Embracing the Future: How Manufacturing Improvement Approaches Will Evolve in the AI and Digital Age
5 minutes read · 3rd Juni 2024
2024 is the Year for Action
For the past seven decades, numerous improvement methodologies have driven significant advancements in manufacturing operational performance. As we look 15 years into the future, we must consider how these methodologies will evolve in the context of advanced AI and digitalization. Will AI dominate the landscape? Will traditional methodologies become obsolete? Will companies still require an OpEx function?
The individuals who master the integration of new technologies, understanding their strengths and limitations, will spearhead tangible improvements. To envision this future, we must first outline the current improvement processes and examine how they might transform.
Defining the improvement process
To answer these questions, we need to firstly define the different stages of the improvement process.
Detailed Process Understanding:
A fundamental step in any improvement effort is a thorough understanding of each stage of the manufacturing process, including the underlying physics and chemistry. This knowledge is crucial for identifying potential areas for enhancement.
Creating list of Prioritized Opportunities:
The second step requires converting time on the line, data and conversations into opportunities by applying improvement methodologies
Testing Phase:
The testing phase ensures that any proposed changes are safe, maintain high product quality, and are an improvement. This is usually through a mixture of lab and plant trials.
Behavioral change and belief in improvement:
Convincing people that improvement is always possible and fostering a culture of continuous improvement are essential. This step involves overcoming long-standing beliefs and habits.
Sustaining change:
Ensuring that improvements are sustained over time is critical. Without this, the entire exercise of improvement is pointless.
The three buckets of AI and Digitalization
We next need to look at the different types of technology that we expect to see in the next 15 years. Different industries will have different technologies making the largest impact. While we work in a wide variety of industries, for this, we’ll consider the chemical industry. However, we expect a lot of overlap with the pharmaceutical industry.
These AI and digitalization advancements can be categorized into three buckets.
Bucket 1: Improved decision making for leaders
Enhanced visualization, data capture and processing capabilities allow leaders to make better-informed decisions. For example, AI can predict market demands, optimize supply chains and improve planning.
Bucket 2: Digital capital expenditure
Investing in digital and AI technologies can yield a strong return on investment in a similar way to traditional CapEx. For example, predictive AI could be used to predict quality failures early in the testing cycle, increasing testing capacity and saving costs. This is very similar to upgrading the testing machine
Bucket 3: Improvement tools
These tools enhance continuous improvement efforts. As a professional improver, the most exciting advancements to me are those that enable more effective and sustained operational improvements. It is the technologies in this bucket that will have the largest impact on manufacturing improvement approaches.
Technological capabilities for the future manufacturer
If we look ahead, what could chemical plants look like? We see five AI and digitalization capabilities that we think are achievable for manufacturers to include in their facilities in the next 15 years:
Data capture and processing and visualization improvements
There is no shortage of data being collected in chemical plants, however the challenge is processing and visualizing this effectively. AI could be part of the solution. We may also see better data sharing across sites, allowing learnings to be shared across sites. This will generate more opportunities.
Covariate analysis
Improvements in covariate analysis will offer manufacturers the ability to analyze two variables to understand how they interact more easily.
Digital Twins
While Digital Twins may seem like one of the largest buzz words at the moment, it offers huge opportunities. The ability to run trials and value opportunities in the digital space will allow faster progression through the testing phase of implementation.
Defect identification
This offers the capability to leverage improved data that analyzes each individual failure. While this applies more to fast moving consumer goods and pharmaceutical manufacturing, chemicals manufacturers can also benefit. This will add problem solving
AI chatbots
Chatbots aren’t just there to act as a replacement for customer service agents. In manufacturing, AI chatbots can be used to aid in problem solving and provide an easier way of accessing information stored in manuals.
The biggest challenge: Changing people’s behavior
If we look at where these technologies will impact the improvement process detailed earlier, we see a lot of them will help process understanding, opportunity identification and prioritization and also the testing phase.
However, these are not the hardest stages of the improvement process. The hardest stage is changing people’s behavior. Doing something different is uncomfortable and comes with risks. Therefore, people are naturally reluctant to do so.
Despite technological advancements, the most challenging aspect of the improvement journey remains changing people’s behavior. Integrating AI and digital tools effectively requires not just technological adaptation but also a cultural shift within organizations.
Conclusion
To stay relevant in the AI and digital age, current manufacturing improvement approaches must evolve. Leveraging AI and digital advancements will be crucial for staying competitive. Those who can effectively integrate the right technologies will be able to implement more complex improvements faster.
However, the core challenge will persist—changing people’s behavior and fostering a culture of continuous improvement will remain paramount.
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