• Written by Sonali Subhadarsini, Product Manager

A shift supervisor at a chemical plant spends a significant amount of time reviewing production data, checking for yield drift and feedstock variability, to ensure the plant operates within tight safety envelopes. This attention to detail is critical, as even small deviations can impact product quality and safety. However, this time-consuming process can be optimised, and the supervisor's time can be returned to more strategic tasks, such as process improvement and optimisation.

Unique challenges in chemicals

The chemicals industry poses unique challenges when it comes to implementing AI-powered productivity solutions. Yield drift, feedstock variability, and plant-to-plant recipe differences can all impact production efficiency and product quality. For instance, a category manager may need to compare different suppliers of raw materials, taking into account factors such as cost, quality, and availability, to ensure the plant receives the best possible inputs. This complexity can make it difficult to identify areas where time can be saved and redeployed.

A plant manager, for example, may need to adjust production recipes on the fly to account for changes in feedstock quality, which can be a time-consuming and manual process. Additionally, the need to maintain tight safety envelopes means that any changes to production processes must be carefully evaluated and implemented, which can further limit the potential for productivity gains.

Time saved vs time redeployed

While AI-powered solutions can certainly save time in the short term, the real benefit comes from redeploying that time to more strategic tasks. A shift supervisor who no longer needs to spend hours reviewing production data can instead focus on identifying areas for process improvement, or developing new production recipes. This redeployment of time can have a much greater impact on productivity and efficiency than simply saving time.

However, this requires a mindset shift, as many people assume that saving time is the ultimate goal. In reality, saving time is only the first step, and it is what you do with that saved time that really matters. By redeploying saved time to more strategic tasks, organisations can achieve greater productivity gains and improve overall efficiency.

Overstating the effect

Self-reported time savings often overstate the effect of AI-powered productivity solutions. This is because people tend to focus on the time saved in the short term, rather than the longer-term benefits of redeploying that time. A category manager may report that they have saved several hours per week using an AI-powered solution, but fail to account for the fact that they are now using that time to focus on more strategic tasks, such as supplier development and negotiation.

This can lead to unrealistic expectations and a lack of understanding of the true benefits of AI-powered productivity solutions. By taking a more nuanced view of the benefits, organisations can better understand how to achieve real productivity gains and improve overall efficiency. You can learn more about how AsscherAi can help your organisation achieve these gains by visiting our website at www.asscherai.com.

Tasks worth removing first

When it comes to implementing AI-powered productivity solutions, it is often best to start by removing tasks that are repetitive, manual, and time-consuming. A shift supervisor who spends hours reviewing production data, for example, may be able to automate this task using an AI-powered solution, freeing up time for more strategic tasks. By removing these tasks first, organisations can quickly achieve productivity gains and improve overall efficiency.

Additionally, by removing these tasks, organisations can also reduce the risk of human error, which can be a major factor in production inefficiencies. A plant manager, for example, may be able to use an AI-powered solution to automate quality control checks, reducing the risk of defective products and improving overall product quality. To learn more about how AsscherAi can help your organisation remove these tasks and improve productivity, you can contact us at www.asscherai.com/contact-us.

Limitations and wrong choices

While AI-powered productivity solutions can be highly effective in certain contexts, they are not always the right choice. In situations where production processes are highly variable or unpredictable, for example, AI-powered solutions may struggle to keep up. In these cases, more traditional approaches to productivity improvement may be more effective.

Additionally, AI-powered solutions may not be suitable for organisations that lack the necessary infrastructure or expertise to support them. A plant manager who lacks experience with AI-powered solutions, for example, may struggle to implement and maintain these systems, which can limit their effectiveness. By understanding the limitations of AI-powered productivity solutions, organisations can make more informed decisions about when and how to use them.