Setup Reduction: How Much Is Too Much?

In this post, Augusto Pretto, a consulting partner at NEO, discusses Detailed Production Sequencing Systems, or Fine Production Scheduling, such as Opcenter APS, which operate using parameterized heuristics based on defined priority criteria for sequencing. One of the main criteria used by industries is the minimization of setups or changeovers, which refer to the activities necessary to prepare a machine, equipment, or production line before the start of a new production order or product change. But to what extent is this worthwhile? Read the following article and find out!

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April 10, 2025
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Setup Reduction: How Much Is Too Much?

Detailed Production Sequencing Systems, or Fine Production Scheduling, such as Opcenter APS, operate using parameterized heuristics based on priority criteria defined for sequencing. One of the main criteria used by industries is the minimization of setups or changeovers , which refer to the activities necessary to prepare a machine, equipment, or production line before the start of a new production order or product change.

But to what extent is it worthwhile?

From one perspective, minimizing setups reduces losses associated with unnecessary operations and lead time (the total time from order placement to product delivery). However, this practice can also lead to increased inventory, premature production, and even mes deadlines. Minimizing setups is only positive to the extent that it benefits the overall business strategy, and not just the manufacturing sector .

There is an intrinsic logic in reducing changeovers: the fewer setups, the less waste—since operations that do not add direct value to the final product are avoided. Furthermore, the efficiency of productive resources increases, as more of the available capacity is used in production, and less time is wasted on unproductive activities. As a result, the makespan (total time required to complete a set of tasks or production orders) tends to decrease, which can positively impact delivery times to the customer.

On the other hand, avoiding setups at all costs can lead to other losses. The two most common are:

  • Overproduction : when more is produced than necessary and/or produced before it is needed, resulting in losses due to anticipation;
  • Excessive inventory : when the production or purchase of materials exceeds actual demand.

To avoid setups, it is common to anticipate the production of certain products, which leads to inventory accumulation, premature resource consumption, and the need for storage, whether of intermediate or finished products. In this scenario, although productivity indicators, such as the OEE (Overall Equipment Efficiency) performance pillar, may show improvement, other indicators such as OTD (On-Time Delivery), Inventory Days, and Inventory Turnover tend to worsen. OTD is compromised by failing to produce what was needed at the right time; inventory days increase by producingmes without anticipated consumption; and inventory turnover automatically decreases.

To understand to what extent it is worthwhile to avoid setups, it is essential to analyze the company 's strategic objectives and the indicators that measure their achievement—always focusing on long-term sustainability. It is worth remembering that good local results do not always represent a healthy business aligned with the global strategy. This reinforces the importance of a horizontal analysis of business processes, so that the decision about setups is made for the benefit of the whole, and not specific areas.

As an example, we can consider generic objectives common to any industry: delivering products on time, with quality, and in the expected quantity . Therefore, setups should only be avoided to the extent that they do not compromise these objectives.

Production planning and sequencing solutions like Opcenter APS offer agility, flexibility, and robustness in generating information and supporting decision-making. They allow for an intelligent and effective balance between productive and strategic criteria, supporting decision-making through the parameterization of sequencing heuristics and the definition of minimization and maximization criteria, enabling the generation of numerous sequencing scenarios in just a few minutes.

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