According to manufacturing consultant Mark Woeppel, many plants are now caught in a cycle of missed deliveries, part shortages and constant expediting, not because they lack effort, but because their systems are fundamentally misaligned with how production actually works.

“I get called when somebody has a problem,” says Woeppel, who has spent more than 30 years improving manufacturing operations. “They’re missing delivery dates… customers are crying, and in some cases threatening to pull business for missing dates. At the same time, the plant is spending significant money just to keep the line moving.”

That disconnect often shows up physically on the factory floor. In one case, a fire truck manufacturer had dozens of partially assembled units sitting idle, waiting for missing components. To keep production moving, workers would strip parts from unfinished units to complete others, creating what Woeppel describes as a cycle of “doom” that reinforces delays rather than solving them.

Similar conditions exist in more complex assembly environments. At an aerospace supplier, incomplete assemblies were shipped downstream with the expectation that missing work would be completed later. The result was a fragmented production process driven by urgency instead of coordination.

At the root of these problems is a lack of synchronization between supply and assembly. When parts do not arrive in alignment with production needs, manufacturers compensate by expediting orders, adding labor or constantly shifting priorities. Over time, those actions create more instability rather than less.

“In most assembly plants, the biggest problem is not being able to synchronize the supply chain with the assembly operation,” Woeppel explains. “When that breaks down, everything else starts to follow.”

Many manufacturers attempt to solve the issue by adding inventory at the line or implementing replenishment systems based on average lead times. While those approaches can provide temporary relief, they often fail under real operating conditions.

“A four-week lead time sounds precise, but it’s just an average,” Woeppel says. “And averages always have variation. That variation is what causes the system to fail.”

When suppliers fall behind or internal production is disrupted, those fixed assumptions break down. Buffer stock is quickly depleted, triggering emergency responses across the plant. Companies assign expediters to track parts, create additional planning layers and introduce new priority systems to manage the chaos.

The result is a reactive environment with conflicting signals. Production teams are forced to change setups, shift schedules and respond to constantly changing priorities. Instead of improving delivery performance, the system becomes less predictable.

“You end up with multiple priority systems layered on top of each other,” Woeppel says. “At that point, nobody really knows what the true priority is.”

The underlying issue, he adds, is that manufacturers are trying to manage a variable system with fixed assumptions.

“We build deterministic plans for a system that is inherently probabilistic,” Woeppel says. “We expect everything to happen on a specific date, but in manufacturing, things change.”

To address that challenge, Woeppel advocates applying the Theory of Constraints, a methodology developed by Eliyahu Goldratt. The approach focuses on identifying the system’s constraint: the resource that limits overall output; and then aligning all production activities around it.

In one early application, Woeppel implemented a scheduling system centered on a motor winding operation, which was the slowest and most capacity-constrained step in production. By synchronizing all work to that constraint, the plant stabilized its output and improved delivery performance.

“The constraint determines what leaves the plant,” he says. “Once you align everything to that, the system starts to behave much more predictably.”

Similar results were achieved in other facilities, including a steel fabrication plant where throughput increased significantly while overtime was reduced.

While the concept is straightforward, implementation requires a shift in mindset. Rather than focusing on individual efficiencies or local improvements, manufacturers must consider how each part of the system supports overall flow.

In assembly environments, that challenge is compounded by product variability. Many operations are configure-to-order, meaning final specifications are not known until late in the process. At the same time, production lines are highly capital-intensive and depend on consistent flow to remain efficient.

“You can have thousands of part numbers feeding a single assembly line,” Woeppel says. “And you may not know the exact configuration until close to final assembly.”

Without a system designed to absorb variability, those conditions lead to recurring disruptions. Shortages trigger expediting. Expediting creates conflicting priorities. And those conflicts reduce overall efficiency.

Breaking that cycle requires moving away from rigid schedules and toward systems that account for variability. The Theory of Constraints provides a framework for doing that by focusing attention on system-level performance rather than individual tasks.

As manufacturers continue to reassess inventory strategies and production methods, that perspective is becoming increasingly relevant. The challenge is not simply how much inventory to carry, but how to maintain production flow despite constant variation.