Mike Colby is the head of Logistics Automation at Sick Inc. Colby first joined Sick in 2012 as a director of sales for one of the Factory Automation sales teams and was subsequently promoted to lead Sick's Logistics Automation business in the U.S.
Logistics Automation is focused on helping customers design and optimize their entire logistics chain by automating material flows and making sorting, picking, and warehousing processes faster, more efficient, and more reliable. As the industry embraces the fourth industrial revolution with its digitization and networking of systems and machines, the prerequisite for this communication is an abundance of data, which is what Sick's sensors provide. Colby recently spoke with DC Velocity Editorial Director David Maloney.
Q: How do you view the current state of the supply chain automation market?
A: I view the current state as transitionary. The supply chain automation market is a dynamic space right now as it becomes connected across its enterprise. Everyone involved with material handling (OEMs, end-users, suppliers) is facing new challenges, new technologies, and new expectations. Success in this environment centers not only on meeting customers' expectations, but also on anticipating future needs by designing flexible solutions that will be able to meet the demands of constant change.
Q: What are some of the pain points you've seen customers experience when automating their material flows?
A: With the current labor shortage, companies are considering now, more than ever, automating material flows. But with this decision, several pain points may exist. First, balancing major automation investments against the uncertainty of what tomorrow may bring. Second, when we talk about a connected enterprise across supply chains and the digital world we live in, there can be multiple pain points around how to manage data effectively. Lastly, as new automated systems and processes are implemented, there is a challenge to effectively redeploy the existing workforce into roles that create value in their organizations.
Q: What roles will sensors and the shared data they collect play in growing the Internet of Things and Industry 4.0?
A: Without sensors and the data they provide, there is no Internet of Things and Industry 4.0. Sensors are the eyes and ears of everything going on in the industrial environment at the machine and/or system level. In the past, it was important to realize what's happened in a process. Tomorrow, it will be critical to understand what is going to happen across the entire supply chain network, utilizing artificial intelligence and predictive analytics that rely on sensing data.
Q: How extensive will the growth of artificial intelligence (AI) be over the next five years within distribution centers?
A: I think AI will become part of our everyday lives in the near future. The speed at which this will develop will follow a classic bell curve: Innovators (already utilizing AI today), Early Adopters (just starting), Early Majority (coming soon), Late Majority (TBD), and Laggards (R.I.P.). I think it's critical that organizations embrace technology advancements (i.e., AI) so they can not only survive, but also thrive.
Q: Most supply chain executives see the need for digitalization. But how far along are they in this process?
A: Those who move quickly to digitize their supply chain will gain efficiencies, develop new business models, grow revenue streams, and create competitive advantages for their business. This effort has started and will gain momentum in the midterm.
Q: Are there any particular projects that Sick is working on that you would like to share?
A: Sick is working on a number of new projects outside of our traditional business that are incredibly exciting and will create tremendous value in the Industry 4.0 world. Among the projects we've shown at trade shows are ones that focus on:
- Localization: Indoor GPS that utilizes hardware and software solutions to extract, visualize, and analyze the geo-position of persons, objects, or any other asset that allows process improvement in (mainly) industrial environments.
- Robotics: The safe collaboration between man and machine by combining hardware, software, integration, and visualization competencies.
- Deep Learning/Analytics: Using visualization and sensing to draw conclusions from data in order to communicate to the business, which aids in making better decisions.
