FOCUS ON WORKFORCE
workflow. That information feeds back into the digital thread for compliance tracking, quality analysis and continuous improvement. When you combine that feedback with the engineering systems upstream, you create a closed loop where the same product data that designed the part also guides manufacturing, supports field service and captures real-world insights that flow back into engineering. The digital thread stops being a pipeline and becomes a living system.
Smart factories need connected knowledge, not just connected machines. In practical terms, closing the knowledge gap requires rethinking how instructions are created, structured and delivered.
1. First, connect to the source. Instructions and procedures should originate from engineering data, not from someone manually recreating content in a separate system. When the instruction is linked to the product definition, accuracy improves and maintenance becomes sustainable. When designs change, the instructions reflect those changes because they originate from the same source. For environments where engineering change orders are frequent, this connection eliminates the lag between what engineering specifies and what the floor executes.
2. Second, capture expertise before it walks out the door. Use modern tools, including AI, to help experienced workers capture their knowledge in structured, visual formats. AI is a powerful co-pilot here. It can analyse legacy documents, service manuals and even videos of experienced workers performing procedures, then generate structured instructional steps. But the experts must stay in control of validation and refinement. AI drafts; humans approve. For safety-critical work, that human-in-the-loop is non-negotiable.
3. Third, deliver the right knowledge to the right person at the right moment. Enterprise systems like PLM and MES manage enormous operational complexity, but their interfaces were never designed to guide individual workers through specific tasks. A visual execution layer sits on top of those systems and translates operational data into instructions that workers can follow with confidence.
Critically, this layer should adapt to the person and the situation. A new worker performing a procedure for the first time needs complete step-by-step guidance. A veteran running a familiar job needs the summary: what is different this time, what changed in the design and where the critical quality or safety checks fall. Think of it as the difference between reading the full manual and getting a briefing on what matters right now. The veteran does not want to wade through instructions they already know. They want the essential information for this specific job, delivered clearly, and nothing more.
The system can also introduce intentional moments of friction when something important has changed. A new safety step, a revised specification, a design change that affects the procedure. Instead of burying that change in a document update the worker may never read, the instruction highlights it and requires acknowledgment before the work proceeds. That kind of targeted attention is impossible when every worker receives the same generic document, regardless of experience or context.
4. Fourth, close the loop. Workers should not only receive instructions. They should be able to capture feedback, inspection results, performance data and confirmations directly within the
The most important node on the factory floor
The manufacturing sector will need more workers in coming years, not fewer. Reshoring initiatives, infrastructure investment and increasingly complex product architectures are all increasing demand for skilled labour at a moment when the existing workforce is ageing out. The organisations that thrive will be the ones that use AI and modern platforms to make every new worker more capable from day one: capturing wisdom before it disappears, structuring it into guidance from which the next generation can learn and delivering it at the moment of execution.
The new generation of manufacturing workers grew up with interactive technology. Give them the right tools and they will perform. Hand them a binder and they will leave.
The industry has spent two decades connecting machines, systems and data streams. That investment was necessary and valuable. But the most important node in any factory is not a machine, it is the person standing in front of one. The technology to close the knowledge gap exists today. The bottleneck was never about processing power, automation or data. It was always about getting the right knowledge to the right person at the right moment. Solve that, and everything else the industry has built will start delivering its full value. n
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AI can be a useful tool.
26 | ismr. net | ISMR June 2026