Unlocking the Power of AI
for Faster Problem Resolution

This scenario is all too common in the chemical and pharmaceutical industries. Very few manufacturing problems are actually new. Traditionally, older, more experienced workers in the facility were a trusted resource when unexpected problems arose: Have you ever seen anything like this before? What did you do about it? How can we avoid having this happen again? This type of institutional knowledge, called tacit knowledge, is invaluable for problem solving. However, with many seasoned employees retiring and newer staff frequently changing jobs, this knowledge is becoming harder to retain and access. The loss of this expertise creates a significant challenge in problem diagnosis and resolution for chemical and pharmaceutical manufacturers.
Where else might employees go to find the answers? Often, clues for solving a particular problem are hidden in historical records such as shift notes, maintenance and inspection logs, and data from the manufacturing execution system (MES) or plant process management (PPM) software. The problem here is that these records are often vast, unstructured, and spread across multiple systems, making it incredibly difficult for employees to locate the specific information they need. Sifting through all this data manually can be time-consuming and inefficient, especially when every minute counts in resolving a production issue. This fragmented approach can lead to delays in problem resolution, resulting in extended downtime, missed production targets, and increased costs.
But what if there were a faster way to access that information and resolve issues? That’s where AI comes in.

New AI tools using machine learning (ML) and natural language processing (NLP) can help employees find the answers hiding in plant data. These AI-driven solutions excel at processing and analyzing vast amounts of data from various sources, such as shift notes, maintenance logs, MES and PPM software, and even unstructured data like emails or informal communications between staff. Using NLP, a Smart Search system can understand queries in natural human language and respond to it—a significant improvement over traditional keyword search systems. Some advanced AI tools, like the ones integrated into Shiftconnector^®, can even suggest potential solutions.

AI systems can also learn and improve over time. With each new data point or resolved issue, the AI becomes better at predicting and diagnosing future problems. This continuous learning capability means that the more the AI is used, the more valuable it becomes to the organization, further enhancing its ability to support operational efficiency.
AI tools can save hours during root-cause analysis and problem resolution. In addition, it can reveal and analyze hidden recurring problems in bottlenecks in production, driving continuous improvement.

Shiftconnector^®, eschbach’s industry-leading PPM solution, now features AI-based Smart Search and Smart Solutions. With these tools, operators, technicians, engineers and QC managers can quickly find historical precedents for current problems, as well as the actions taken and outcomes achieved. This vastly speeds up problem resolution and empowers employees to take mitigating actions to get production back on track. Smart Solutions solves five important problems for manufacturers:

• Finding and extracting valuable historical knowledge hidden in employee-generated shift notes, logs or imported data such as maintenance notifications, including descriptions of problems in materials, equipment or processes and their counteractive measures.
• Structuring knowledge in groups and topics and creating summaries to provide a quick overview of all available data.
• Isolating recurring problems identifying opportunities for continuous improvement.
• Addressing information overload by consolidating and sorting through vast amounts of structured and unstructured data from disparate sources.
• Making information findable and usable at the time that employees need it most with timely solution suggestions that are fully integrated into their workflows.

Smart Solutions uses data from the plant historian and other forms of structured and unstructured data—including data from the time before Shiftconnector was implemented. The AI is trained on industry-, company- and location-specific data so it can deliver results tuned to the facility.
Smart Search and Smart Solutions are now part of Shiftconnector. By integrating AI directly into employees’ Shiftconnector workflows, these tools empower employees and help manufacturers put their historical data to work.
The true power of AI in chemical and pharmaceutical manufacturing lies in its ability to enhance human expertise. By working together, AI and human operators can solve complex problems more quickly and efficiently, ensuring that production stays on track, quality is maintained, and valuable institutional knowledge is preserved.