AI-powered smart automation is a pivotal advancement in manufacturing. With this, manufacturers can undergo immensely valuable transformations, such as the elimination of ergonomically challenging physical labor, which not only improves the quality of parts that workers produce, but also their overall quality of life. However, with great power comes great responsibility– and a lot of planning. The decision to deploy an AI-powered smart automation system is a step in the right direction, but the journey from that point forward is often challenging. Pilot studies and proof of concept systems often cannot transition to real deployment without a combination of careful planning, understanding the depth of their challenges, and clear communication of the value proposition or what to expect. So many organizations fail to exploit the benefits of smart automation.
Here are the five common mistakes to avoid when deploying smart automation solutions in manufacturing:
- Attempt to Closely Replicate Manual Processes and Miss out on Innovation Opportunities Enabled by Automation: Humans and robots have different capabilities so an effort to closely replicate a human process by a robot usually does not work. It is much better to exploit the capabilities of robots and redesign the process in ways that use robots’ ability to execute a task precisely, apply significantly higher force, and move tools at much faster speed. Robotic automation allows for significant improvements in process performance. 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 hence 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, slowing it down, or resulting 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 the full value on the first day. Extracting full value from the automation can be an iterative process. Automation inherently requires changes, but for most organizations, change is hard. 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 from the beginning of the journey to the end. 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 the 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 the labor shortage. However, humans are an integral part of the manufacturing process. To get the full value of automation, you need 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 in a cost-effective manner. Workforce availability and readiness issues need to be addressed from the very beginning of the automation project to ensure its success.