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Success in every factory is still largely built on the knowledge, experience, and intuition of its people. Yet, in an increasingly complex world, relying solely on "Tribal Knowledge" is no longer enough. Organisations must combine this invaluable knowledge with structured data, innovative processes, and adaptive technologies to stay competitive.
In this webinar, Matt Suter from Enblex will show how companies can bridge the critical gaps between data, process, and knowledge, transforming operations into living systems that integrate expert knowledge, adapt to variability, and have the potential to learn and improve continuously.
Key Topics:
1. Â Â Production Uncertainty: Why static systems and isolated lab data fall short in dynamic manufacturing environments.
2. Â Â Tribal Knowledge as Operational Backbone: How experience and intuition fill critical gaps and sometimes delay systematic improvement.
3. Â Â Seeing the Hidden: Best practices to unlock hidden patterns through data analytics and eliminate blind spots with sensing.
4. Â Â Closing the Gaps: Lessons learned in combining data, human expertise, and AI into real-world intelligence beyond theoretical promises.
What you will learn:
How to turn isolated expertise into scalable, data-driven operational knowledge,
How to create agile, knowledge-infused production environments ready for future challenges
How to uncover hidden potential in your operations
How AI can amplify — not replace — human knowledge and understanding
Who should attend:
Operational leaders, quality and process engineers, digital transformation architects, and manufacturing strategists who want to harness both human and digital intelligence to future-proof their operations.
Prepare to rethink what operational excellence means in the Data Age - with systems infused with human and contextual knowledge.
Webinar Summary: Data, Processes, and Human Knowledge in Manufacturing
Philipp Osterwalder, CEO of 1LIMS, welcomes attendees and introduces Matt Suter, CEO of Enblex. The webinar is recorded, and questions can be submitted via chat.
00:05:08 – Webinar Goals
Topics include the importance of tribal knowledge, gaps between data, processes, and people, and using lab data to create precise production parameters. The goal is to integrate human expertise with smart systems.
00:06:34 – Introduction of Matt Suter
Matt Suter, an expert in food engineering and AI, shares his experience in process optimization and how he connects human knowledge with machines and data.
00:12:13 – Connecting Data and Knowledge
Matt emphasizes the need to connect raw materials, labs, machines, and people to ensure consistency in manufacturing.
00:16:41 – The Cost of Missing Connections
Missing connections between lab data and production lead to inconsistent products and rework. Structured, digitalized lab data management can help avoid these issues.
00:18:38 – Formalizing Tribal Knowledge
The knowledge of experienced workers (tribal knowledge) is structured and digitalized to ensure consistent quality and enable automation.
00:22:49 – Application of Fuzzy Logic
Fuzzy logic is introduced as a method to more flexibly and accurately control complex production processes, such as adjusting machine parameters.
00:26:58 – Fuzzy Logic in Action
Example: The use of fuzzy logic in washing machines to adjust wash cycles based on variable parameters.
00:31:41 – The Age of Data and AI
Matt contrasts traditional programming with AI-driven pattern recognition from historical data. AI needs complete datasets to function effectively.
00:35:43 – Connecting People, Processes, and Data
Knowledge graphs and neuro-symbolic AI combine human knowledge with machine learning to create trustworthy, context-aware systems.
00:39:57 – Q&A – Tribal Knowledge and Innovation
Matt explains how to distinguish valuable tribal knowledge from habits that hinder innovation.
00:42:01 – Q&A – Product Applicability and Limits
The formalization of knowledge is applicable not only in the food industry but also across other sectors.
00:45:37 – Q&A – Expert Knowledge and Bias
Matt stresses that expert knowledge must be critically examined and tested to avoid biases.
00:47:29 – Q&A – Gut Feeling vs. Model Performance
Example: An operator noticed an issue the model missed because it ignored important environmental factors (e.g., humidity).
00:50:57 – Q&A – The Future Role of Human Intuition
Matt explains that human intuition will remain essential in guiding and improving AI systems.
00:52:59 – Closing Remarks
Philipp thanked Matt for the insights and encouraged attendees to ask further questions.
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