2025/04/10 by Mateus do Rego Ferreira Lima, Mateus José do Rêgo Ferreira Lima, Elliot Bendoly +2 · 7 citations
Decision Sciences · Engineering · Health Professions · #Quality and Safety in Healthcare #Reliability and Maintenance Optimization #Risk and Safety Analysis
paper · doi:10.1002/joom.1366
openalex publication_date 2025/04/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/22
ABSTRACT Condition‐based preventive maintenance (CB‐PM), dependent on robust and precise indicators of equipment quality, stands to gain advantages from the integration of sensor technologies. Yet, the effectiveness of such systems relies on an important factor: people. Even in possession of ideal CB‐PM policies, imperfect adherence can lead to higher equipment downtime, maintenance costs, and increased safety hazards. Here, we describe a normative model of optimal CB‐PM policy determination; specifically, a generalized means by which to determine a valuemaximizing quality threshold as a guideline for triggering PM (preventative maintenance). Motivated by field data, we consider the opportunity cost of not adhering to such optimal policies; that is, premature or delayed responses. We design and execute a controlled laboratory study, exposing participants to two critical manipulations that we theorize might influence adherence: (1) The presence of a supplemental secondary signal, of a type common to time‐based preventive maintenance (TB‐PM), (2) a pre‐task priming intended to emphasize the value of discretized task completion. Results showed that the combination of CB‐PM and TB‐PM signals, along with completion priming, significantly increases adherence to CB‐PM guidelines. We demonstrate that individuals exposed to this combination of treatments forfeit far less value than those receiving CB‐PM signals alone.