Most often, the manufacturing engineers already have a sense of where they want to utilize robots within their facility. Many can readily describe the ideal applications and likely candidates, namely those that pose safety risks, are highly repetitive, labor intensive or too slow.
Despite high awareness, many automation projects struggle to get off the ground. To help assuage apprehension, I often encourage teams I work with to keep the following top of mind as they consider embarking on their automation journey.
Dream Big, but Start Small
Deploying automation is often a multiyear process. For manufacturing engineers tasked with delivering on a broad Industry-4.0 mandate, it can be daunting to know where to begin. Almost always, the best first step is to start small and deliver a quick win. Picking an “easy” robotic application that immediately solves a pain point, no matter how big or small, is critical to building momentum and allows the organization to learn.
Clearly Define the Metric for Success
Another good starting point for any automation idea is to first quantify the impact. What is the KPI that automation will improve? Ultimately, all robotic projects should deliver a quantifiable improvement toward the overall site goals. Defining the parameters and expectations in advance of scoping the projects can help prioritize opportunities and level-set in internal funding reviews.
Simplify, Then Automate
A common challenge for robotic projects is variation. Some teams spend weeks investigating projects only to find that, in the end, the idea is too costly to automate due to the high number of variants. Other times, teams will de-prioritize potentially great ideas too early because an initial survey deems the sequence of operations too complex. However, many perceived challenges to automation can be solved by looking upstream. Are there elements of the product design that can be changed to improve manufacturability? Can prior manufacturing steps be modified to make robotic applications downstream easier? Before trying to automate a suboptimal and unnecessarily complex process as-is, look for ways to simplify in-station and upstream.
Many robotic projects rely on integrator partners to support the engineering, sourcing and implementation activities. When external vendors are involved, there is an information asymmetry between the two parties. This can manifest in many ways, but a common symptom is an inaccurate scope of work, which leads to risk for all parties. To mitigate the concerns, it is helpful for all parties to recognize both teams are learning as the project evolves. Striving for transparency throughout the quoting, design and engineering processes helps eliminate surprises for all and ensures the group’s collective success.
Plan for Change
As companies assess opportunities to deploy automation, it is helpful to analyze change through multiple lenses. The most intuitive lens often focuses on the manufacturing process itself. For example, many companies have line of sight into future model changes and can account for flexibility during the design phase. However, it is also important to view the automation through a wider lens. How does the automated work cell change upstream or downstream processes? How are day-to-day roles for operators affected? What type of training programs should be created?
While not exhaustive, thinking through the above can help engineers assess automation projects from multiple points of view. Ultimately, I am excited to see how advances in technology, in the field of robotics and more broadly within our industrial manufacturing industry, will unfold. As companies continue to embrace automation, robotics or other novel manufacturing processes, I look forward to helping create the next era of “How It’s Made.”
About the Author
Jeff Chu leads factory of the future consulting at Eckhart, an Industry 4.0 solutions provider that supports some of the largest manufacturing operations in the world. Chu has consulted for Fortune 500 clients across multiple industries and end markets on topics including robotics, factory flow and operations management. He graduated from the University of Michigan and has an MBA and master’s degree in engineering from MIT. Chu is a member of SME’s Chicagoland chapter.