Plant-wide oscillations are common in many processes. Their effects propagate to many units and may impact the overall process performance. It is important to detect and diagnose the cause of such oscillations in order to rectify the situation. This paper proposes a new procedure to detect and diagnose plant-wide oscillations using routine operating data. A technique called spectral envelope is used to detect oscillations. The variables that have common oscillations are identified and categorized accurately by a statistical hypothesis test. A new index called the oscillation contribution index (OCI) is proposed to isolate the key variables as the potential root cause candidates of the common oscillation(s). Two industrial case studies are presented to demonstrate the utility and practicality of the proposed procedure. (C) 2006 Elsevier Ltd. All rights reserved.