynamic and collaborative. Rather than eliminating jobs altogether, AI will augment the capabilities and resources of employees and businesses, allowing them to do more with less. In more

    5 MINUTES READ Continue Reading »
    AI & Machine Learning
    How Can AI Help Improve Legal Services Delivery?

    Everybody is discussing Artificial Intelligence (AI) and machine learning, and some legal professionals are already leveraging these technological capabilities.  AI is not the future expectation; it is the present reality.  Aside from law, AI is widely used in various fields such as transportation and manufacturing, education, employment, defense, health care, business intelligence, robotics, and so

    5 MINUTES READ Continue Reading »
    AI & Machine Learning
    5 AI Applications Changing the Energy Industry

    The energy industry faces some significant challenges, but AI applications could help. Increasing demand, population expansion, and climate change necessitate creative solutions that could fundamentally alter how businesses generate and utilize electricity. Industry researchers looking for ways to solve these problems have turned to data and new data-processing technology. Artificial intelligence, in particular — and

    3 MINUTES READ Continue Reading »

    About Us

    Incubated in Harvard Innovation Lab, Experfy specializes in pipelining and deploying the world's best AI and engineering talent at breakneck speed, with exceptional focus on quality and compliance. Enterprises and governments also leverage our award-winning SaaS platform to build their own customized future of work solutions such as talent clouds.

    Join Us At

    Contact Us

    1700 West Park Drive, Suite 190
    Westborough, MA 01581

    Email: support@experfy.com

    Toll Free: (844) EXPERFY or
    (844) 397-3739

    © 2023, Experfy Inc. All rights reserved.