Production Data Must Reach Engineering Before Manufacturers Can Fix Recurring Defects
A recurring production defect creates two decisions for a manufacturer: how to keep orders moving today, and whether the underlying product or process needs to change. Shop-floor data can help identify the problem, but approving a design change requires a connection between what happened in production and the product configuration involved. Without that connection, an engineering team may have evidence of a failure without enough context to determine what should be changed.
Sergio Viera Velasco, Territory Manager North America at CONTACT Software, identifies that connection as a central requirement for turning production information into engineering decisions. His comments address both the information that needs to reach engineering and the measures manufacturers can use to assess whether a subsequent change reduces defects.
Connect the defect to the design revision
“The MES captures relevant production and quality data, such as machine parameters, process deviations, defect rates, and affected production orders,” Viera Velasco said. “Through the Digital Thread, this information can be directly linked to the corresponding product structures, components, and design revisions in the PLM system, providing a solid foundation for engineering decisions.” The distinction matters because a defect rate describes the scale of a problem, while the connection to a component, revision or affected order helps establish its context. For an engineering review, both are relevant.
Viera Velasco also recommends consolidating the information rather than leaving production and engineering teams to reconstruct the relationship across separate records. “It is helpful to collect and consolidate relevant data from production and operations in centralized data objects, as this simplifies the closed-loop approach,” he said. He cited CONTACT Elements’ dedicated “Insights” data objects as the company’s approach to feeding shop-floor information back to engineering. The operational requirement is that evidence collected during production remains connected to the product information needed to evaluate a change.
Measure what happens after the change
Connecting systems is only part of the task. Manufacturers also need a way to assess whether the resulting design or process change improves production outcomes. Viera Velasco recommends starting with a measure directly tied to the recurring problem: “I would recommend starting with the Rework Rate.” This gives the review a practical focus on whether fewer products require additional work after the intervention.
“First Pass Yield (FPY) is another useful metric, measuring the rate of products that pass without defects on the first attempt,” he added. “It is particularly valuable to compare these metrics before and after implementing a design or process change.” His proposed test is whether the intervention produces fewer defects and less rework. A completed engineering change therefore marks the point at which its operational effect can be assessed, rather than establishing that the problem has been resolved.
Production improvement and delivery readiness are different tests
Reducing rework can address a production constraint, but it does not establish whether finished stock is positioned to meet customer demand. In earlier coverage by The Supply Chainer on retail peaks, Shibu Sasidharan, Senior Vice President of Strategy and Growth at Exol, described that separate limitation: “You can have plenty of stock available, but if it’s sitting hundreds of miles from where customers are placing orders, you will pay for it in transportation costs and longer delivery times.” His comments concerned fulfillment networks rather than engineering changes. They underline why a production-quality measure and a delivery-readiness measure answer different operational questions.
For manufacturers investigating recurring defects, Viera Velasco’s comments establish a sequence: capture the production evidence, connect it to the relevant product and design records, and compare quality outcomes after the change. Engineering needs enough context to assess the intervention, while operations needs evidence that it worked. The value of the digital thread becomes measurable when that connection supports a change that reduces the work required to produce an acceptable product.
