Dr. Satyandra K. Gupta: Co-Founder, Chief Scientist, GrayMatter Robotics; Smith Int’l Professor & Dir. CAM USC; Fellow ASME, IEEE, SME, SMA.
AI-powered smart automation has the potential to truly transform manufacturing. People with technical backgrounds are usually interested in exploring smart automation solutions. They are often successful in getting approval to conduct initial pilot studies or develop proof of concept systems. However, many of these efforts fail to transition to production due to a lack of careful planning, underestimation of challenges and not being able to communicate the value proposition.
Here is a list of common mistakes to avoid when deploying smart automation solutions in manufacturing.
Attempting To Closely Replicate Manual Processes
Humans and robots have different capabilities, so an effort to closely replicate a manual process via a robot usually does not work. It is much better to exploit the capabilities of robots and redesign the process to utilize robots’ ability to execute a task precisely, apply higher force and move tools at a much faster speed.
Let us consider the robotic sanding example. Robots can apply much higher forces and hence enable the use of less expensive abrasives and dramatically reduce the abrasive costs. Robots are able to apply consistent force, allowing for more aggressive process parameters without risking part damage and potentially reducing cycle time. Processing consistency might also eliminate some intermediate processing steps and decrease cycle time. Additionally, automation can use tool motions that are impossible for humans to execute due to speed or vibration constraints.
Not Thinking About System-Level Impacts
Typically, a process step that faces quality issues or is challenging from an ergonomic perspective is targeted for automation. Even if this process step can be successfully automated, its overall efficacy can be limited by downstream processing steps.
For example, if a downstream process is inefficient, it will become a bottleneck. Even if the automated process operates at high speed, it will not be fully utilized due to downstream bottlenecks, and hence, it cannot deliver its full value.
Additionally, if the downstream process is manual, then it would neutralize the high quality produced by the automated process. On the other hand, if an upstream process is manual and exhibits significant variability in quality, it can pose a challenge for the automated process. Variability may force the automated process to perform additional work, which could slow it down or result in lower-quality outputs.
Automation often cannot fix quality problems originating from upstream processes. Therefore, when automating a process step, it’s crucial to consider the entire workflow. This may require changes in the overall process flow and system-level optimization to ensure the automated process step can deliver the expected value.
Not Having A Champion To Guide The Automation Journey
Automation solutions rarely deliver full value on the first day. Extracting full value from automation can be an iterative process. Automation inherently requires changes, and changes are hard for most organizations. So, the deployment of automation should be viewed as a journey, and the initial part of the journey may be bumpy because things may not go as planned and there might be unexpected challenges.
Therefore, embracing automation requires patience at the beginning of the journey. Successfully completing the automation journey requires having a champion who truly believes in the long-term value of automation and, therefore, is able to weather the storms along the way and ensure that the small problems do not derail the project. Successfully deploying automation requires careful planning, anticipating challenges and managing risks. Being prepared for challenges, quickly adapting to changes and having a flexible mindset are crucial for successfully completing the automation journey.
Narrowly Focused ROI Calculations
ROI calculations for automation projects often exclusively focus on labor cost savings, and if a proposed automation solution does not appear favorable on this metric, then it is often ruled out. However, this can be a very narrow perspective. It is essential to consider all potential savings from deploying automation. While labor wages are a key factor, other factors must also be considered.
For example, automation can save on consumables in manufacturing, such as using less sandpaper in robotic sanding. Additionally, frequent worker turnover requires constant training of new workers, and therefore, the training costs must be included in ROI calculations. Worker injury risks in ergonomically challenging tasks should also be factored in. Automation can create digital models that significantly benefit downstream processes and enable 100% inspection, adding extra value.
Finally, as the Baby Boomer generation begins to retire, organizations should worry about losing valuable process knowledge. By automating a process, this essential knowledge is preserved within the software, ensuring it remains accessible and protected. Therefore, it is crucial to consider all potential benefits in ROI calculations to make an informed decision.
Not Paying Attention To Workforce Availability And Readiness Issues
Smart automation is often presented as a solution to a labor shortage. Humans are an integral part of the manufacturing process. Extracting the full value of automation requires workers with the right skill sets. For example, human operators may need to interact with automated machines and robotic cells by feeding parts into them or removing parts from them. If they cannot effectively utilize the automated equipment, it cannot deliver value.
For existing workers to perform effectively, the interface to the automation system must be intuitive and simple to use. For example, consider a scenario where a human loads a part into a robotic cell and then instructs the cell to execute the process. In such cases, we cannot expect the human operator to perform robot programming. The robot should be able to program itself with just the click of a button.
Another challenge is the maintenance and servicing of automation technologies. Often, developing in-house talent to maintain automation equipment becomes cost-prohibitive. Alternatively, external service providers can be employed to service the automation equipment. AI-based prognostics and health management (PHM) systems are enabling service providers to remotely monitor and service automation solutions cost-effectively. Workforce availability and readiness issues need to be addressed from the very beginning of the automation project to ensure its success.
Successful deployment of smart automation requires looking beyond technology and considering all relevant operational, business and workforce issues. Having a detailed roadmap for implementing smart automation and getting buy-in from all stakeholders goes a long way toward successfully completing the automation journey.
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