Minimizing setup: when is it worth it?
In this post, Augusto Pretto, a consulting partner at NEO, discusses Detailed Production Scheduling systems—or Finite Capacity Scheduling—such as Opcenter APS. These systems operate using heuristics parameterized 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 required to prepare a machine, piece of equipment, or production line before starting a new production order or product change. But to what extent is this worth it? Read the following article to find out!
Detailed Production Scheduling systems, or Finite Capacity Scheduling, such as Opcenter APS, operate using heuristics parameterized by priority criteria defined for sequencing. One of the main criteria used by industries is minimizing setups or changeovers, which refers to the activities required to prepare a machine, piece of equipment, or production line before starting a new production order or product change.
But to what extent is this worth it?
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, early production, and even compromise deadline compliance. Minimizing setups is positive only to the point where it supports the business strategy as a whole, rather than just the manufacturing department.
There is an intrinsic logic to reducing changeovers: fewer setups mean less waste, as operations that do not add direct value to the final product are avoided. Furthermore, the efficiency of production resources increases, as more of the available capacity is used for production and less time is wasted on unproductive activities. Consequently, the makespan (the total time required to complete a set of tasks or production orders) tends to decrease, which can positively impact customer delivery deadlines.
On the other hand, avoiding setups at any cost can generate other losses. The two most common are:
- Overproduction: when more than necessary is produced and/or before it is needed, resulting in waste through 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 storage requirements for either intermediate or finished products. In this scenario, although productivity indicators, such as the performance pillar of OEE (Overall Equipment Effectiveness), may show improvement, other indicators like OTD (On-Time Delivery), Days of Inventory, and Inventory Turnover tend to worsen. OTD is compromised by failing to produce what was needed at the right time; days of inventory increase by producing volumes without forecasted consumption; and inventory turnover automatically decreases.
To understand to what extent it is worth avoiding setups, it is essential to analyze the company's strategic objectives and the indicators that measure their achievement—always with a focus 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 decisions regarding setups are made for the benefit of the whole, rather than specific areas.
As an example, we can consider generic objectives common to any industry: delivering products on time, with quality, and in the expected quantityTherefore, setups should only be avoided to the extent that they do not compromise these objectives.
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Production planning and scheduling 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 production and strategic criteria, supporting decision-making through the parameterization of sequencing heuristics and the definition of minimization and maximization criteria, which enable the generation of countless sequencing scenarios in just a few minutes.
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